Room-Temperature Superparamagnetic FeCu Nanoalloys: Insights into Magnetic Behavior from Synthesis and Simulation

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Jafar Hoseini, Mohammad Hadi Ghatee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6141115/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Jun, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Bimetallic nanoalloys combining magnetic and noble metals are promising for applications in magnetic sensors, catalysis, optical detection, and biomedical imaging. Their development relies on understanding morphology, electronic structure, and crystallography. This study explores iron-based magnetic nanoalloys using efficient synthesis and advanced characterization. Molecular dynamics (MD) simulations examined atomic-scale morphology and structural features, linking them to magnetic behavior. A spin-lattice dynamics algorithm simulated iron-copper (FeCu) nanoalloys of varying sizes and compositions. FeCu nanoalloys were synthesized via a one-step reduction reaction and analyzed using multiple techniques, yielding nanoparticles with high saturation magnetization and an 11 nm average size. Simulations and experiments confirmed core-shell (CS) and Janus morphologies, where copper shells an iron core. Findings suggest that composition, rather than morphology alone, predominantly influences magnetic properties, while the core-shell morphology enhances oxidation resistance due to the noble copper metal employed. This study is the first to integrate the spin-lattice algorithm with experimental analysis, providing consistent insights into design and accurate characterization. Thus, it confirms the practical and novel synthesis of low-size FeCu nanoparticles with exact ideal superparamagnetic properties—exhibiting no hysteresis—suitable for various research and industrial applications. Physical sciences/Chemistry Physical sciences/Energy science and technology Physical sciences/Materials science Physical sciences/Mathematics and computing Physical sciences/Nanoscience and technology Core-shell and Janus FeCu nanomaterial synthesis Magnetization spectrum Molecular dynamics simulation Nano superparamagnetic Spin-lattice dynamics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 1. INTRODUCTION Nanoparticles (1–100 nm) are key to nanotechnology, exhibiting unique properties due to their small size, large surface area, and quantum effects. These traits enable advanced applications in medicine, electronics, energy, and environmental science, surpassing bulk materials. Their high surface-area-to-volume ratio boosts chemical reactivity and catalysis, while quantum effects influence conductivity, magnetism, and optics. The class of magnetic nanoparticles (MNPs) has distinct properties shaped by size, uniformity, surface area, and biocompatibility. By adjusting synthesis parameters, traits like superparamagnetism and adsorption kinetics can be tailored for applications in biology, catalysis, data storage, spintronics, sensors, and MRI contrast [ 1 – 10 ]. Their large surface area enhances superparamagnetism, making MNPs a dynamic focus of theoretical and experimental nanoscience research. These MNPs are classified as diamagnetic, paramagnetic, ferromagnetic, ferrimagnetic, or antiferromagnetic based on magnetic dipole interactions. Among them, superparamagnetic nanoparticles, which exhibit zero magnetization in the absence of an external field, are particularly useful in drug delivery and MRI enhancement. Since they do not retain magnetization once the field is removed, interparticle attraction is eliminated, influencing surface properties and biological applications. Their high sensitivity to magnetic fields allows precise control over their behavior. Controlling MNP size and morphology is essential for tailoring their physicochemical properties. Reaction parameters must be carefully adjusted to achieve desired size distributions [ 11 , 12 ]. For example, nanoparticles below the single-domain limit (~ 20 nm for iron oxide) often exhibit superparamagnetism at room temperature, making them valuable for ferrofluids, data storage, and medicine [ 11 , 12 ]. Nanoparticle size significantly impacts properties such as coercivity, magnetization, and magnetic structure, which are shaped by intrinsic composition and surface effects. Below 20 nm, thermal fluctuations typically prevent permanent magnetization [12,13,]. For example, ε-Fe₂O₃ nanoparticles transition from ferromagnetic to superparamagnetic around 6 nm due to surface effects and weakened exchange interactions. Larger particles (~ 20 nm) exhibit higher coercivity than smaller ones (~ 6 nm) due to an increased surface-to-volume ratio, impacting magnetic stability and ordering [ 11 , 14 ]. At temperatures higher than room temperatures, thermal energy overcomes magnetic interactions, reducing effective magnetization, particularly in smaller nanoparticles, where high surface-to-volume ratios amplify thermal fluctuations [ 13 , 15 , 16 ]. In magnetic alloys, exchange coupling between core and shell atoms affects magnetic properties. This coupling, arising from atomic magnetic moment interactions, results in diverse magnetic behaviors based on materials and structure. Differences in atom arrangement and cooling rates during synthesis yield varied phase diagrams and thermal behaviors [ 13 , 17 ]. Magnetic bimetallic nanoparticles (MBNPs) offer enhanced properties over monometallic particles due to synergistic effects between two metals, improving magnetic response for applications like magnetic separation and targeted drug delivery. MBNPs enable efficient separation from solutions via external magnetic fields, which is critical for catalytic processes and environmental remediation [ 7 , 8 ]. Core-shell interactions in MBNPs lead to diverse exchange coupling mechanisms, with differences in atomic number and coupling type (core vs. shell) influencing thermal stability and magnetic behavior [ 13 ]. Notably, core@shell nanoparticles exhibit stability against oxygen, water, and chemicals. Copper and iron combinations yield multifunctional nanoparticles with high catalytic activity and ferromagnetic properties, enabling magnetic separation from reaction systems [ 18 ]. Bimetallic FeCu nanoparticles, made from cost-effective metals, exhibit notable magnetic properties despite the immiscibility of iron and copper. These alloys are traditionally produced via vapor deposition and mechanical alloying [ 9 , 10 ], balancing iron's magnetism with copper's diamagnetic behavior. Despite synthesis challenges like oxidation, FeCu nanoparticles offer noble-metal catalyst alternatives. Their structures—random alloys, ordered alloys, core-shell, or Janus—depend on synthesis methods, composition, and temperature [ 19 – 21 ]. They achieve saturation magnetization of ~ 15 µWb·m·kg⁻¹ via mechanical milling [ 22 ] and ~ 18 emu·g⁻¹ through chemical reduction [ 23 ]. Because Cu and Fe are immiscible at equilibrium, FeCu solid solutions require non-equilibrium techniques like mechanical alloying [ 24 – 26 ] or vapor deposition [ 27 ]. FeCu nanoparticles have also been synthesized through chemical reduction, involving sodium borohydride in oxygen-free conditions. These nanoparticles exhibit superparamagnetic behavior at ~ 10 K [ 28 ]. Synthesis methods significantly influence nanoparticle size and magnetic properties. In nickel ferrite nanoparticles (NiFe₂O₄), synthesis variations can result in differences in particle size, which in turn affect magnetic behavior. Nanoparticles synthesized via sol-gel methods tend to be ferromagnetic, while those produced by sputtering are superparamagnetic [ 23 ]. FeCu alloy preparation via redox reactions, such as using sodium borohydride and activated carbon, produces nanoparticles with average sizes around 20 nm and chain-like arrangements [ 29 ]. Also, the preparation of FeCu nanoparticles through a redox reaction of mixed aqueous salts was reported. The analysis included structure, morphology, and magnetic properties, though the magnetic loop's hysteresis did not confirm a strong superparamagnetic FeCu alloy formation [ 30 ]. Computational studies have been crucial in designing and characterizing FeCu bimetallic nanoparticles using molecular dynamics (MD) simulations [ 19 , 20 ]. These studies identified two structural types: a core-shell structure at low Cu concentrations and a Janus-like morphology at higher levels [ 19 ]. The cooling rate is key, with Janus morphology forming at lower rates. Different crystalline phases are observed, and the cooling rate strongly influences liquid-to-crystalline transitions. Structural characterization and potential energy assessments have been conducted [ 20 ]. However, a broader simulation framework is needed to fully understand MNPs, as molecular and spin dynamics alone cannot capture magnetic and atomic excitations [ 31 ]. Atomistic spin-lattice simulations integrate spin and lattice dynamics using classical equations like the Landau-Lifshitz-Gilbert equation for spins and Newton's equations for lattice atoms, incorporating exchange interactions, magnetic anisotropy, and magnetoelastic coupling. By combining the MD, Monte Carlo, and spin-dynamics methods [ 32 ], the MD simulation is generalized to magnetic materials. These studies are vital for magnetism, spintronics, and materials science, aiding the design of magnetic materials and devices. A unified molecular and spin dynamics model [ 33 ] enables simulations without phenomenological spin damping, enhancing understanding of magnetic relaxation and energy transfer between lattice and spins [ 33 , 34 ]. Studies also examine compressed iron's magnetic properties using Langevin equations [ 34 ] and first-principles methods integrating spin and molecular dynamics for solids and clusters [ 35 ]. Ma and Dudarev [ 36 ] reviewed spin-lattice coupling, simulation methods, and DFT-based approaches for various materials. MNPs, including FeCu nanoparticles, are used in recovering valuable materials from waste streams and separating biological components [ 37 , 38 ]. FeCu nanoparticles excel in electrochemical applications, improving battery and fuel cell performance by enhancing conductivity and stability [ 38 , 39 ]. Their magnetic behavior depends on structural phase, composition, and grain size. These alloys have soft magnetic characteristics, ideal for data storage, biomedical devices, and catalysis. Understanding how size, surface effects, exchange coupling, and structure influence magnetic behavior is key to optimizing their applications. Advances in synthesis and characterization will continue to refine magnetic properties. The goal is to synthesize and study the alloying process, thermodynamic stability, chemical composition, and structural and magnetic properties of FeCu-based magnetic nanoalloys. FeCu alloys are produced via redox reactions and characterized to examine nanoparticle structure and magnetism. Molecular dynamics simulations complement experiments by exploring atomic-level phenomena. These simulations heat nanoclusters with varying Cu/Fe ratios to 2000 K, then cool them stepwise to 300 K, while also assessing the effects of an external magnetic field during cooling. Uniformly small nanoparticles are essential. Comparing experimental magnetization curves with simulations shows how size and structure (core-shell vs. Janus) influence magnetic behavior, highlighting room-temperature superparamagnetism in these durable nanoparticles. 2. SIMULATION METHODOLOGY Molecular dynamics simulations were carried out to investigate the structural and magnetic properties of FeCu bimetallic nanoparticles. The Embedded Atom Method (EAM) potential by Bonny et al. [ 40 ] modeled inter- and intra-atomic interactions. Besides EAM—the most trusted potential for metallic systems—other commonly used force fields include ReaxFF, INTERFACE Force Field (IFF), AMOEBA, DREIDING, and CHARMM [ 41 , 42 ]. MD simulations were performed in the canonical ensemble (NVT) using LAMMPS (stable version, March 3, 2020) [ 43 ], while spin-lattice simulations used the SPIN package per Tranchida et al. [ 44 ]. The canonical ensemble computed total energies, magnetizations, magnetization energies, and optimized structures. Atomic visualization and trajectory analysis employed OVITO [ 45 ] and VMD [ 46 ]. First, energy and spin minimization used the conjugate gradient algorithm. Fe and Cu atoms equilibrated at 2000 K—well above their melting points—for 20 ns to reach equilibrium. Next, the FeCu nanoparticle system was cooled from 2000 K to 300 K at 0.34 K/ps. Minimization calculations applied both the conjugate gradient and FIRE algorithms. Temperature control combined a Langevin thermostat with the Velocity-Verlet algorithm. All simulations used a 1 fs time step, no boundary conditions, and a 400 × 400 × 400 ų supercell. We explored various FeCu nanocluster sizes and concentrations. Initial spherical core-shell nanoclusters with 5,601 Fe atoms (~ 5 nm diameter) and varying Cu amounts were constructed (see Fig. 1 , Table 1 ). Data for Janus FeCu nanoparticle construction appear in Fig. 2 and Table 1 . Also, we prepared MNPs that experienced an external magnetic field (of 1000 Tesla) during the stepwise cooling process from 2000K to 300K under the simulation procedures explained above. The results were analyzed for the possible improvement of the extent of magnetic properties at 300K. Table 1 Number of Fe and Cu atoms and radius (Å) for the simulation of CS-FeCu and Janus-FeCu nanoparticles Nanoparticle (sizes) No. of atoms Fe/Cu ratio Fe Cu Core-shell (25,30) 5601 2634 2.13 (25,40) 5601 15700 0.36 (25,50) 5601 37152 0.15 (30,45) 9577 20788 0.46 (35,50) 15353 26158 0.59 Janus (25,25) 5601 5546 1.0 (25,35) 5601 15227 0.37 (25,45) 5601 32349 0.17 3. EXPERIMENTAL PROCEDURE Chemicals: FeSO 4 ×7H 2 O (99.5%, Merck), CuSO 4 ×5H 2 O (99.0%, Merck), de-ionized water, Argon gas (local agents), NaOH (99.0%, Merck), NaBH 4, (96.0%, Merck) acetone (99.8%, Merck). Instruments: Bruker AXS D8 Avance X-Ray Diffraction (XRD), MIRA3TESCAN-XMU Scanning electron microscope (SEM), FEI TECNAI F20 High-Resolution Transmission Electron Microscopy (HRTEM), Energy Dispersive Analysis of X-ray (EDAX), Kavir Vibrating Sample Magnetometer (VSM). The stoichiometric FeCu nano-alloy was synthesized following the procedure by Morales-Luckie et al . [30]. A 5 mM aqueous solution of FeSO₄·7H₂O and CuSO₄·5H₂O was prepared using deionized water. Both 500 ml metal salt solutions were mixed, degassed, and kept under an argon atmosphere. After stirring for 20 minutes, the pH was adjusted to 7.0 with 1 M NaOH. Then, 100 ml of a 10 mM NaBH₄ solution was added dropwise to the metal salt mixture over 60 minutes at room temperature. The fine dark precipitate was filtered, washed three times with deionized water, and dried with acetone. For the FeCu nanoparticle sample, room temperature powder XRD patterns were obtained using a D-5000 Siemens diffractometer with Cu Kα radiation at 1.54 Å. FE-SEM analysis, X-ray energy dispersive spectroscopy, and elemental mapping were performed using the MIRA3 TESCAN-XMU model. The HRTEM studies were conducted at an accelerating voltage of 200 kV. For HRTEM, a small amount of powder was subjected to ultrasonic waves in absolute ethanol for homogeneous dispersion. One drop of this FeCu/ethanol-suspended solution was applied to the copper grid and allowed to dry before imaging. Magnetic properties were analyzed with a VSM. The sample was examined as a solid powder without additional preparation. 4. RESULTS and DISCUSSION This study examines FeCu nanoparticles via MD simulations, starting with core-shell and Janus morphologies. Both structures were optimized with and without a magnetic field applied. The simulations explored how varying core/shell size ratios influence the nanoparticles' structural and magnetic properties. The next section presents comprehensive experimental studies on synthesized FeCu nanoparticles, focusing on their structure and magnetization. 4.1. Simulation Results 4.1.1 Structural Properties of Nanoparticles Simulated at B ext =0 Figure 3 shows simulated core-shell FeCu nanoparticles heated above their melting point (2000 K) and cooled to 300 K without a magnetic field. The nanoparticles retain their core-shell structure, with Cu atoms forming the shell due to their lower surface energy. The atom-atom radial distribution function (RDF, g ( r )) characterizes the morphology of bimetallic nanoparticles, revealing their structural and coordination properties. Figure 4 presents the calculated g ( r ) for optimized core-shell clusters. Pronounced short-range peaks indicate strong local coordination, while longer distances show weaker interactions. In the CS(25,30) cluster, Cu⋯Cu correlations are weaker than Fe⋯Fe, whereas other morphologies show the opposite trend, influenced by core-shell size ratios (Figs. 2 and 3 ). In CS(25,30), copper forms a thin shell around the iron core, similar to phenomena reported for other bimetallic alloys like cesium-sodium nanoclusters [ 47 ]. A similar morphological variation has been discussed as arising from van der Waals interactions and modeled using double-wall carbon nanotubes [ 48 ]. A comparison of RDFs (Figure S1 , Supporting Information) shows major interatomic correlations from Fe⋯Fe and Cu⋯Cu interactions, with minor Fe⋯Cu correlations. This reflects the thermodynamic stability of uniform Fe and Cu phases within alloy cluster patches and limited Fe-Cu interaction at patch interfaces. The higher Cu atom count at r = 50 leads to less dynamic behavior and a more ordered Cu crystal structure. Fe atoms in the core are similarly organized, minimally affecting the Cu shell, which remains stable despite excess Cu. The first minimum in Figure S1 (a) indicates a solid-like Fe⋯Fe structure, contrasting with the liquid-like Cu⋯Cu structure in Figure S1 (c). These RDF-derived features guide magnetic nanoparticle (MNP) synthesis for targeted applications. As discussed in the experimental section, factors like thermodynamics, surface energy, and redox rates determine which metal forms the shell. Crystalline phases of FeCu nanoalloys are identified using common neighbor analysis (CNA) via the OVITO algorithm [ 45 ] (Table 2 ). In core-shell and Janus nanoparticles, crystalline proportions (excluding icosahedral coordination, ICO) increase with the Fe/Cu ratio. Recognizable crystalline structures remain minor, with all phases sensitive to nanoparticle size. Controlling thermodynamic and kinetic factors during synthesis is key to achieving desired bimetallic morphologies. Core-shell structures form when one metal exhibits stronger self-affinity and lower surface energy, leading to encapsulation, whereas Janus morphologies arise from metal repulsion or unmet thermodynamic equilibrium. Radial RDFs (Figure S2, Supporting Materials) show Janus nanoparticles, like core-shell systems, with strong Fe⋯Fe and Cu⋯Cu correlations but weak Fe⋯Cu correlations. Increasing the Cu/Fe ratio strengthens Cu⋯Cu correlations while Fe⋯Fe retains its solid-like character and Cu⋯Cu remains liquid-like. Applying a magnetic field during MNP synthesis significantly affects Fe₃O₄ crystallinity and magnetic properties. Such studies highlight their potential in hyperthermia therapies, leveraging heat generated under an alternating magnetic field [ 49 , 50 ]. While primarily used in cancer treatment, this approach can be adapted for controlled warming in hypothermia therapy. Heat output is precisely regulated by adjusting field parameters and nanoparticle properties, enabling safe, localized temperature elevation. External fields during synthesis further enhance magnetization, and combined with functionalization, enable biocompatible, minimally invasive warming [ 49 – 51 ]. Figure 5 presents the influence of the 1000 Tesla external field on the simulated core-shell FeCu nanoparticles at 300 K (cooled from 2000 K). Comparing Figs. 3 and 5 unravels the increased core iron atom ordering under the field. Similar behavior appears in imidazolium-based ionic liquids with (FeCl 4 ) − anions [ 52 ]. Magnetic properties of [C₄mim][FeCl 4 ] were confirmed as paramagnetic, with a 5.8 µB per Fe atom magnetic moment via SQUID magnetometry [ 53 ]. Nanoparticle magnetization stems from electron spin alignment, typically short-range at the nanoscale due to strong local exchange interactions. In well-ordered systems, alignment extends longer-range, producing collective magnetization. This alignment—governed by crystalline structure, particle size, and synthesis conditions—is enhanced by external fields. Structural improvements in MNPs are evidenced by increased RDF peak heights at both short and long ranges (Figure S3). Table 2 Common neighbor analysis (CNA) for FeCu nanoparticles, simulated in the absence of an external magnetic field at 300 K. nanoparticle Common neighbor analysis FCC HCP BCC ICO other CS(25,30) 0.0 0.0 0.3 0.9 98.7 CS(25,40) 0.3 0.4 0.3 0.6 98.3 CS(25,50) 1.0 1.2 0.8 0.3 96.7 CS(30,45) 0.2 0.3 0.3 0.7 98.5 CS(35,50) 0.3 0.4 0.7 0.8 97.8 Janus(25,25) 0.1 0.1 0.3 0.9 98.6 Janus(25,35) 0.4 0.4 0.8 0.6 97.8 Janus(25,45) 1.8 1.7 1.3 0.3 94.8 4.1.2 Simulation of Magnetic Properties of Nanoparticles Spin-lattice dynamics simulations of core-shell MNPs prepared without an external magnetic field show notable magnetization and magnetic energy variations. The magnetization spectrum across magnetic fields (-1000 to 1000 Tesla) was calculated for all (core-shell and Janus) simulated NPs at 300 K. Figure 6 displays a sigmoid-shaped spectrum with a sharp zero-field transition. The plateaus indicate the attainable saturation magnetization and also allow the evaluation of the magnetization’s size dependence quantitatively. Following the spectra, Fig. 7 shows that as the Fe/Cu ratio increases, magnetization rises nonlinearly at high- (saturation and) mid-range fields. Around zero external fields, FeCu NPs exhibit convergence behavior, producing a unified crossing point near − 3 T. Collecting more data near zero shifts this point closer to zero, as shown in Fig. 8 for CS(25,30), highlighting the simulation’s accuracy Notably, this confirms simulation is capable of identifying the true superparamagnetic of the behavior, and superparamagnetic is shown by all NP independent of their size. Therefore, superparamagnetic NPs exhibit no residual magnetism after field removal, preventing attraction to nearby materials and reducing aggregation. This property is vital for drug delivery and enhanced MRI imaging. Furthermore, superparamagnetic NPs offer better magnetic control due to their strong yet reversible response to external fields. Figure 9 shows Janus FeCu nanoparticle structures equilibrated at 300 K. The final Janus (25,25) NP structure, achieved via the same simulation procedure, suggests FeCu systems may evolve into core-shell structures over longer simulations. As depicted in Figs. 6 and 8 , Janus structures generally exhibit lower magnetization than core-shell counterparts, depending on nanoparticle size and Fe/Cu ratio. Although their spectra appear indistinguishable, Janus NPs’ lower magnetization stems from their premature geometry, differing from the more developed core-shell configurations. Similar to FeCu core-shell NPs, Janus NPs exhibit non-linear magnetization increases with the Fe/Cu ratio (Figure S4). Magnetization trends nonlinearly at higher external fields but remains linear at lower ones. Table 3 summarizes magnetization energy variations for Janus NPs with and without an external field. Magnetic structural similarities are inferred from magnetization energy values: CS (25, 50) ~ J (25, 45) and CS (25, 40) ~ J (25, 35). At equilibrium, magnetization primarily depends on size, regardless of initial structure. Analyzing magnetization vector components under external fields reveals the magnetization behavior of NPs. These components represent projections along the x -, y -, and z -axes, influenced by NP shape, size, anisotropy, and field strength. Table S1 (A) and S1(B) compare simulated magnetization vectors of core-shell and Janus FeCu NPs at 300 K, under zero external field and fields up to 1000 Tesla along the z -axis. Higher Fe/Cu ratios correspond to stronger magnetic components, while lower ratios significantly reduce magnetization, aligning it along the z -axis. Notably, the results suggest that NPs exhibit magnetization isotropy in the absence of external fields but develop anisotropic magnetization under moderate to strong fields, independent of morphology or Fe/Cu ratio. Table 3 Total magnetization and magnetic energy of FeCu core-shell nanoparticles at 300 K simulated in the absence and presence of the external magnetic field. Magnetic Energy (eV) B ext = 0 B ext = 1000 T CS -FeCu nanoparticle (25,30) -750.6656 -2294.9119 (25,40) -483.8495 -2012.1841 (25,50) -343.8628 -1824.0066 (30,45) -924.0859 -3453.5828 (35,50) -1647.0832 -6027.7027 Janus FeCu nanoparticle (25,25) -702.8656 -2236.0684 (25,35) -549.8612 -2076.3187 (25,45) -460.6027 -1965.3182 4.1.3 Effect of the external magnetic field during the cooling process To investigate the structural and magnetic behavior of FeCu core-shell NPs prepared under an external magnetic field, we analyzed a representative CS(30,45) NP with initial core-shell configuration simulations under two conditions: (1) equilibration at 2000 K without an external field and (2) equilibration at 2000 K with a 1000 Tesla external field. Both systems were then cooled from 2000 K to 300 K, as detailed in the simulation methodology. Figure 10 compares the two scenarios, showing that the structure cooled under the external field (Fig. 10 (b)) exhibits enhanced atomic ordering, with iron atoms preferentially aggregating in the core. The corresponding correlation functions (Fig. 11 ) reveal significant structural differences, confirming the external field’s impact. Notably, these differences extend to long distances, reflecting effective long-range correlations governed by both exchange and dipolar interactions. Exchange interactions, typically short-ranged, include (1) direct exchange between neighboring atoms and (2) super-exchange mediated by non-magnetic atoms, allowing longer-range effects. This spin-lattice simulation effectively captures intrinsic spin-spin correlations, accurately representing the magnetic properties of FeCu NPs. Dipolar interactions, arising from magnetic dipole moments, can align or anti-align neighboring spins depending on orientation. While weaker than exchange interactions, they extend over longer ranges and significantly affect systems with moderately separated magnetic moments. Both interaction types are encompassed by the simulation algorithm applied to these FeCu nanoalloys. 5. EXPERIMENTAL RESULTS In synthesizing these nanoparticle materials, the optimal concentration of the reducing agent is crucial for achieving complete reduction while preventing agglomeration and uncontrolled growth. Maintaining a stable inert gas atmosphere is essential to avoid oxidation of the metal nanoparticles. Additionally, precise control of pH and minimizing temperature fluctuations are critical for ensuring product homogeneity. Several experimental techniques, such as X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray analysis (EDAX), elemental mapping, and high-resolution transmission electron microscopy (HRTEM), can be employed to characterize the crystal structure, morphology, and electronic properties of the as-synthesized FeCu nanoparticles. The magnetic properties of the material can be assessed using vibrating sample magnetometry (VSM). 5.1 XRD Analysis The crystal structure of the synthesized FeCu alloy was analyzed using XRD to monitor the reduction process and detect phase separation. Bragg reflections (Figure S5) corresponding to the [(104), (110), (113), (024), (116), (214), and (300)] planes were observed at 2θ values of 35.6°, 38.7°, 43.4°, 49.1°, 53.5°, 62.8°, and 66.0°, respectively, which align well with reported results for this alloy [ 54 ]. Furthermore, a comparison of the crystal planes of Fe(0) (JCPDS card No. 01-087-0721) [ 37 ] and Cu(0) (JCPDS card No. 003-1018) [ 55 ] with those of the synthesized FeCu nanoalloy revealed a shift of approximately 0.2°, confirming the successful alloying of iron and copper. Lattice expansion or contraction occurs when Cu is added to Fe, shifting XRD peaks (Figure S5) to higher or lower angles, directly influenced by atomic metallic radii. The larger metallic radius (Cu) expands the lattice, shifting peaks to lower angles, while the smaller radius (Fe) contracts it, shifting peaks higher. Since Cu’s radius exceeds Fe’s, its peaks appear at lower angles. A second set of peaks marked with an asterisk (*) in Figure S5(a) confirms alloy formation. FeCu’s Bragg reflections differ from pure Fe or Cu but fall between them, supporting FeCu nanostructure formation [ 56 ]. Peak broadening indicates small nanostructure size, while strong, sharp peaks reflect high crystallinity. The nanoparticle size is approximately calculated using the Scherrer equation (Eq. 1 ) based on the corresponding XRD pattern. $$\:d=\frac{9\lambda\:}{\beta\:\text{cos}\theta\:}$$ 1 where d is the average diameter of the structure and λ (= 1.54 Å) is the wavelength of the X-ray source in the presence of copper metal. The width of the peak, β (in radian), is estimated at half maximum. For Bragg angle \(\:\theta\:=35.66\) o and β = 0.778, the average diameter of the synthesized nanostructures (Eq. 1 ) can be estimated to be 10.74 nm. Figures S5(b) and S5(c) present the XRD analysis generated using VESTA software [ 56 ] for Cu(0) and Fe(0), derived from the experimental XRD patterns. These serve as standard calibration references for Cu(0) and Fe(0). 5.2 Field Emission Scanning Electron Microscope (FE-SEM) Analysis To examine the morphology and composition of the synthesized FeCu nanoalloy, FE-SEM, EDAX, and elemental mapping were employed. FE-SEM revealed highly homogeneous spherical particles averaging ~ 11 nm in diameter (Figure S6), closely aligning with the 10.74 nm size from XRD analysis (Eq. ( 1 )). EDAX was conducted by directing an electron beam onto the sample, collecting emitted X-rays characteristic of the elements present, thus providing bulk material insights due to deep beam penetration. The NP size distribution from FE-SEM centers around 11 nm (Figure S6(c)), within the lower range reported in literature, indicating strong superparamagnetic potential (Table 4 ). EDAX (via FE-SEM, Figure S7) confirms Fe and Cu presence and detects 32% oxygen (Table 5 ). Elemental mapping shows a uniform Fe, Cu, and O distribution (Figure S8). Table 4 A comparison with the properties of synthesized (bimetallic) magnetic nanoparticles in the literature. Although the magnetization of nanoparticles out of precious metals (Co and Ag) is high, using cheaper Cu (this work) produces acceptable magnetization while superparamagnetic. MNPs Synthetic Method NP Size (nm) Saturation Magnetization (M s ) (emu/g) Ref. FeNi 2 9.27 ferromagnetic [ 57 ] CoNi 4.15 superparamagnetic [ 57 ] FeCo 273 [ 57 ] FeAg 47.2 [ 57 ] Fe-oxide 38.7 [ 57 ] Fe 0.5 Cu 0.5 chemical reduction 11 27.50 superparamagnetic This work Fe 0.5 Cu 0.5 chemical reduction ~ 15 [ 23 ] Fe 0.9 Cu 0.1 chemical reduction ~ 30 [ 23 ] FeCu dry-ball milling [ 58 ] FeCu laser ablation 102 ~ 5 [ 59 ] FeCu aqueous chemical reduction (fast method) \(\:\stackrel{-}{5}\) [ 30 ] FeCu aqueous chemical reduction (slow method) \(\:\stackrel{-}{10}\) [ 30 ] FeCu mechanical milling 16–50 [ 22 ] Table 5 Mass ratio of the elements in the FeCu synthesized nanoalloy. W% (O) W% (Fe) W% (Cu) Ref. 31.97 32.52 35.51 This Work 30.14 40.01 29.84 [ 19 ] 5.3 High-Resolution Transmission Electron Microscope (HR-TEM) Analysis The morphology of FeCu nanostructures was examined in detail using HR-TEM analysis. Figures 12 (a–d) show that the nanostructures predominantly display a core-shell configuration with diverse morphologies. The off-centered core-shell formation is particularly intriguing, given its implications for interatomic interactions as a function of the relative core/shell size. Additionally, electron diffraction patterns obtained from arbitrary surfaces reveal bright spots, confirming the crystalline structure of the sample (Fig. 12 (e–f) ). Chemical characterization of the sample via EDAX analysis verifies the presence of iron, copper, oxygen, and carbon, suggesting partial oxidation of the sample under the reaction media (Figure S9). Based on the elemental composition, an empirical formula such as FeCuO₃.₆ can be estimated. 5.4 Mechanism of FeCu nanoalloy formation The formation of FeCu core-shell nanoalloy is significantly influenced by precursor and reducing agent concentrations, reaction medium pH, and the reducing agent addition rate, collectively affecting precursor reduction, nucleation, and growth. Dropwise NaBH 4 addition to an alkaline copper and iron precursor solution (Fig. 13 (a)) facilitates metal precursor reduction according to their standard electrode potentials. Copper ( E ° Cu 2+ /Cu = + 0.34 V) reduces first, forming primary copper nanoparticle nuclei (Fig. 13 (b)) and initiating growth. In contrast, Fe²⁺ reduction with NaBH 4 alone is challenging due to its more negative potential ( E ° Fe 2+ /Fe = -0.44 V). However, an alkaline medium, copper presence, and a favorable Cu–Fe synergistic effect promote faster Fe²⁺ reduction. p H control influences hydrogen production, with NaBH 4 hydrolysis enhancing reducing hydrogen availability. As Fe(0) forms the core, Cu(0) arranges around it to form the shell (Fig. 13 (c)). Notably, this shelling is self-catalyzed by Cu(0)’s lower surface energy, protecting Fe(0) nanoparticles from fracture and oxidation. [ 60 ] Subsequent crystal growth and diffusion produce FeCu nanostructures with an off-centric core-shell morphology (Fig. 13 (d)). The reduction reaction with NaBH 4 is shown in Eq. 2. \(\:4{\text{F}\text{e}}^{2+}+4{\text{C}\text{u}}^{2+}+3{{\text{B}\text{H}}_{4}}^{-}+12{\text{H}}_{2}\text{O}\to\:4{\text{F}\text{e}}^{0}{\text{C}\text{u}}^{0}+3\text{B}{{\left(\text{O}\text{H}\right)}_{4}}^{-}+24{\text{H}}^{+}\) (Eq. 2) 5.5 Magnetic Property Analysis VSM analyzed the magnetic property of synthesized FeCu nanoalloy at ambient temperature within an external field of ± 10 kOe. The obtained spectrum (Fig. 14 ) has a sinusoidal shape, having a saturation magnetization value of 27.50 emu/g, indicating the magnetic moment per unit mass and reflecting the degree of alignment of magnetic domains. Since the saturation magnetization for the single nanoparticle(s) has been simulated under no effective boundary condition, implying no interparticle-induced magnetization contribution, the big difference between the synthesized and the simulated single NP represents the surface effect, particle size, and superparamagnetic extension. The inset in Fig. 14 (magnifies the spectrum and) shows the existence of an ignorable hysteresis of about 1 Oe in zero external fields, on the reversal of the external field, for the synthesized FeCu NP. The forward magnetization hysteresis loop indicates zero magnetization at zero external fields, revealing the strict superparamagnetic properties of the synthesized FeCu nanoalloy. Although the simulated magnetization spectrum follows a trend similar to that observed in real-world experiments, several factors contribute to the substantial decrease in magnetization seen in MD simulations. First, MD simulations typically operate on nanosecond timescales, whereas magnetic phenomena often evolve over much longer periods, leading to an incomplete representation of nanoparticle magnetic behavior. Additionally, the simulations involved smaller system sizes (~ 5 nm) compared to experimental counterparts (~ 11 nm) (see Fig. 1 and Figure S6(c)). Another limitation arises from the approximations in interatomic potentials used in MD simulations, which may not fully capture the electronic structure and magnetic interactions of the material. Moreover, in experimentally prepared samples, nanoparticles interact via magnetic dipolar interactions, significantly influencing measured magnetization. However, these interactions are absent in the present simulations, as only a single isolated nanoparticle is modeled. Despite this, the spin-lattice method can account for magnetization effects due to magnetic dipole interactions if, during simulation optimization, the aggregated core Fe atoms separate and form islands immersed in the Cu shell atoms. 6. CONCLUSIONS The properties of bimetallic FeCu nanoalloys were investigated through experimental synthesis, characterization, and MD simulations. The spin-lattice algorithm, incorporating spin coupling and magnetic dipole interaction into classical MD, successfully simulates magnetic properties consistent with real world experiments. For both core-shell and Janus FeCu nanoparticles, no direct correlation was found between morphology and magnetic properties; however, magnetization depends only on the Fe/Cu mass ratio. Correlation function analysis confirms that Cu atoms form a shell around Fe cores, with persisting long-range atom-atom correlations indicating direct and indirect spin-spin coupling, effectively captured by the spin-lattice algorithm. This first-time simulation of the magnetization spectrum accurately identifies saturation magnetization and achieves near-zero magnetization at zero external fields, evidencing FeCu’s superparamagnetic behavior. Multi-technique analysis verified the core-shell morphology of the synthesized FeCu nanoalloy. The average particle size of 11 nm from FE-SEM closely matches the 10.74 nm calculated from XRD data, aligning with the lower bound of reported sizes and supporting the observed superparamagnetism. The Fe magnetic core, protected by a noble Cu shell, resists oxidation while maintaining a high saturation magnetization of 27.50 emu/g. The precise attainment of zero magnetization at zero fields, combined with the novel spin-lattice simulation, compellingly demonstrates the room-temperature superparamagnetic nature of synthesized FeCu under controlled conditions. Declarations Authors Deceleration: the authors claim no conflict of interest. Data Availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Authors contributions: Maryam Bahrami : conceptualizations, first draft, simulation, software, visualization, analysis, synthesis. Mehrangiz Bahrami : synthesis, analysis, interpretation of spectrum S. Jafar Hoseini : synthesis, analysis, interpretation of spectrum Mohammad Had Ghatee : conceptualization, writing, editing, interpretation, synthesis, supervision. ACKNOWLEDGMENTS The authors are indebted to the research council of the Shiraz University and Iran National Science Foundation (grant no. 97024308) for financial support. The authors also thank the Iranian Nanotechnology Initiative Council for their support. The cluster computing times are also provided in part by the High-Performance Computing research laboratory of the Institute for Research in Fundamental Sciences (IPM). 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Mater. 3, 256–265, 2025 Additional Declarations No competing interests reported. Supplementary Files 181203SupportingIFeCu.docx Cite Share Download PDF Status: Published Journal Publication published 03 Jun, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 09 Apr, 2025 Reviews received at journal 08 Apr, 2025 Reviews received at journal 04 Apr, 2025 Reviewers agreed at journal 18 Mar, 2025 Reviewers agreed at journal 18 Mar, 2025 Reviewers invited by journal 18 Mar, 2025 Editor assigned by journal 18 Mar, 2025 Editor invited by journal 18 Mar, 2025 Submission checks completed at journal 17 Mar, 2025 First submitted to journal 02 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6141115","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":431211369,"identity":"37a1d3af-9ff2-49fc-8e56-eddaceca425b","order_by":0,"name":"Maryam Bahrami","email":"","orcid":"","institution":"Shiraz University","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Bahrami","suffix":""},{"id":431211370,"identity":"c36eb137-be1c-4241-ae93-7940b80da5e3","order_by":1,"name":"Mehrangiz Bahrami","email":"","orcid":"","institution":"Shiraz University","correspondingAuthor":false,"prefix":"","firstName":"Mehrangiz","middleName":"","lastName":"Bahrami","suffix":""},{"id":431211371,"identity":"70c7d81d-56ed-4039-b552-45a5908f03c7","order_by":2,"name":"S. Jafar Hoseini","email":"","orcid":"","institution":"Shiraz University","correspondingAuthor":false,"prefix":"","firstName":"S.","middleName":"Jafar","lastName":"Hoseini","suffix":""},{"id":431211372,"identity":"27e40424-382b-4060-8cd8-31c01a489c13","order_by":3,"name":"Mohammad Hadi Ghatee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYDACCQY2MM3PwMNwAC6aQFALUIVkA8laDA7wEOku3dnt1x78/GEjZ3z+7MHDFTV1iQ3shx8wPNyDW4vZnTPlhj0JacZmN/ISDp45xpbYwJNmwJDwDI+WGzlpEjwJhxO33eAxONjAxpPYwJADdOkB/Fok/yT8r9/cfwao5Z9EYgP/G0Ja0o9J8yQcSDBgyDE42NhmkNggQdgWNmmZtGTDGTdAWvoSjNsknhkcIGDLM8k3Nnby/P1njD82fKuT7edPfvjwBx4tDAw8Bqh8UGLAq4GBgf0BfvlRMApGwSgYBQDpZ1auwz74ewAAAABJRU5ErkJggg==","orcid":"","institution":"Shiraz University","correspondingAuthor":true,"prefix":"","firstName":"Mohammad","middleName":"Hadi","lastName":"Ghatee","suffix":""}],"badges":[],"createdAt":"2025-03-02 20:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6141115/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6141115/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-01130-y","type":"published","date":"2025-06-03T15:57:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79336728,"identity":"71e05fb3-415e-4f02-9e72-73e43878e65f","added_by":"auto","created_at":"2025-03-27 08:00:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":549981,"visible":true,"origin":"","legend":"\u003cp\u003eThe initial structures of core-shell FeCu nanoparticle alloys.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/98a0c44a3e6bb014aa8fad44.png"},{"id":79337272,"identity":"c98c7446-0ef7-4de9-84a4-50ad3d0cafa9","added_by":"auto","created_at":"2025-03-27 08:08:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":546240,"visible":true,"origin":"","legend":"\u003cp\u003eThe initial structures of Janus FeCu nanoparticles.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/24c2d5e1e3e6a5712fdbfa72.png"},{"id":79338310,"identity":"3bb4c253-55ec-4a83-b9ca-90e6d0687947","added_by":"auto","created_at":"2025-03-27 08:16:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":578995,"visible":true,"origin":"","legend":"\u003cp\u003eStructures of core-shell FeCu nanoparticles equilibriated at 300 K simulated in the absence of an external magnetic field.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/ca38608838c73dd9b375550b.png"},{"id":79336730,"identity":"909b5654-e84c-4846-af3e-1d42b92e3e4d","added_by":"auto","created_at":"2025-03-27 08:00:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":71792,"visible":true,"origin":"","legend":"\u003cp\u003eRDFs for FeCu atoms of different-sized core-shell nanoparticles (\u003cstrong\u003eFigure 1\u003c/strong\u003e) simulated at 300 K without an external magnetic field.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/da79f5b3b45f50b26f064ce0.png"},{"id":79336735,"identity":"064fa245-9437-4f44-991c-13d55b37eabe","added_by":"auto","created_at":"2025-03-27 08:00:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":468506,"visible":true,"origin":"","legend":"\u003cp\u003eCore-shell FeCu nanoparticles equilibrated at 300 K and in the presence of an external magnetic field with a magnitude of 1000 Tesla.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/e1ba31a64ee5f0f0bfef9d50.png"},{"id":79336731,"identity":"3c09355c-c2fb-4e71-8146-8fd9ed1449c3","added_by":"auto","created_at":"2025-03-27 08:00:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":61186,"visible":true,"origin":"","legend":"\u003cp\u003eMagnetization spectrum of core-shell and Janus FeCu nanoparticles as a function of the external magnetic field at 300 K. Lines and broken lines facilitate trend analysis.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/4cc00f670d7fe2529153af7c.png"},{"id":79337273,"identity":"e57aebfe-34fe-4742-bf3b-372fdd92e3cf","added_by":"auto","created_at":"2025-03-27 08:08:09","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":34695,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the magnetic properties of core-shell FeCu nanoparticles as a function of the ratio of Fe/Cu atoms, in the absence and different external magnetic fields. Lines facilitate trend analysis.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/c8c944cdd5faa849d904b810.png"},{"id":79336752,"identity":"2a104aca-da82-42ef-8d7b-0da13f22dc29","added_by":"auto","created_at":"2025-03-27 08:00:09","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":50640,"visible":true,"origin":"","legend":"\u003cp\u003eThe magnified magnetization spectrum (\u003cstrong\u003eFigure 7\u003c/strong\u003e) provides detailed insights into the magnetic behavior near zero external fields. The blue arrow indicates the external field (approximately -3 Tesla) where zero magnetization is observed for all NPs studied. Similarly, the red arrow highlights the zero magnetization point (achieved at -1 Tesla) in the CS(25,30) NP. For this NP specifically, additional simulated data points closer to zero external fields were incorporated to refine the spectrum, providing a basis for identifying true superparamagnetic NPs through spin-lattice simulation. Lines and broken lines facilitate trend analysis.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/1c91b5d5d7c5a78b1760de2e.png"},{"id":79337282,"identity":"7ce2106f-0c74-45c8-846d-fd18686bf238","added_by":"auto","created_at":"2025-03-27 08:08:09","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":296609,"visible":true,"origin":"","legend":"\u003cp\u003eFeCu nanoparticles simulated from Janus's initial structure, equilibriated at 300 K in the absence of an external magnetic field.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/dc7e424ed4fdba390cf898bf.png"},{"id":79338316,"identity":"569a4caf-5426-46f1-b258-fae524d83342","added_by":"auto","created_at":"2025-03-27 08:16:10","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":229332,"visible":true,"origin":"","legend":"\u003cp\u003eStructure of FeCu-CS(30,45), \u003cstrong\u003e(a)\u003c/strong\u003e cooled from 2000 K to 300 K in the absence of external magnetic field and then equilibriated at 300 K in the presence of 1000 Tesla external magnetic field, \u003cstrong\u003e(b)\u003c/strong\u003e cooled stepwise from 2000 K to 300 K and equilibriated (at 300 K) while the 1000 Tesla external magnetic field is on.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/863ec01ed51276144c35fbcb.png"},{"id":79336753,"identity":"53cc46db-dbd4-459d-b159-a8cf8d18ef0c","added_by":"auto","created_at":"2025-03-27 08:00:10","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":19661,"visible":true,"origin":"","legend":"\u003cp\u003eRadial distribution functions of Fe atoms for FeCu-CS(30,45), illustrate how the external field affects the cooling process, (a) condition 1, (b) condition 2. The difference in behavior is extended to long ranges up to 25 Å (not shown for clarity).\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/f1ffe9664d8073f6b6f25d62.png"},{"id":79336761,"identity":"bbc2cfb3-9372-4c75-a593-e5554d49b226","added_by":"auto","created_at":"2025-03-27 08:00:10","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":1197674,"visible":true,"origin":"","legend":"\u003cp\u003e(a-d) HR-TEM analysis and (e-f) electron diffraction patterns of arbitrary surfaces of iron-copper nanoalloy.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/8a3891390db1433cc04e7969.png"},{"id":79337277,"identity":"525590dc-4fa1-4c70-b54d-a5ab2cb8679c","added_by":"auto","created_at":"2025-03-27 08:08:09","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":213830,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe detailed mechanism of FeCu nanoalloy Formation: \u003c/strong\u003e(a) \u003cstrong\u003egradual addition of NaBH₄\u003c/strong\u003e to the alkaline solution containing CuSO₄ and FeSO₄, (b) \u003cstrong\u003ereduction of\u003c/strong\u003eCu(II) precursor, (c) \u003cstrong\u003ereduction of Fe(II) and \u003c/strong\u003ethe generation of Fe(0) atoms, and (d) \u003cstrong\u003ecore-shell structure formation of FeCu t\u003c/strong\u003ehrough the crystal growth process, completing the nanoalloy formation.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/f6c9ecfe5cf2fc40a58e1f37.png"},{"id":79338314,"identity":"2b193b2f-474e-40fe-b860-3e375ddc6336","added_by":"auto","created_at":"2025-03-27 08:16:09","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":50031,"visible":true,"origin":"","legend":"\u003cp\u003eMagnetization property of a sample of FeCu nanoalloy synthesized. The inset magnifies the trend of magnetization near zero external fields, showing that zero magnetization is attainable at zero external fields. The saturation magnetization decreases by 3% after 20 days.\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/8cad7c6cdaae746266ad1ee7.png"},{"id":84242541,"identity":"457c3819-2a8d-42f4-8085-ac43bb727bec","added_by":"auto","created_at":"2025-06-09 16:09:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5764290,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/36f7a4af-cdee-4744-9a8d-82e9fa4e32a7.pdf"},{"id":79338312,"identity":"29087a4f-ced6-4fd9-a664-af172728f779","added_by":"auto","created_at":"2025-03-27 08:16:09","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2409295,"visible":true,"origin":"","legend":"","description":"","filename":"181203SupportingIFeCu.docx","url":"https://assets-eu.researchsquare.com/files/rs-6141115/v1/1d6807e8d9654e1cc514bc3b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Room-Temperature Superparamagnetic FeCu Nanoalloys: Insights into Magnetic Behavior from Synthesis and Simulation","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eNanoparticles (1\u0026ndash;100 nm) are key to nanotechnology, exhibiting unique properties due to their small size, large surface area, and quantum effects. These traits enable advanced applications in medicine, electronics, energy, and environmental science, surpassing bulk materials. Their high surface-area-to-volume ratio boosts chemical reactivity and catalysis, while quantum effects influence conductivity, magnetism, and optics.\u003c/p\u003e \u003cp\u003eThe class of magnetic nanoparticles (MNPs) has distinct properties shaped by size, uniformity, surface area, and biocompatibility. By adjusting synthesis parameters, traits like superparamagnetism and adsorption kinetics can be tailored for applications in biology, catalysis, data storage, spintronics, sensors, and MRI contrast [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7 CR8 CR9\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Their large surface area enhances superparamagnetism, making MNPs a dynamic focus of theoretical and experimental nanoscience research.\u003c/p\u003e \u003cp\u003eThese MNPs are classified as diamagnetic, paramagnetic, ferromagnetic, ferrimagnetic, or antiferromagnetic based on magnetic dipole interactions. Among them, superparamagnetic nanoparticles, which exhibit zero magnetization in the absence of an external field, are particularly useful in drug delivery and MRI enhancement. Since they do not retain magnetization once the field is removed, interparticle attraction is eliminated, influencing surface properties and biological applications. Their high sensitivity to magnetic fields allows precise control over their behavior.\u003c/p\u003e \u003cp\u003eControlling MNP size and morphology is essential for tailoring their physicochemical properties. Reaction parameters must be carefully adjusted to achieve desired size distributions [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. For example, nanoparticles below the single-domain limit (~\u0026thinsp;20 nm for iron oxide) often exhibit superparamagnetism at room temperature, making them valuable for ferrofluids, data storage, and medicine [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Nanoparticle size significantly impacts properties such as coercivity, magnetization, and magnetic structure, which are shaped by intrinsic composition and surface effects. Below 20 nm, thermal fluctuations typically prevent permanent magnetization [12,13,]. For example, ε-Fe₂O₃ nanoparticles transition from ferromagnetic to superparamagnetic around 6 nm due to surface effects and weakened exchange interactions. Larger particles (~\u0026thinsp;20 nm) exhibit higher coercivity than smaller ones (~\u0026thinsp;6 nm) due to an increased surface-to-volume ratio, impacting magnetic stability and ordering [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt temperatures higher than room temperatures, thermal energy overcomes magnetic interactions, reducing effective magnetization, particularly in smaller nanoparticles, where high surface-to-volume ratios amplify thermal fluctuations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In magnetic alloys, exchange coupling between core and shell atoms affects magnetic properties. This coupling, arising from atomic magnetic moment interactions, results in diverse magnetic behaviors based on materials and structure. Differences in atom arrangement and cooling rates during synthesis yield varied phase diagrams and thermal behaviors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMagnetic bimetallic nanoparticles (MBNPs) offer enhanced properties over monometallic particles due to synergistic effects between two metals, improving magnetic response for applications like magnetic separation and targeted drug delivery. MBNPs enable efficient separation from solutions via external magnetic fields, which is critical for catalytic processes and environmental remediation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Core-shell interactions in MBNPs lead to diverse exchange coupling mechanisms, with differences in atomic number and coupling type (core vs. shell) influencing thermal stability and magnetic behavior [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNotably, core@shell nanoparticles exhibit stability against oxygen, water, and chemicals. Copper and iron combinations yield multifunctional nanoparticles with high catalytic activity and ferromagnetic properties, enabling magnetic separation from reaction systems [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Bimetallic FeCu nanoparticles, made from cost-effective metals, exhibit notable magnetic properties despite the immiscibility of iron and copper. These alloys are traditionally produced via vapor deposition and mechanical alloying [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], balancing iron's magnetism with copper's diamagnetic behavior. Despite synthesis challenges like oxidation, FeCu nanoparticles offer noble-metal catalyst alternatives. Their structures\u0026mdash;random alloys, ordered alloys, core-shell, or Janus\u0026mdash;depend on synthesis methods, composition, and temperature [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. They achieve saturation magnetization of ~\u0026thinsp;15 \u0026micro;Wb\u0026middot;m\u0026middot;kg⁻\u0026sup1; via mechanical milling [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and ~\u0026thinsp;18 emu\u0026middot;g⁻\u0026sup1; through chemical reduction [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBecause Cu and Fe are immiscible at equilibrium, FeCu solid solutions require non-equilibrium techniques like mechanical alloying [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] or vapor deposition [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. FeCu nanoparticles have also been synthesized through chemical reduction, involving sodium borohydride in oxygen-free conditions. These nanoparticles exhibit superparamagnetic behavior at ~\u0026thinsp;10 K [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSynthesis methods significantly influence nanoparticle size and magnetic properties. In nickel ferrite nanoparticles (NiFe₂O₄), synthesis variations can result in differences in particle size, which in turn affect magnetic behavior. Nanoparticles synthesized via sol-gel methods tend to be ferromagnetic, while those produced by sputtering are superparamagnetic [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. FeCu alloy preparation via redox reactions, such as using sodium borohydride and activated carbon, produces nanoparticles with average sizes around 20 nm and chain-like arrangements [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Also, the preparation of FeCu nanoparticles through a redox reaction of mixed aqueous salts was reported. The analysis included structure, morphology, and magnetic properties, though the magnetic loop's hysteresis did not confirm a strong superparamagnetic FeCu alloy formation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComputational studies have been crucial in designing and characterizing FeCu bimetallic nanoparticles using molecular dynamics (MD) simulations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. These studies identified two structural types: a core-shell structure at low Cu concentrations and a Janus-like morphology at higher levels [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The cooling rate is key, with Janus morphology forming at lower rates. Different crystalline phases are observed, and the cooling rate strongly influences liquid-to-crystalline transitions. Structural characterization and potential energy assessments have been conducted [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, a broader simulation framework is needed to fully understand MNPs, as molecular and spin dynamics alone cannot capture magnetic and atomic excitations [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Atomistic spin-lattice simulations integrate spin and lattice dynamics using classical equations like the Landau-Lifshitz-Gilbert equation for spins and Newton's equations for lattice atoms, incorporating exchange interactions, magnetic anisotropy, and magnetoelastic coupling. By combining the MD, Monte Carlo, and spin-dynamics methods [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], the MD simulation is generalized to magnetic materials. These studies are vital for magnetism, spintronics, and materials science, aiding the design of magnetic materials and devices. A unified molecular and spin dynamics model [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] enables simulations without phenomenological spin damping, enhancing understanding of magnetic relaxation and energy transfer between lattice and spins [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Studies also examine compressed iron's magnetic properties using Langevin equations [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and first-principles methods integrating spin and molecular dynamics for solids and clusters [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Ma and Dudarev [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] reviewed spin-lattice coupling, simulation methods, and DFT-based approaches for various materials.\u003c/p\u003e \u003cp\u003eMNPs, including FeCu nanoparticles, are used in recovering valuable materials from waste streams and separating biological components [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. FeCu nanoparticles excel in electrochemical applications, improving battery and fuel cell performance by enhancing conductivity and stability [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Their magnetic behavior depends on structural phase, composition, and grain size. These alloys have soft magnetic characteristics, ideal for data storage, biomedical devices, and catalysis. Understanding how size, surface effects, exchange coupling, and structure influence magnetic behavior is key to optimizing their applications. Advances in synthesis and characterization will continue to refine magnetic properties.\u003c/p\u003e \u003cp\u003eThe goal is to synthesize and study the alloying process, thermodynamic stability, chemical composition, and structural and magnetic properties of FeCu-based magnetic nanoalloys. FeCu alloys are produced via redox reactions and characterized to examine nanoparticle structure and magnetism. Molecular dynamics simulations complement experiments by exploring atomic-level phenomena. These simulations heat nanoclusters with varying Cu/Fe ratios to 2000 K, then cool them stepwise to 300 K, while also assessing the effects of an external magnetic field during cooling. Uniformly small nanoparticles are essential. Comparing experimental magnetization curves with simulations shows how size and structure (core-shell vs. Janus) influence magnetic behavior, highlighting room-temperature superparamagnetism in these durable nanoparticles.\u003c/p\u003e"},{"header":"2. SIMULATION METHODOLOGY","content":"\u003cp\u003eMolecular dynamics simulations were carried out to investigate the structural and magnetic properties of FeCu bimetallic nanoparticles. The Embedded Atom Method (EAM) potential by Bonny et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] modeled inter- and intra-atomic interactions. Besides EAM\u0026mdash;the most trusted potential for metallic systems\u0026mdash;other commonly used force fields include ReaxFF, INTERFACE Force Field (IFF), AMOEBA, DREIDING, and CHARMM [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMD simulations were performed in the canonical ensemble (NVT) using LAMMPS (stable version, March 3, 2020) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], while spin-lattice simulations used the SPIN package per Tranchida et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The canonical ensemble computed total energies, magnetizations, magnetization energies, and optimized structures. Atomic visualization and trajectory analysis employed OVITO [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and VMD [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. First, energy and spin minimization used the conjugate gradient algorithm. Fe and Cu atoms equilibrated at 2000 K\u0026mdash;well above their melting points\u0026mdash;for 20 ns to reach equilibrium. Next, the FeCu nanoparticle system was cooled from 2000 K to 300 K at 0.34 K/ps. Minimization calculations applied both the conjugate gradient and FIRE algorithms. Temperature control combined a Langevin thermostat with the Velocity-Verlet algorithm. All simulations used a 1 fs time step, no boundary conditions, and a 400 \u0026times; 400 \u0026times; 400 \u0026Aring;\u0026sup3; supercell.\u003c/p\u003e \u003cp\u003eWe explored various FeCu nanocluster sizes and concentrations. Initial spherical core-shell nanoclusters with 5,601 Fe atoms (~\u0026thinsp;5 nm diameter) and varying Cu amounts were constructed (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Data for Janus FeCu nanoparticle construction appear in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAlso, we prepared MNPs that experienced an external magnetic field (of 1000 Tesla) during the stepwise cooling process from 2000K to 300K under the simulation procedures explained above. The results were analyzed for the possible improvement of the extent of magnetic properties at 300K.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of Fe and Cu atoms and radius (\u0026Aring;) for the simulation of CS-FeCu and Janus-FeCu nanoparticles\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNanoparticle (sizes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo. of atoms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFe/Cu ratio\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCore-shell\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(25,30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(25,40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(25,50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(30,45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(35,50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eJanus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(25,25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(25,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(25,45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. EXPERIMENTAL PROCEDURE","content":"\u003cp\u003e\u003cstrong\u003eChemicals:\u0026nbsp;\u003c/strong\u003eFeSO\u003csub\u003e4\u003c/sub\u003e\u0026times;7H\u003csub\u003e2\u003c/sub\u003eO (99.5%, Merck), CuSO\u003csub\u003e4\u003c/sub\u003e\u0026times;5H\u003csub\u003e2\u003c/sub\u003eO (99.0%, Merck), de-ionized water, Argon gas (local agents), NaOH (99.0%, Merck), NaBH\u003csub\u003e4,\u0026nbsp;\u003c/sub\u003e(96.0%, Merck)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eacetone (99.8%, Merck).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstruments:\u0026nbsp;\u003c/strong\u003eBruker AXS D8 Avance X-Ray Diffraction (XRD), MIRA3TESCAN-XMU Scanning electron microscope (SEM), FEI TECNAI F20\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eHigh-Resolution Transmission Electron Microscopy (HRTEM), Energy Dispersive Analysis of X-ray (EDAX),\u0026nbsp;Kavir Vibrating Sample Magnetometer (VSM).\u003c/p\u003e\n\u003cp\u003eThe stoichiometric FeCu nano-alloy was synthesized following the procedure by Morales-Luckie \u003cem\u003eet al\u003c/em\u003e. [30]. A 5 mM aqueous solution of FeSO₄\u0026middot;7H₂O and CuSO₄\u0026middot;5H₂O was prepared using deionized water. Both 500 ml metal salt solutions were mixed, degassed, and kept under an argon atmosphere. After stirring for 20 minutes, the pH was adjusted to 7.0 with 1 M NaOH. Then, 100 ml of a 10 mM NaBH₄ solution was added dropwise to the metal salt mixture over 60 minutes at room temperature. The fine dark precipitate was filtered, washed three times with deionized water, and dried with acetone.\u003c/p\u003e\n\u003cp\u003eFor the FeCu nanoparticle sample, room temperature powder XRD patterns were obtained using a D-5000 Siemens diffractometer with Cu K\u0026alpha; radiation at 1.54 \u0026Aring;. FE-SEM analysis, X-ray energy dispersive spectroscopy, and elemental mapping were performed using the MIRA3 TESCAN-XMU model. The HRTEM studies were conducted at an accelerating voltage of 200 kV. For HRTEM, a small amount of powder was subjected to ultrasonic waves in absolute ethanol for homogeneous dispersion. One drop of this FeCu/ethanol-suspended solution was applied to the copper grid and allowed to dry before imaging. Magnetic properties were analyzed with a VSM. The sample was examined as a solid powder without additional preparation.\u003c/p\u003e"},{"header":"4. RESULTS and DISCUSSION","content":"\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eThis study examines FeCu nanoparticles via MD simulations, starting with core-shell and Janus morphologies. Both structures were optimized with and without a magnetic field applied. The simulations explored how varying core/shell size ratios influence the nanoparticles\u0026apos; structural and magnetic properties. The next section presents comprehensive experimental studies on synthesized FeCu nanoparticles, focusing on their structure and magnetization.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Simulation Results\u003c/h2\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e4.1.1 Structural Properties of Nanoparticles Simulated at B\u003csub\u003eext\u003c/sub\u003e=0\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows simulated core-shell FeCu nanoparticles heated above their melting point (2000 K) and cooled to 300 K without a magnetic field. The nanoparticles retain their core-shell structure, with Cu atoms forming the shell due to their lower surface energy.\u003c/p\u003e\n \u003cp\u003eThe atom-atom radial distribution function (RDF, \u003cem\u003eg\u003c/em\u003e(\u003cem\u003er\u003c/em\u003e)) characterizes the morphology of bimetallic nanoparticles, revealing their structural and coordination properties. Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e presents the calculated \u003cem\u003eg\u003c/em\u003e(\u003cem\u003er\u003c/em\u003e) for optimized core-shell clusters. Pronounced short-range peaks indicate strong local coordination, while longer distances show weaker interactions. In the CS(25,30) cluster, Cu⋯Cu correlations are weaker than Fe⋯Fe, whereas other morphologies show the opposite trend, influenced by core-shell size ratios (Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In CS(25,30), copper forms a thin shell around the iron core, similar to phenomena reported for other bimetallic alloys like cesium-sodium nanoclusters [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e]. A similar morphological variation has been discussed as arising from van der Waals interactions and modeled using double-wall carbon nanotubes [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eA comparison of RDFs (Figure \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e, Supporting Information) shows major interatomic correlations from Fe⋯Fe and Cu⋯Cu interactions, with minor Fe⋯Cu correlations. This reflects the thermodynamic stability of uniform Fe and Cu phases within alloy cluster patches and limited Fe-Cu interaction at patch interfaces. The higher Cu atom count at \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;50 leads to less dynamic behavior and a more ordered Cu crystal structure. Fe atoms in the core are similarly organized, minimally affecting the Cu shell, which remains stable despite excess Cu. The first minimum in Figure \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e(a) indicates a solid-like Fe⋯Fe structure, contrasting with the liquid-like Cu⋯Cu structure in Figure \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e(c). These RDF-derived features guide magnetic nanoparticle (MNP) synthesis for targeted applications. As discussed in the experimental section, factors like thermodynamics, surface energy, and redox rates determine which metal forms the shell.\u003c/p\u003e\n \u003cp\u003eCrystalline phases of FeCu nanoalloys are identified using common neighbor analysis (CNA) via the OVITO algorithm [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e] (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In core-shell and Janus nanoparticles, crystalline proportions (excluding icosahedral coordination, ICO) increase with the Fe/Cu ratio. Recognizable crystalline structures remain minor, with all phases sensitive to nanoparticle size.\u003c/p\u003e\n \u003cp\u003eControlling thermodynamic and kinetic factors during synthesis is key to achieving desired bimetallic morphologies. Core-shell structures form when one metal exhibits stronger self-affinity and lower surface energy, leading to encapsulation, whereas Janus morphologies arise from metal repulsion or unmet thermodynamic equilibrium. Radial RDFs (Figure S2, Supporting Materials) show Janus nanoparticles, like core-shell systems, with strong Fe⋯Fe and Cu⋯Cu correlations but weak Fe⋯Cu correlations. Increasing the Cu/Fe ratio strengthens Cu⋯Cu correlations while Fe⋯Fe retains its solid-like character and Cu⋯Cu remains liquid-like.\u003c/p\u003e\n \u003cp\u003eApplying a magnetic field during MNP synthesis significantly affects Fe₃O₄ crystallinity and magnetic properties. Such studies highlight their potential in hyperthermia therapies, leveraging heat generated under an alternating magnetic field [\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. While primarily used in cancer treatment, this approach can be adapted for controlled warming in hypothermia therapy. Heat output is precisely regulated by adjusting field parameters and nanoparticle properties, enabling safe, localized temperature elevation. External fields during synthesis further enhance magnetization, and combined with functionalization, enable biocompatible, minimally invasive warming [\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the influence of the 1000 Tesla external field on the simulated core-shell FeCu nanoparticles at 300 K (cooled from 2000 K). Comparing Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e unravels the increased core iron atom ordering under the field. Similar behavior appears in imidazolium-based ionic liquids with (FeCl\u003csub\u003e4\u003c/sub\u003e)\u003csup\u003e\u0026minus;\u003c/sup\u003e anions [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. Magnetic properties of [C₄mim][FeCl\u003csub\u003e4\u003c/sub\u003e] were confirmed as paramagnetic, with a 5.8 \u0026micro;B per Fe atom magnetic moment via SQUID magnetometry [\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eNanoparticle magnetization stems from electron spin alignment, typically short-range at the nanoscale due to strong local exchange interactions. In well-ordered systems, alignment extends longer-range, producing collective magnetization. This alignment\u0026mdash;governed by crystalline structure, particle size, and synthesis conditions\u0026mdash;is enhanced by external fields. Structural improvements in MNPs are evidenced by increased RDF peak heights at both short and long ranges (Figure S3).\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCommon neighbor analysis (CNA) for FeCu nanoparticles, simulated in the absence of an external magnetic field at 300 K.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003enanoparticle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eCommon neighbor analysis\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFCC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHCP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBCC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eICO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eother\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCS(25,30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCS(25,40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCS(25,50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCS(30,45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCS(35,50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJanus(25,25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJanus(25,35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJanus(25,45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003e4.1.2 Simulation of Magnetic Properties of Nanoparticles\u003c/h2\u003e\n \u003cp\u003eSpin-lattice dynamics simulations of core-shell MNPs prepared without an external magnetic field show notable magnetization and magnetic energy variations. The magnetization spectrum across magnetic fields (-1000 to 1000 Tesla) was calculated for all (core-shell and Janus) simulated NPs at 300 K. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e displays a sigmoid-shaped spectrum with a sharp zero-field transition. The plateaus indicate the attainable saturation magnetization and also allow the evaluation of the magnetization\u0026rsquo;s size dependence quantitatively. Following the spectra, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e shows that as the Fe/Cu ratio increases, magnetization rises nonlinearly at high- (saturation and) mid-range fields. Around zero external fields, FeCu NPs exhibit convergence behavior, producing a unified crossing point near \u0026minus;\u0026thinsp;3 T. Collecting more data near zero shifts this point closer to zero, as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e for CS(25,30), highlighting the simulation\u0026rsquo;s accuracy Notably, this confirms simulation is capable of identifying the true superparamagnetic of the behavior, and superparamagnetic is shown by all NP independent of their size.\u003c/p\u003e\n \u003cp\u003eTherefore, superparamagnetic NPs exhibit no residual magnetism after field removal, preventing attraction to nearby materials and reducing aggregation. This property is vital for drug delivery and enhanced MRI imaging. Furthermore, superparamagnetic NPs offer better magnetic control due to their strong yet reversible response to external fields.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e shows Janus FeCu nanoparticle structures equilibrated at 300 K. The final Janus (25,25) NP structure, achieved via the same simulation procedure, suggests FeCu systems may evolve into core-shell structures over longer simulations. As depicted in Figs. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, Janus structures generally exhibit lower magnetization than core-shell counterparts, depending on nanoparticle size and Fe/Cu ratio. Although their spectra appear indistinguishable, Janus NPs\u0026rsquo; lower magnetization stems from their premature geometry, differing from the more developed core-shell configurations.\u003c/p\u003e\n \u003cp\u003eSimilar to FeCu core-shell NPs, Janus NPs exhibit non-linear magnetization increases with the Fe/Cu ratio (Figure S4). Magnetization trends nonlinearly at higher external fields but remains linear at lower ones. Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes magnetization energy variations for Janus NPs with and without an external field. Magnetic structural similarities are inferred from magnetization energy values: CS (25, 50)\u0026thinsp;~\u0026thinsp;J (25, 45) and CS (25, 40)\u0026thinsp;~\u0026thinsp;J (25, 35). At equilibrium, magnetization primarily depends on size, regardless of initial structure.\u003c/p\u003e\n \u003cp\u003eAnalyzing magnetization vector components under external fields reveals the magnetization behavior of NPs. These components represent projections along the \u003cem\u003ex\u003c/em\u003e-, \u003cem\u003ey\u003c/em\u003e-, and \u003cem\u003ez\u003c/em\u003e-axes, influenced by NP shape, size, anisotropy, and field strength. Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e(A) and S1(B) compare simulated magnetization vectors of core-shell and Janus FeCu NPs at 300 K, under zero external field and fields up to 1000 Tesla along the \u003cem\u003ez\u003c/em\u003e-axis. Higher Fe/Cu ratios correspond to stronger magnetic components, while lower ratios significantly reduce magnetization, aligning it along the \u003cem\u003ez\u003c/em\u003e-axis. Notably, the results suggest that NPs exhibit magnetization isotropy in the absence of external fields but develop anisotropic magnetization under moderate to strong fields, independent of morphology or Fe/Cu ratio.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTotal magnetization and magnetic energy of FeCu core-shell nanoparticles at 300 K simulated in the absence and presence of the external magnetic field.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMagnetic Energy (eV)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003csub\u003eext\u003c/sub\u003e = 0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003csub\u003eext\u003c/sub\u003e = 1000 T\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eCS\u003c/strong\u003e-FeCu nanoparticle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(25,30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-750.6656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2294.9119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(25,40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-483.8495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2012.1841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(25,50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-343.8628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1824.0066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(30,45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-924.0859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3453.5828\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(35,50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1647.0832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6027.7027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eJanus\u003c/strong\u003e FeCu nanoparticle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(25,25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-702.8656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2236.0684\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(25,35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-549.8612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2076.3187\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(25,45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-460.6027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1965.3182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e4.1.3 Effect of the external magnetic field during the cooling process\u003c/h2\u003e\n \u003cp\u003eTo investigate the structural and magnetic behavior of FeCu core-shell NPs prepared under an external magnetic field, we analyzed a representative CS(30,45) NP with initial core-shell configuration simulations under two conditions: (1) equilibration at 2000 K without an external field and (2) equilibration at 2000 K with a 1000 Tesla external field. Both systems were then cooled from 2000 K to 300 K, as detailed in the simulation methodology. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e compares the two scenarios, showing that the structure cooled under the external field (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e(b)) exhibits enhanced atomic ordering, with iron atoms preferentially aggregating in the core.\u003c/p\u003e\n \u003cp\u003eThe corresponding correlation functions (Fig. \u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e) reveal significant structural differences, confirming the external field\u0026rsquo;s impact. Notably, these differences extend to long distances, reflecting effective long-range correlations governed by both exchange and dipolar interactions. Exchange interactions, typically short-ranged, include (1) direct exchange between neighboring atoms and (2) super-exchange mediated by non-magnetic atoms, allowing longer-range effects. This spin-lattice simulation effectively captures intrinsic spin-spin correlations, accurately representing the magnetic properties of FeCu NPs.\u003c/p\u003e\n \u003cp\u003eDipolar interactions, arising from magnetic dipole moments, can align or anti-align neighboring spins depending on orientation. While weaker than exchange interactions, they extend over longer ranges and significantly affect systems with moderately separated magnetic moments. Both interaction types are encompassed by the simulation algorithm applied to these FeCu nanoalloys.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"5. EXPERIMENTAL RESULTS","content":"\u003cp\u003eIn synthesizing these nanoparticle materials, the optimal concentration of the reducing agent is crucial for achieving complete reduction while preventing agglomeration and uncontrolled growth. Maintaining a stable inert gas atmosphere is essential to avoid oxidation of the metal nanoparticles. Additionally, precise control of pH and minimizing temperature fluctuations are critical for ensuring product homogeneity.\u003c/p\u003e \u003cp\u003eSeveral experimental techniques, such as X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray analysis (EDAX), elemental mapping, and high-resolution transmission electron microscopy (HRTEM), can be employed to characterize the crystal structure, morphology, and electronic properties of the as-synthesized FeCu nanoparticles. The magnetic properties of the material can be assessed using vibrating sample magnetometry (VSM).\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e5.1 XRD Analysis\u003c/h2\u003e \u003cp\u003eThe crystal structure of the synthesized FeCu alloy was analyzed using XRD to monitor the reduction process and detect phase separation. Bragg reflections \u003cb\u003e(Figure S5)\u003c/b\u003e corresponding to the [(104), (110), (113), (024), (116), (214), and (300)] planes were observed at 2θ values of 35.6\u0026deg;, 38.7\u0026deg;, 43.4\u0026deg;, 49.1\u0026deg;, 53.5\u0026deg;, 62.8\u0026deg;, and 66.0\u0026deg;, respectively, which align well with reported results for this alloy [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Furthermore, a comparison of the crystal planes of Fe(0) (JCPDS \u003cb\u003ecard\u003c/b\u003e No. 01-087-0721) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and Cu(0) (JCPDS \u003cb\u003ecard\u003c/b\u003e No. 003-1018) [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] with those of the synthesized FeCu nanoalloy revealed a shift of approximately 0.2\u0026deg;, confirming the successful alloying of iron and copper.\u003c/p\u003e \u003cp\u003eLattice expansion or contraction occurs when Cu is added to Fe, shifting XRD peaks (Figure S5) to higher or lower angles, directly influenced by atomic metallic radii. The larger metallic radius (Cu) expands the lattice, shifting peaks to lower angles, while the smaller radius (Fe) contracts it, shifting peaks higher. Since Cu\u0026rsquo;s radius exceeds Fe\u0026rsquo;s, its peaks appear at lower angles.\u003c/p\u003e \u003cp\u003eA second set of peaks marked with an asterisk (*) in Figure S5(a) confirms alloy formation. FeCu\u0026rsquo;s Bragg reflections differ from pure Fe or Cu but fall between them, supporting FeCu nanostructure formation [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Peak broadening indicates small nanostructure size, while strong, sharp peaks reflect high crystallinity.\u003c/p\u003e \u003cp\u003eThe nanoparticle size is approximately calculated using the Scherrer equation (Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) based on the corresponding XRD pattern.\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:d=\\frac{9\\lambda\\:}{\\beta\\:\\text{cos}\\theta\\:}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ed\u003c/em\u003e is the average diameter of the structure and \u003cem\u003eλ\u003c/em\u003e (=\u0026thinsp;1.54 \u0026Aring;) is the wavelength of the X-ray source in the presence of copper metal. The width of the peak, \u003cem\u003eβ \u003c/em\u003e(in radian), is estimated at half maximum. For Bragg angle \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\theta\\:=35.66\\)\u003c/span\u003e\u003c/span\u003e\u003csup\u003eo\u003c/sup\u003e and \u003cem\u003eβ \u003c/em\u003e=\u0026thinsp;0.778, the average diameter of the synthesized nanostructures (Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) can be estimated to be 10.74 nm. \u003cb\u003eFigures S5(b)\u003c/b\u003e and \u003cb\u003eS5(c)\u003c/b\u003e present the XRD analysis generated using VESTA software [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] for Cu(0) and Fe(0), derived from the experimental XRD patterns. These serve as standard calibration references for Cu(0) and Fe(0).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Field Emission Scanning Electron Microscope (FE-SEM) Analysis\u003c/h2\u003e \u003cp\u003eTo examine the morphology and composition of the synthesized FeCu nanoalloy, FE-SEM, EDAX, and elemental mapping were employed. FE-SEM revealed highly homogeneous spherical particles averaging\u0026thinsp;~\u0026thinsp;11 nm in diameter (Figure S6), closely aligning with the 10.74 nm size from XRD analysis (Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)). EDAX was conducted by directing an electron beam onto the sample, collecting emitted X-rays characteristic of the elements present, thus providing bulk material insights due to deep beam penetration.\u003c/p\u003e \u003cp\u003eThe NP size distribution from FE-SEM centers around 11 nm (Figure S6(c)), within the lower range reported in literature, indicating strong superparamagnetic potential (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). EDAX (via FE-SEM, Figure S7) confirms Fe and Cu presence and detects 32% oxygen (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Elemental mapping shows a uniform Fe, Cu, and O distribution (Figure S8).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA comparison with the properties of synthesized (bimetallic) magnetic nanoparticles in the literature. Although the magnetization of nanoparticles out of precious metals (Co and Ag) is high, using cheaper Cu (this work) produces acceptable magnetization while superparamagnetic.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMNPs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSynthetic Method\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNP Size (nm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSaturation Magnetization (M\u003csub\u003es\u003c/sub\u003e) (emu/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeNi\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.27\u003c/p\u003e \u003cp\u003eferromagnetic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.15 superparamagnetic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeCo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeAg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFe-oxide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFe\u003csub\u003e0.5\u003c/sub\u003eCu\u003csub\u003e0.5\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echemical reduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.50\u003c/p\u003e \u003cp\u003esuperparamagnetic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThis work\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFe\u003csub\u003e0.5\u003c/sub\u003eCu\u003csub\u003e0.5\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echemical reduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e~\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFe\u003csub\u003e0.9\u003c/sub\u003eCu\u003csub\u003e0.1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echemical reduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e~\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edry-ball milling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elaser ablation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e~\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eaqueous chemical reduction (fast method)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{5}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eaqueous chemical reduction (slow method)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{10}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emechanical milling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMass ratio of the elements in the FeCu synthesized nanoalloy.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW% (O)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW% (Fe)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eW% (Cu)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThis Work\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e5.3 High-Resolution Transmission Electron Microscope (HR-TEM) Analysis\u003c/h2\u003e \u003cp\u003eThe morphology of FeCu nanostructures was examined in detail using HR-TEM analysis. Figures\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e\u003cb\u003e(a\u0026ndash;d)\u003c/b\u003e show that the nanostructures predominantly display a core-shell configuration with diverse morphologies. The off-centered core-shell formation is particularly intriguing, given its implications for interatomic interactions as a function of the relative core/shell size. Additionally, electron diffraction patterns obtained from arbitrary surfaces reveal bright spots, confirming the crystalline structure of the sample (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e\u003cb\u003e(e\u0026ndash;f)\u003c/b\u003e). Chemical characterization of the sample via EDAX analysis verifies the presence of iron, copper, oxygen, and carbon, suggesting partial oxidation of the sample under the reaction media (Figure S9). Based on the elemental composition, an empirical formula such as FeCuO₃.₆ can be estimated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Mechanism of FeCu nanoalloy formation\u003c/h2\u003e \u003cp\u003eThe formation of FeCu core-shell nanoalloy is significantly influenced by precursor and reducing agent concentrations, reaction medium pH, and the reducing agent addition rate, collectively affecting precursor reduction, nucleation, and growth. Dropwise NaBH\u003csub\u003e4\u003c/sub\u003e addition to an alkaline copper and iron precursor solution (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(a)) facilitates metal precursor reduction according to their standard electrode potentials. Copper (\u003cem\u003eE\u003c/em\u003e\u0026deg;\u003csub\u003eCu\u003c/sub\u003e2+\u003csub\u003e/Cu\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;+\u0026thinsp;0.34 V) reduces first, forming primary copper nanoparticle nuclei (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(b)) and initiating growth. In contrast, Fe\u0026sup2;⁺ reduction with NaBH\u003csub\u003e4\u003c/sub\u003e alone is challenging due to its more negative potential (\u003cem\u003eE\u003c/em\u003e\u0026deg;\u003csub\u003eFe\u003c/sub\u003e2+\u003csub\u003e/Fe\u003c/sub\u003e = -0.44 V). However, an alkaline medium, copper presence, and a favorable Cu\u0026ndash;Fe synergistic effect promote faster Fe\u0026sup2;⁺ reduction. \u003cem\u003ep\u003c/em\u003eH control influences hydrogen production, with NaBH\u003csub\u003e4\u003c/sub\u003e hydrolysis enhancing reducing hydrogen availability. As Fe(0) forms the core, Cu(0) arranges around it to form the shell (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(c)). Notably, this shelling is self-catalyzed by Cu(0)\u0026rsquo;s lower surface energy, protecting Fe(0) nanoparticles from fracture and oxidation. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] Subsequent crystal growth and diffusion produce FeCu nanostructures with an off-centric core-shell morphology (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(d)). The reduction reaction with NaBH\u003csub\u003e4\u003c/sub\u003e is shown in Eq.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:4{\\text{F}\\text{e}}^{2+}+4{\\text{C}\\text{u}}^{2+}+3{{\\text{B}\\text{H}}_{4}}^{-}+12{\\text{H}}_{2}\\text{O}\\to\\:4{\\text{F}\\text{e}}^{0}{\\text{C}\\text{u}}^{0}+3\\text{B}{{\\left(\\text{O}\\text{H}\\right)}_{4}}^{-}+24{\\text{H}}^{+}\\)\u003c/span\u003e \u003c/span\u003e (Eq.\u0026nbsp;2)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e5.5 Magnetic Property Analysis\u003c/h2\u003e \u003cp\u003eVSM analyzed the magnetic property of synthesized FeCu nanoalloy at ambient temperature within an external field of \u0026plusmn;\u0026thinsp;10 kOe. The obtained spectrum (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e) has a sinusoidal shape, having a saturation magnetization value of 27.50 emu/g, indicating the magnetic moment per unit mass and reflecting the degree of alignment of magnetic domains. Since the saturation magnetization for the single nanoparticle(s) has been simulated under no effective boundary condition, implying no interparticle-induced magnetization contribution, the big difference between the synthesized and the simulated single NP represents the surface effect, particle size, and superparamagnetic extension.\u003c/p\u003e \u003cp\u003eThe inset in Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e (magnifies the spectrum and) shows the existence of an ignorable hysteresis of about 1 Oe in zero external fields, on the reversal of the external field, for the synthesized FeCu NP. The forward magnetization hysteresis loop indicates zero magnetization at zero external fields, revealing the strict superparamagnetic properties of the synthesized FeCu nanoalloy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlthough the simulated magnetization spectrum follows a trend similar to that observed in real-world experiments, several factors contribute to the substantial decrease in magnetization seen in MD simulations. First, MD simulations typically operate on nanosecond timescales, whereas magnetic phenomena often evolve over much longer periods, leading to an incomplete representation of nanoparticle magnetic behavior. Additionally, the simulations involved smaller system sizes (~\u0026thinsp;5 nm) compared to experimental counterparts (~\u0026thinsp;11 nm) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Figure S6(c)). Another limitation arises from the approximations in interatomic potentials used in MD simulations, which may not fully capture the electronic structure and magnetic interactions of the material. Moreover, in experimentally prepared samples, nanoparticles interact via magnetic dipolar interactions, significantly influencing measured magnetization. However, these interactions are absent in the present simulations, as only a single isolated nanoparticle is modeled. Despite this, the spin-lattice method can account for magnetization effects due to magnetic dipole interactions if, during simulation optimization, the aggregated core Fe atoms separate and form islands immersed in the Cu shell atoms.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. CONCLUSIONS","content":"\u003cp\u003eThe properties of bimetallic FeCu nanoalloys were investigated through experimental synthesis, characterization, and MD simulations. The spin-lattice algorithm, incorporating spin coupling and magnetic dipole interaction into classical MD, successfully simulates magnetic properties consistent with real world experiments. For both core-shell and Janus FeCu nanoparticles, no direct correlation was found between morphology and magnetic properties; however, magnetization depends only on the Fe/Cu mass ratio. Correlation function analysis confirms that Cu atoms form a shell around Fe cores, with persisting long-range atom-atom correlations indicating direct and indirect spin-spin coupling, effectively captured by the spin-lattice algorithm. This first-time simulation of the magnetization spectrum accurately identifies saturation magnetization and achieves near-zero magnetization at zero external fields, evidencing FeCu\u0026rsquo;s superparamagnetic behavior. Multi-technique analysis verified the core-shell morphology of the synthesized FeCu nanoalloy. The average particle size of 11 nm from FE-SEM closely matches the 10.74 nm calculated from XRD data, aligning with the lower bound of reported sizes and supporting the observed superparamagnetism. The Fe magnetic core, protected by a noble Cu shell, resists oxidation while maintaining a high saturation magnetization of 27.50 emu/g. The precise attainment of zero magnetization at zero fields, combined with the novel spin-lattice simulation, compellingly demonstrates the room-temperature superparamagnetic nature of synthesized FeCu under controlled conditions.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors Deceleration:\u0026nbsp;\u003c/strong\u003ethe authors claim no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMaryam Bahrami\u003c/em\u003e: conceptualizations, first draft, simulation, software, visualization, analysis, synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMehrangiz Bahrami\u003c/em\u003e: synthesis, analysis, interpretation of spectrum\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. Jafar Hoseini\u003c/em\u003e: synthesis, analysis, interpretation of spectrum\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMohammad Had Ghatee\u003c/em\u003e: conceptualization, writing, editing, interpretation, synthesis, supervision.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are indebted to the research council of the Shiraz University and Iran National Science Foundation (grant no. 97024308) for financial support. The authors also thank the Iranian Nanotechnology Initiative Council for their support. The cluster computing times are also provided in part by the High-Performance Computing research laboratory of the Institute for Research in Fundamental Sciences (IPM).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Materials\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eare available online/upon request from the author\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHao, R., Xing, R., Xu, Z., Hou, Y., Gao, S. \u0026amp; Sun, S. Synthesis, functionalization, and biomedical applications of multifunctional magnetic nanoparticles. \u003cem\u003eAdv. Mater. \u003c/em\u003e\u003cstrong\u003e22\u003c/strong\u003e, 2729-2742 (2010).\u003c/li\u003e\n\u003cli\u003eWu, L., Mendoza-Garcia, A., Li, Q. \u0026amp; Sun, S. 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Matter, \u003c/em\u003e\u003cstrong\u003e650\u003c/strong\u003e, 414503, (2023).\u003c/li\u003e\n\u003cli\u003eWei\u0026szlig;, N.P., Rocabert, U., Hoppe, C., Zwick, J.-P., Loewe, K., Fries, M., Karttunen, A.J., Gutfleisch, O., Muench, F., Stable Operation of Copper-Protected La(FeMnSi)\u003csub\u003e13\u003c/sub\u003eH\u003cem\u003e\u003csub\u003ey\u003c/sub\u003e\u003c/em\u003e Regenerators in a Magnetic Cooling Unit, \u003cem\u003eACS Appl. Eng. Mater.\u003c/em\u003e3, 256\u0026ndash;265, 2025\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Core-shell and Janus, FeCu nanomaterial synthesis, Magnetization spectrum, Molecular dynamics simulation, Nano superparamagnetic, Spin-lattice dynamics","lastPublishedDoi":"10.21203/rs.3.rs-6141115/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6141115/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBimetallic nanoalloys combining magnetic and noble metals are promising for applications in magnetic sensors, catalysis, optical detection, and biomedical imaging. Their development relies on understanding morphology, electronic structure, and crystallography. This study explores iron-based magnetic nanoalloys using efficient synthesis and advanced characterization. Molecular dynamics (MD) simulations examined atomic-scale morphology and structural features, linking them to magnetic behavior. A spin-lattice dynamics algorithm simulated iron-copper (FeCu) nanoalloys of varying sizes and compositions. FeCu nanoalloys were synthesized via a one-step reduction reaction and analyzed using multiple techniques, yielding nanoparticles with high saturation magnetization and an 11 nm average size. Simulations and experiments confirmed core-shell (CS) and Janus morphologies, where copper shells an iron core. Findings suggest that composition, rather than morphology alone, predominantly influences magnetic properties, while the core-shell morphology enhances oxidation resistance due to the noble copper metal employed. This study is the first to integrate the spin-lattice algorithm with experimental analysis, providing consistent insights into design and accurate characterization. Thus, it confirms the practical and novel synthesis of low-size FeCu nanoparticles with exact ideal superparamagnetic properties\u0026mdash;exhibiting no hysteresis\u0026mdash;suitable for various research and industrial applications.\u003c/p\u003e","manuscriptTitle":"Room-Temperature Superparamagnetic FeCu Nanoalloys: Insights into Magnetic Behavior from Synthesis and Simulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-27 08:00:04","doi":"10.21203/rs.3.rs-6141115/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-10T03:19:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-08T04:26:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-04T20:43:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118943337895024067601530215812605554660","date":"2025-03-18T19:00:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189639657421826344199432626632763006185","date":"2025-03-18T11:12:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-18T10:40:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-18T10:24:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-18T05:21:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-17T05:47:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-02T20:05:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2ed721c0-bd0f-424d-b0ad-8d455035575c","owner":[],"postedDate":"March 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":45930527,"name":"Physical sciences/Chemistry"},{"id":45930528,"name":"Physical sciences/Energy science and technology"},{"id":45930529,"name":"Physical sciences/Materials science"},{"id":45930530,"name":"Physical sciences/Mathematics and computing"},{"id":45930531,"name":"Physical sciences/Nanoscience and technology"}],"tags":[],"updatedAt":"2025-06-09T16:01:15+00:00","versionOfRecord":{"articleIdentity":"rs-6141115","link":"https://doi.org/10.1038/s41598-025-01130-y","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-06-03 15:57:22","publishedOnDateReadable":"June 3rd, 2025"},"versionCreatedAt":"2025-03-27 08:00:04","video":"","vorDoi":"10.1038/s41598-025-01130-y","vorDoiUrl":"https://doi.org/10.1038/s41598-025-01130-y","workflowStages":[]},"version":"v1","identity":"rs-6141115","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6141115","identity":"rs-6141115","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}