Design & Analysis of a Highly Sensitive Biosensor for Detecting Breast Malignancy using a Charge Plasma TFET with SiGe Pocket  

Design & Analysis of a Highly Sensitive Biosensor for Detecting Breast Malignancy using a Charge Plasma TFET with SiGe Pocket | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Design & Analysis of a Highly Sensitive Biosensor for Detecting Breast Malignancy using a Charge Plasma TFET with SiGe Pocket Sidhartha Dash This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8131934/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 18 You are reading this latest preprint version Abstract This study proposes a source pocket-based charge plasma TFET with a dual source cavity (DSC-SPCPT) sensor for detecting various cancerous breast cells. A compound SiGe source pocket in the charge plasma TFET offers a higher drain current than TFET as a result of its wider band bending and shorter tunneling length. The breast cells get immobile within the etched nanocavity beneath both source metals. The source cavity's dielectric constant changes with exposure to four tumorigenic breast cells (MCF-7, Hs578T, T47D, and MDA-MB-231) and a healthy cell (MCF-10A). The energy band diagram, threshold voltage, drain current, and transconductance are among the analogue metrics analysed when exposed to malignant cells. This study further estimates the biosensor's sensitivity considering parameters such as drain current, current ratio, transconductance, and threshold voltage, when exposed to both kinds of cells. The proposed sensor is significantly more sensitive to T47D malignant cells in terms of peak drain current (1.03×10 12 ), transconductance (3.46×10 11 ), and current ratio (3.31×10 9 ). This magnitude is more than four decades higher than the result of healthy breast cells. The effects of temperature on the sensitivity performance are also thoroughly examined. Breast cancer biosensor SiGe pocket sensitivity malignant cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. INTRODUCTION The growing cancer mortality rate is one of the biggest challenges the world is currently experiencing. Specific genetic alterations in tissues cause cancer. Tumors are masses of changed tissue caused by these cells' uncontrolled reproduction and multiplication. It is classified according to the type of cell created and where it originates. Breast, Colon, Lung and Rectal cancers are the most common across the world due to their high incidence. However, breast cancer is among the most commonly found cancers in women [ 1 ]. Early identification can lead to more comprehensive therapy and fewer fatalities. In the initial phase, X-ray mammography is considered for identifying breast cancer. Although this method has made significant progress, it has been shown to have several shortcomings [ 2 – 4 ]. For larger breasts, the sensitivity and specificity of this technique declined sharply to 67% and 89%, respectively [ 5 – 6 ]. Conversely, high-contrast Magnetic Resonance Imaging (MRI) offers a sensitivity of more than 90% [ 7 ]. MRI is an expensive and time-consuming process that requires an in-hospital procedure. Ultrasonography provides a greater rate of false positives compared to mammography [ 8 ]. Furthermore, it is challenging for women to access high-quality diagnostic treatments when they live in secluded areas. Because medical expenses are rising, even in affluent countries, there is a current demand for a trustworthy, quick, and affordable cancer diagnosis [ 9 ]. Microwave-based cancer diagnosis and treatment is one of the most important scientific areas to explore. This type of research relies primarily on the fact that healthy and cancerous cells have substantially distinct dielectric properties [ 10 – 11 ]. A higher water content in cancerous tissues enhances microwave dispersion and provides a higher dielectric constant. Microwave spectroscopy has been used in several scientific studies to analyse living cells electrically [ 12 – 19 ]. An open-ended coaxial probe procedure was used for conducting dielectric testing on animal tissues in earlier days. Stuchly et al. evaluated tissue specimens from cats [ 13 ]. Rat tissues were used to assess the electrical characteristics at 30 MHz to 2 GHz [ 14 ]. Eventually, the research went further to include human samples. In 1994, Joines et al. conducted an ex vivo dielectric study of several human samples at frequencies ranging from 50 to 900 MHz [ 14 ]. Lazebnik et al. conducted a comprehensive study to examine breast tissues at 0.5 GHz to 2 GHz [ 15 – 16 ]. According to the study, breast cell diversity and obesity influence the dielectric value of the cells. Martellosio et al. explored various dielectric features of breast cells for a wider frequency range [ 17 – 19 ]. The dielectric measurements of different cancer cells were also experimentally demonstrated by Hussein et al. in 2019 [ 20 ]. The researchers evaluated both healthy and malignant cells' k-values [ 20 ]. At microwave frequencies, dielectric-modulated biosensors are one of the effective methods for early cancer detection, as the biomarkers associated with cells have a variable dielectric constant (k-value) [ 21 – 22 ]. Tunnel field-effect transistors (TFETs) are among the most promising options for biosensor design due to their low power consumption and superior sensitivity [ 23 – 29 ]. These sensors' interband tunneling current transmission method enables them to surpass the drawbacks of traditional MOSFETs. Several researchers have examined the effectiveness of a dual-metal gate DLTFET as a biosensor [ 30 – 31 ]. These sensors can be an excellent choice for a number of critical applications, such as environmental monitoring and medical diagnostics, as a result of their higher sensitivity at lower drain bias. In 2022, Singh and Singh [ 32 ] developed a charge plasma TFET for breast cancer detection. Priyadarshani et al. [ 33 ] developed an ultrasensitive FET biosensor for detecting cancer. A TFET biosensor with improved current sensitivity was proposed in 2024 for breast cancer diagnosis, utilising dielectric variation [ 34 ]. A source pocket-based charge plasma TFET with a dual source cavity (DSC-SPCPT) biosensor is presented here to effectively detect healthy and cancerous breast cells. Here, we have designed a compound SiGe source pocket near the source-channel (S-C) interface, which enhances drain current and sensitivity with exposure to tumorigenic cells. An extensive electrical analysis of the suggested sensor was conducted using varying cell samples with different dielectric constants (k-values). The sensitivity investigation of the biosensor is estimated by considering several electrical parameters, such as ON-current, current ratio, transconductance, and threshold voltage, in the presence of both types of breast cells. The study also examines how cavity length and thickness affect the sensitivity performance of both cells. The Silvaco 2D device simulator has been utilised to comprehensively simulate the suggested DSC-SPCPT cancer detector [ 35 ]. Section 2 provides the simulator modeling and device architecture. The comprehensive results and discussion part are presented in Section 3. Lastly, the conclusion related to the complete investigation is provided in Section 4. 2. DSC-SPCPT BIOSENSOR DESIGN Figure 1 depicts the cross-section of a source pocket-based charge plasma TFET with a dual source cavity (DSC-SPCPT) biosensor. The intrinsic body of the charge plasma TFET can address the problems of complex manufacturing, a limited thermal budget, and random dopant fluctuations (RDFs) [ 27 – 29 ]. The source and drain metal electrodes are chosen to be platinum and hafnium with work functions of 3.90 eV and 5.93 eV, respectively. Two spacers in the source and drain of the biosensor have lengths of 2 nm and 15 nm, respectively. Adding a SiGe pocket to the source also enhances its ability to drive current, making it a desirable choice for many advanced semiconductor technologies. Per industry standards, we have taken 40% of the germanium molar proportion in Si 1 − x Ge x . Here, the different breast cell lines are exposed to the sensor's etched dual source cavity. The dimensions related to the source cavity are provided in Table 1 . The thickness of the HfO 2 interfacial layer supporting the cavity immobilisation layer is 1 nm (T ox ). A non-cancerous cell (MCF-10A) and four cancerous (MCF-7, Hs578T, T47D, and MDA-MB-231) breast cells are examined in the study. The idea behind TFET sensing is that a change in the k-value alters the electric field and capacitance, which in turn alters the drain current. The biosensor’s sensitivity is assessed using the gradient change in different parameters relative to the air (reference). Table 1 Simulated design parameters of the suggested biosensor Parameters (symbols) Value Body thickness (T Si ) 10 nm HfO 2 gate dielectric thickness (T ox ) 1 nm Gate length (L G ) 30 nm Source work-function ( \(\:{\varvec{\phi\:}}_{\varvec{S}})\) 5.93 eV Gate work-function ( \(\:{\varvec{\phi\:}}_{\varvec{G}}\) ) 4.50 eV Drain work-function ( \(\:{\varvec{\phi\:}}_{\varvec{D}})\) 3.90 eV Drain spacer length (L S1 ) 15 nm Source spacer length (L S2 ) 2 nm Si 1 − x Ge x molar percentage (x) 40% Length of SiGe pocket (L SiGe ) 5 nm Height of SiGe pocket (h SiGe ) 10 nm Cavity thickness (T cavity ) 5 nm Cavity length (L cavity ) 30 nm Several physics models are used in conjunction with the Silvaco TCAD 2-D simulator to simulate the suggested DSC-SPCPT biosensor [ 35 ]. It implements the BBT.NONLOCAL model to offer precise charge carrier tunneling in both directions (forward and backwards) across the interface. The nonlocal band-to-band tunneling model uses QTX.MESH and QTY.MESH in both directions for the interband tunneling process. The BBT.FORWARD model overcomes tunneling junction convergence issues when a p-n junction is forward-biassed. In the higher doping regions, the BGN model enables bandgap narrowing effects. The grid incorporates precise and appropriate meshing in both directions to guarantee charge carrier tunneling along both interfaces (S-C and C-D). The Shockley-Read-Hall (SRH) model estimated the temperature dependence and trap carriers at the semiconductor/oxide interface, which resulted in recombination effects and leaking drain current. The simulation process considers the AUGER model, which examines the impact of faults and traps. The Lombardi CVT mobility model estimates charge conduction by considering the parallel electric field mobility. The Fermi–Dirac carrier statistics examines the Fermi model effect. For the precise estimation of different DC and RF parameters of the proposed biosensor, the aforementioned models are numerically calculated using Newton's approach. To ensure accurate TCAD Silvaco model calibration, the n-TFET is configured with exact device characteristics obtained from an experimentally designed TFET, as mentioned in [ 36 ]. The transfer characteristics for the simulated outcomes and the cited data are shown in Fig. 2 . The closely matching result confirms the precision of the model parameters used for testing. 3. RESULTS & DISCUSSION 3.1. Analog Performance Study A comprehensive review for diagnosing cancer is presented by examining the drain current performance of several breast cells, both cancerous and healthy. The present sensor's I d -V gs curve for different malignant cells, which are immobilized in the dual source cavity, is illustrated in Fig. 3 (a). Four distinct types of breast tumorigenic cells, including T47D, MCF-7, HS578t, and MDA-MB-231, have been examined here. The sensor's drain current (I d ) curve for healthy cells (MCF-10A) is compared to the results. At a drain bias of 1.0V, the biosensor exhibits the lowest drain current of 3.91×10 − 9 A/µm in the case of healthy cells at a gate bias of 1.5V. When the dual source cavity is exposed to multiple tumorigenic cells, the drain current magnitude improves substantially (by four decades). Higher capacitance coupling at the gate contact results in a stronger electric field, which causes this significant improvement in the I d magnitude. The malignant cell lines' wider k-value range (22.59–32.11) results in this stronger coupling. The DSC-SPCPT displays a larger ON current (I ON ) of 8.72×10 − 5 A/µm in the case of T47D, as illustrated in Fig. 3 (a). This value is higher than the outcomes of exposure to other cancerous cells, and HS578t yields the least magnitude of 3.41×10 − 5 A/µm among the four malignant cells. I ON magnitude with exposure to malignant cells is significantly greater than that of healthy cells. This larger difference alternately provides a greater current gradient, which subsequently aids in achieving improved drain current sensitivity. It is noteworthy that the biosensor's I ON rises without affecting the leakage current (I OFF ). Thus, the current ratio (I ON /I OFF ) improves substantially when the sensor is exposed to cancerous cells, as seen from Fig. 3 (b). For malignant cells, the DSC-SPCPT sensor displays a larger I ON /I OFF ratio of approximately 10 12 A/A because of greater I ON and unaffected I OFF . This magnitude is over four decades higher than the ratio of healthy cells (2.21×10 8 A/A). Additionally, this suggested biosensor offers a lower threshold voltage in the range of 0.568 V to 0.599 V for malignant cells, and this value is 20% lower than the V th magnitude in the case of healthy cells. Figure 4 illustrates a comparative investigation of the performance of transconductance (g m ) and TGF (transconductance generation factor) between healthy and four malignant breast cells. The DSC-SPCPT cancer detector yields the lowest g m of 1.59×10 − 8 S/µm for healthy cells at a gate voltage of 1.5V, as seen from Fig. 4 (a). However, g m sharply improves over three decades when the tumor is exposed to the device's dual source cavities. When exposed to HS578t and T47D cells, it rises to 8.51×10 − 5 S/µm and 2.02×10 − 4 S/µm, respectively. This substantial g m shift is due to a larger I d created with a higher electric field. The transconductance generation factor (TGF) follows a similar pattern, as seen in Fig. 4 (b). Since the fluctuation of g m /I d is greatest in the subthreshold domain, the suggested biosensor achieved its peak TGF in the subthreshold region due to a larger g m /I d variation in that region. The biosensor offers a higher peak TGF of 1.94×10 5 V − 1 in the case of T47D, and the value lowers to 2.79×10 2 V − 1 for healthy cells. As illustrated in Fig. 5 (a), the energy band diagram in the ON condition is utilized to explain the interband tunneling process. The effect of the valence and conduction band variation for the DSC-SPCPT biosensor is examined with exposure to the tumorigenic cells. The simulated results of the band analysis in the case of healthy cells are compared with those of T47D malignant cells. The simulation of the band analysis is carried out by taking a cutline along the x-axis at 1nm below the gate-body interface. T47D exhibits a larger band bending at the primary tunneling junction (S-C interface) at a gate bias of 1.5V, as seen from the figure. This implies faster interband tunneling at the respective interface of the DSC-SPCPT sensor. The shortest tunneling length at the interface has a smaller magnitude due to the higher energy band bending. Thus, more charge carriers are able to tunnel through the interface as a result, increasing the interband tunneling rate (IBT) and improving Id. The shortest tunneling length (λ) is the smallest separation between the valence and conduction bands, as shown in Fig. 5 (a) inset. The recommended sensor's λ value is higher when healthy cells are present, and it reduces with the exposure of T47D cells. This apparent difference is due to a larger increase in the k-value of the biomolecules present in the dual-source cavity. A comparison of the peak electric field and maximum IBT generation rate between healthy and T47D cancerous breast cells is presented in Fig. 5 (b). The suggested biosensor's peak absolute electric field is the lowest, measuring 1.91×10 6 V/cm for healthy cells, and increases to 3.38×10 6 V/cm with exposure to T47D cells. At V gs = 1.5 V, the biosensor also shows a higher interband tunneling rate (IBT) of 5.62×10 32 cm − 3 s with malignant breast cells. Compared to the IBT in the case of a healthy cell, this magnitude is four decades higher. The higher IBT generation rate and larger electric field allow more carriers through the channel and provide larger band bending, further increasing I d . The recommended sensor achieves a significantly improved sensitivity as it has a larger gradient for I ON , I ON /I OFF parameters with exposure to cancerous cells. A thorough sensitivity investigation is provided in the next section. 3.2. Sensitivity Investigation This section investigates the sensitivity of the suggested biosensor in terms of drain current and switching ratio. Sensitivity is an essential criterion for evaluating the efficacy of tumor detectors. Sensors of a high-sensitivity nature can easily and rapidly identify tumours, and early identification increases the probability of disease recovery. Sensitivity is estimated as the ratio of the unit change of different parameters to the reference (air). The gradient change is the difference between the active state and the reference condition. The air-filled source cavity serves as the reference condition. The term "active state (act)" refers to the sensor's exposure to healthy and cancerous cells. Equations ( 1 )-( 4 ) provide the mathematical expression for assessing the sensitivity. $$\:{S}_{Id}=\:\frac{{{I}_{d\:}}_{\left(act\right)}-\:{{I}_{d\:}}_{\left(air\right)}}{{{I}_{d\:}}_{\left(air\right)}}$$ 1 $$\:{S}_{ratio}=\:\frac{{\left[\frac{{I}_{ON}}{{I}_{OFF}}\right]}_{\left(act\right)}-\:{\left[\frac{{I}_{ON}}{{I}_{OFF}}\right]}_{\left(air\right)}}{{\left[\frac{{I}_{ON}}{{I}_{OFF}}\right]}_{\left(air\right)}}$$ 2 $$\:{S}_{gm}=\:\frac{{{g}_{m\:}}_{\left(act\right)}-\:{{g}_{m\:}}_{\left(air\right)}}{{{g}_{m\:}}_{\left(air\right)}}$$ 3 $$\:{S}_{vth}=\:\frac{{{V}_{th\:}}_{\left(act\right)}-\:{{V}_{th\:}}_{\left(air\right)}}{{{V}_{th\:}}_{\left(air\right)}}$$ 4 The suggested sensor's drain current sensitivity (S Id ) in the presence of malignant and healthy cells is shown in Fig. 6 (a). The biosensor offers a higher value of S Id for all conditions (healthy and four tumorigenic cells) at a gate bias of 1.00 V. For healthy cells, the DSC-SPCPT offers the lowest peak S Id of magnitude 9.85×10 6 , and with the exposure to cancerous cells, it increases by four decades. This sharp rise is caused by a greater drain current gradient at a higher dielectric constant. Figure 6 (b) compares the peak S Id of the biosensor for different malignant cells. A peak S id of 1.03×10 12 is achieved for T47D cells and drops to 3.26×10 11 in the case of HS578t. In addition, the sensor with a higher k-value (T47D) provides a much-enhanced current ratio sensitivity (S ratio ) than the results for healthy cells, as illustrated in Fig. 6 (b). T47D has a greater S ratio of 3.31×10 9 ; for HS578t, the magnitude progressively decreases by 55% (1.48×10 9 ). The healthy cell provides the least S ratio of 1.44×10 5 , four decades lower than the tumorigenic cell. Figure 7 (a) displays the transconductance sensitivity (S gm ) as a function of V gs at a constant V ds . The sensitivity curve will follow the S Id curve as obtained in Fig. 6 (a), as it is estimated from g m (1st order differentiation of I d ). The proposed cancer detector produces a peak S gm of 3.46×10 11 when exposed to T47D cell lines, steadily decreasing to 1.19×10 11 for HS578t. For a healthy cell, the sensor exhibits the lowest peak S gm of 7.97×10 6 . The comparison between regular and malignant cells' peak transconductance sensitivity (S gm ) and threshold voltage sensitivity (S vth ) is shown in Fig. 7 (b). The V th sensitivity analysis displays a steadily rising trend with a greater k-value for various tumorigenic cells. In the case of T47D exposure, the sensor's S vth is 0.299. However, a minimum S vth of 0.070 is found for the non-tumorigenic cell, which is four times lower than cancerous cells. 3.3. Impact of variation in the cavity thickness and length This section investigates the influence of cavity parameters upon the sensitivity performance of the recommended cancer detector. We have considered a nanocavity of length 30 nm and thickness of 5 nm etched in the source region of the double-gate charge plasma TFET. The cavity parameters play a critical role in optimizing the sensitivity as it is exposed to both healthy and cancerous biomolecules. Here, we have varied the cavity thickness (t cav ) from 3 nm to 5 nm and cavity length (L cav ) from 20 nm to 30 nm. Figure 8 shows the impact of cavity thickness variation upon the drain current sensitivity of the suggested sensor. The study is conducted with three different t cav values, 3 nm, 4 nm, and 5 nm, keeping L cav = 30 nm. The drain current sensitivity vs gate voltage for a healthy cell with variation in t cav is provided in Fig. 8 (a), and the results are compared with one of the malignant T47D cells. It can be seen that the sensor exhibits a higher value of peak S id for both cases at a lower thickness. The sensor offers a larger current gradient due to the higher I ds performance with reduced cavity thickness. The suggested DSC-SPCPT offers a peak S id of 1.72×10 7 and 1.74×10 12 for healthy and T47D, respectively, for t cav = 3 nm. The magnitude decreases gradually with an increase in t cav . The change in peak S id in the case of all four malignant cells with respect to thickness is illustrated in a comparative way in Fig. 8 (b). For T47D, the peak S id is 1.74×10 12 at 3 nm and reduces to 1.03×10 12 at 5 nm. The same scenario can also be seen for MCF-7, HS578t, and MDA-MB-231 malignant biomolecules. The effect of cavity length variation on the proposed sensor's drain current sensitivity is depicted in Fig. 9 . With t cav = 5 nm, the study is carried out using three distinct values of L cav : 20 nm, 25 nm, and 30 nm. Figure 9 (a) illustrates the S id performance with respect to gate voltage with variation in L cav . The outcomes of a healthy cell are compared with the results of one of the malignant T47D cells. In both situations, the sensor shows a bit higher peak S id value at a higher cavity length. The slightly increased I ON at larger L cav results in a somewhat greater current gradient offered by the biosensor. For L cav = 30 nm, the DSC-SPCPT provides a peak S id of 9.85×10 6 for healthy and 1.03×10 12 for T47D cells. A drop in L cav causes a slowish fall in S id magnitude. Figure 9 (b) provides a comparative illustration of the change in peak S id with L cav for each of the four cancer cells. At 30 nm length, the peak S id for T47D is 1.03×10 12 , while at 20 nm, it slightly decreases to 9.99×10 11 . Other cancerous biomolecules, MCF-7, HS578t, and MDA-MB-231, exhibit a similar situation. 3.4. Influence of temperature variation The I ds -V gs characteristics of the proposed biosensor when exposed to both tumorigenic and healthy T47D cells are displayed in Fig. 10 at a broader temperature range (T) of 200 K to 400 K. The DSC-SPCPT's drain current analysis is carried out at a temperature step change of 50 K. The sensor's leakage current (I OFF ) is largely influenced by temperature variation compared to the ON current (I ON ), as seen from both figures. The suggested biosensor exhibits a much lower I OFF of 5.61×10 − 18 A/µm at 200 K in the case of a healthy cell, and it rises sharply with an increase in temperature, as illustrated in Fig. 10 (a). The I OFF magnitude is 1.90×10 − 15 A/µm at 400 K, three decades larger than the result at 200 K. The I ON of the device will also increase marginally with T rise as seen in the inset Fig. 10 (a). For T47D malignant cells, the I OFF and I ON variations due to the temperature change are very similar. As per Fig. 10 (b), the magnitude of I OFF is 5.47×10 − 18 A/µm and 1.88×10 − 15 A/µm for 200 K and 400 K, respectively. Figure 11 (a) illustrates the DSC-SPCPT’s drain current sensitivity (S id ) performance with a broader temperature range as a function of gate voltage. A comparison is made between the results of the malignant T47D cells and those of a healthy cell. The sensor displays a greater peak S id at a lower T (200 K) in both cases. This higher S id magnitude is because of the greater drain current gradient in the subthreshold regime, as seen from Fig. 11 (a). With an increase in the T value, the magnitude progressively falls. The magnitude of the peak S id as a function of temperature, ranging from 200 K to 400 K, is provided in Fig. 11 (b). For T = 200 K, the DSC-SPCPT provides a peak S id of 1.52×10 13 for T47D cells, and the magnitude reduces by three decades to 3.83×10 10 at 400 K. The healthy cell exhibits a peak S id of 9.85×10 6 and 2.70×10 6 for 200 K and 400 K, respectively. It is worth mentioning that the malignant cells are severely affected by temperature variation than the regular/noncancerous cells. Other malignant cells, MCF-7, HS578 T, and MDA-MB-231, were also significantly affected by T variation. 4. CONCLUSION Here, the suggested DSC-SPCPT sensor was used to detect four malignant breast cells (MDA-MB-231, MCF-7, Hs578T, and T47D) and distinguish them from a healthy cell (MCF-10). Dielectric value (k-value) variation in the case of different malignant cells is the key principle behind this investigation. Different sensitivity parameters such as S Id , S ratio , S gm and S vth were estimated when exposed to both kinds of cells. The recommended biosensor offers a larger S Id of 1.03×10 12 , S ratio of 3.31×10 9 and S gm of 3.46×10 11 compared to the healthy cell. An in-depth analysis was also conducted to examine the effect of cavity length and thickness on the sensor's sensitivity. Due to its early detection capabilities, lack of doping fluctuations, ease of manufacture, optimised transduction process, and compatibility with MOS technology, such a biosensor may be a suitable option for diagnosing breast cancer. Declarations Funding Information: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contribution S. Dash has designed and simulated all the results. Further, he wrote the manuscript and did all the analysis. Acknowledgment: The author acknowledges the support from the Device Simulation Laboratory, Institute of Technical Education and Research, Siksha 'O' Anusandhan Deemed to be University, Bhubaneswar, Odisha, India, for facilitating the Silvaco TCAD simulation software to carry out the research. 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F., Hilsenbeck, K., Nirschl, T., Oswald, M., Stepper, C., Weis, M., Schmitt-Landsiedel, D., & Hansch, W. (2004). Complementary tunneling transistor for low power application. Solid-State Electronics , 48 , 2281–2286. 10.1016/j.sse.2004.04.006 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 23 Dec, 2025 Reviews received at journal 22 Dec, 2025 Reviews received at journal 21 Dec, 2025 Reviews received at journal 20 Dec, 2025 Reviews received at journal 17 Dec, 2025 Reviews received at journal 15 Dec, 2025 Reviews received at journal 15 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers agreed at journal 11 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers invited by journal 10 Dec, 2025 Editor assigned by journal 27 Nov, 2025 Submission checks completed at journal 18 Nov, 2025 First submitted to journal 17 Nov, 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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1","display":"","copyAsset":false,"role":"figure","size":183717,"visible":true,"origin":"","legend":"\u003cp\u003eSchematics of a source pocket-based charge plasma TFET with a dual source cavity (DSC-SPCPT) sensor with the exposure to both healthy and tumorigenic breast cells in the nanocavity\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/a9e5abfb3e6b712da1e50458.jpeg"},{"id":98449462,"identity":"f6dfba4d-9c7c-495b-917a-ab1537361c6f","added_by":"auto","created_at":"2025-12-17 17:29:34","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":85179,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the transfer curve between the simulated TFET and the experimental data 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4","display":"","copyAsset":false,"role":"figure","size":775310,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Transconductance and (b) transconductance generation factor (TGF) as a function of V\u003csub\u003egs\u003c/sub\u003e in the presence of various malignant breast cell lines\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/05335a49f77f0f44d65bde99.jpeg"},{"id":98450134,"identity":"26c3b115-704a-4579-a1aa-42cef5041107","added_by":"auto","created_at":"2025-12-17 17:30:13","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":897825,"visible":true,"origin":"","legend":"\u003cp\u003e(a). Energy band analysis (b) peak electric field and maximum interband tunneling rate (IBT) for the proposed biosensor at V\u003csub\u003egs \u003c/sub\u003e= 1.5V when exposed to healthy and malignant breast cells\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/d0955b3ac3e08f1ee218cdf8.jpeg"},{"id":98450212,"identity":"c9f5b39b-2f03-4f42-a979-0445e1a7af9d","added_by":"auto","created_at":"2025-12-17 17:30:15","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1000199,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Drain current sensitivity (S\u003csub\u003eId\u003c/sub\u003e) as a function of gate voltage, (b) peak S\u003csub\u003eId \u003c/sub\u003eand current ratio sensitivity (S\u003csub\u003eratio\u003c/sub\u003e) when exposed to both types of breast cells\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/69121dcf41be244d885590d7.jpeg"},{"id":98450100,"identity":"dfe939f5-207d-483c-a761-16ae6e51fbd9","added_by":"auto","created_at":"2025-12-17 17:30:10","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":840273,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Transconductance sensitivity (S\u003csub\u003egm\u003c/sub\u003e) as a function of gate bias, (b) a comparative analysis of peak S\u003csub\u003egm\u003c/sub\u003e and threshold voltage sensitivity (S\u003csub\u003evth\u003c/sub\u003e) with exposure to both malicious and healthy cells\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/d85c6d7953b7da278e14de81.jpeg"},{"id":98450138,"identity":"ab92cfc1-7fcd-42b7-ac1e-bd3fb361ca29","added_by":"auto","created_at":"2025-12-17 17:30:13","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":854499,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of varying cavity thickness (t\u003csub\u003ecav\u003c/sub\u003e) upon (a) S\u003csub\u003eId \u003c/sub\u003ecurve, and (b) peak S\u003csub\u003eId\u003c/sub\u003e when exposed to both malicious and healthy cells\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/61a05c4b3da7b72d4ce104d8.jpeg"},{"id":98450247,"identity":"eac2fc47-59b5-4dbe-98a5-6109a21a31ac","added_by":"auto","created_at":"2025-12-17 17:30:15","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":839492,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of varying cavity length (L\u003csub\u003ecav\u003c/sub\u003e) upon (a) S\u003csub\u003eId \u003c/sub\u003echaracteristics, and (b) peak S\u003csub\u003eId\u003c/sub\u003e when exposed to both malicious and healthy cells\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/a0980776b576bf441883b6bc.jpeg"},{"id":98449959,"identity":"c07e3ebd-fc12-46b2-b3b5-13f1f69a3fd2","added_by":"auto","created_at":"2025-12-17 17:30:06","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":698314,"visible":true,"origin":"","legend":"\u003cp\u003eI\u003csub\u003eds\u003c/sub\u003e vs V\u003csub\u003egs\u003c/sub\u003e curve for the suggested sensor as a function of temperature when exposed to (a) healthy cells and (b) T47D malignant cells\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/d03001725e41b6d4dc18dd22.jpeg"},{"id":98450001,"identity":"7d6b2632-2b6e-442c-88b3-71a9f0b85cb0","added_by":"auto","created_at":"2025-12-17 17:30:08","extension":"jpeg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":681696,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of temperature variation upon (a) drain current sensitivity and (b) peak S\u003csub\u003eId\u003c/sub\u003e when exposed to both malicious and healthy cells\u003c/p\u003e","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/539e3fea0d1ba1d9929dedc6.jpeg"},{"id":98622607,"identity":"9cb89e7f-a9d8-4b16-bf65-981cdeb4ea4a","added_by":"auto","created_at":"2025-12-19 16:59:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8423163,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8131934/v1/2cd90661-26f2-4c72-88de-6a82c88087c7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Design \u0026 Analysis of a Highly Sensitive Biosensor for Detecting Breast Malignancy using a Charge Plasma TFET with SiGe Pocket ","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eThe growing cancer mortality rate is one of the biggest challenges the world is currently experiencing. Specific genetic alterations in tissues cause cancer. Tumors are masses of changed tissue caused by these cells' uncontrolled reproduction and multiplication. It is classified according to the type of cell created and where it originates. Breast, Colon, Lung and Rectal cancers are the most common across the world due to their high incidence. However, breast cancer is among the most commonly found cancers in women [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Early identification can lead to more comprehensive therapy and fewer fatalities. In the initial phase, X-ray mammography is considered for identifying breast cancer. Although this method has made significant progress, it has been shown to have several shortcomings [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. For larger breasts, the sensitivity and specificity of this technique declined sharply to 67% and 89%, respectively [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Conversely, high-contrast Magnetic Resonance Imaging (MRI) offers a sensitivity of more than 90% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. MRI is an expensive and time-consuming process that requires an in-hospital procedure. Ultrasonography provides a greater rate of false positives compared to mammography [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Furthermore, it is challenging for women to access high-quality diagnostic treatments when they live in secluded areas. Because medical expenses are rising, even in affluent countries, there is a current demand for a trustworthy, quick, and affordable cancer diagnosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicrowave-based cancer diagnosis and treatment is one of the most important scientific areas to explore. This type of research relies primarily on the fact that healthy and cancerous cells have substantially distinct dielectric properties [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A higher water content in cancerous tissues enhances microwave dispersion and provides a higher dielectric constant. Microwave spectroscopy has been used in several scientific studies to analyse living cells electrically [\u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16 CR17 CR18\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. An open-ended coaxial probe procedure was used for conducting dielectric testing on animal tissues in earlier days. Stuchly et al. evaluated tissue specimens from cats [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Rat tissues were used to assess the electrical characteristics at 30 MHz to 2 GHz [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Eventually, the research went further to include human samples. In 1994, Joines et al. conducted an ex vivo dielectric study of several human samples at frequencies ranging from 50 to 900 MHz [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Lazebnik et al. conducted a comprehensive study to examine breast tissues at 0.5 GHz to 2 GHz [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. According to the study, breast cell diversity and obesity influence the dielectric value of the cells. Martellosio et al. explored various dielectric features of breast cells for a wider frequency range [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The dielectric measurements of different cancer cells were also experimentally demonstrated by Hussein et al. in 2019 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The researchers evaluated both healthy and malignant cells' k-values [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt microwave frequencies, dielectric-modulated biosensors are one of the effective methods for early cancer detection, as the biomarkers associated with cells have a variable dielectric constant (k-value) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Tunnel field-effect transistors (TFETs) are among the most promising options for biosensor design due to their low power consumption and superior sensitivity [\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27 CR28\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These sensors' interband tunneling current transmission method enables them to surpass the drawbacks of traditional MOSFETs. Several researchers have examined the effectiveness of a dual-metal gate DLTFET as a biosensor [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These sensors can be an excellent choice for a number of critical applications, such as environmental monitoring and medical diagnostics, as a result of their higher sensitivity at lower drain bias. In 2022, Singh and Singh [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] developed a charge plasma TFET for breast cancer detection. Priyadarshani et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] developed an ultrasensitive FET biosensor for detecting cancer. A TFET biosensor with improved current sensitivity was proposed in 2024 for breast cancer diagnosis, utilising dielectric variation [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA source pocket-based charge plasma TFET with a dual source cavity (DSC-SPCPT) biosensor is presented here to effectively detect healthy and cancerous breast cells. Here, we have designed a compound SiGe source pocket near the source-channel (S-C) interface, which enhances drain current and sensitivity with exposure to tumorigenic cells. An extensive electrical analysis of the suggested sensor was conducted using varying cell samples with different dielectric constants (k-values). The sensitivity investigation of the biosensor is estimated by considering several electrical parameters, such as ON-current, current ratio, transconductance, and threshold voltage, in the presence of both types of breast cells. The study also examines how cavity length and thickness affect the sensitivity performance of both cells. The Silvaco 2D device simulator has been utilised to comprehensively simulate the suggested DSC-SPCPT cancer detector [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Section 2 provides the simulator modeling and device architecture. The comprehensive results and discussion part are presented in Section 3. Lastly, the conclusion related to the complete investigation is provided in Section 4.\u003c/p\u003e"},{"header":"2. DSC-SPCPT BIOSENSOR DESIGN","content":"\u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts the cross-section of a source pocket-based charge plasma TFET with a dual source cavity (DSC-SPCPT) biosensor. The intrinsic body of the charge plasma TFET can address the problems of complex manufacturing, a limited thermal budget, and random dopant fluctuations (RDFs) [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The source and drain metal electrodes are chosen to be platinum and hafnium with work functions of 3.90 eV and 5.93 eV, respectively. Two spacers in the source and drain of the biosensor have lengths of 2 nm and 15 nm, respectively. Adding a SiGe pocket to the source also enhances its ability to drive current, making it a desirable choice for many advanced semiconductor technologies. Per industry standards, we have taken 40% of the germanium molar proportion in Si\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;x\u003c/sub\u003eGe\u003csub\u003ex\u003c/sub\u003e. Here, the different breast cell lines are exposed to the sensor's etched dual source cavity. The dimensions related to the source cavity are provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The thickness of the HfO\u003csub\u003e2\u003c/sub\u003e interfacial layer supporting the cavity immobilisation layer is 1 nm (T\u003csub\u003eox\u003c/sub\u003e). A non-cancerous cell (MCF-10A) and four cancerous (MCF-7, Hs578T, T47D, and MDA-MB-231) breast cells are examined in the study. The idea behind TFET sensing is that a change in the k-value alters the electric field and capacitance, which in turn alters the drain current. The biosensor\u0026rsquo;s sensitivity is assessed using the gradient change in different parameters relative to the air (reference).\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\u003eSimulated design parameters of the suggested biosensor\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters (symbols)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody thickness (T\u003csub\u003eSi\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHfO\u003csub\u003e2\u003c/sub\u003e gate dielectric thickness (T\u003csub\u003eox\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGate length (L\u003csub\u003eG\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource work-function (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{\\phi\\:}}_{\\varvec{S}})\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.93 eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGate work-function (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{\\phi\\:}}_{\\varvec{G}}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.50 eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrain work-function (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{\\phi\\:}}_{\\varvec{D}})\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.90 eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrain spacer length (L\u003csub\u003eS1\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource spacer length (L\u003csub\u003eS2\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSi\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;x\u003c/sub\u003eGe\u003csub\u003ex\u003c/sub\u003e molar percentage (x)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of SiGe pocket (L\u003csub\u003eSiGe\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight of SiGe pocket (h\u003csub\u003eSiGe\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCavity thickness (T\u003csub\u003ecavity\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 nm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCavity length (L\u003csub\u003ecavity\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 nm\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\u003eSeveral physics models are used in conjunction with the Silvaco TCAD 2-D simulator to simulate the suggested DSC-SPCPT biosensor [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It implements the BBT.NONLOCAL model to offer precise charge carrier tunneling in both directions (forward and backwards) across the interface. The nonlocal band-to-band tunneling model uses QTX.MESH and QTY.MESH in both directions for the interband tunneling process. The BBT.FORWARD model overcomes tunneling junction convergence issues when a p-n junction is forward-biassed. In the higher doping regions, the BGN model enables bandgap narrowing effects. The grid incorporates precise and appropriate meshing in both directions to guarantee charge carrier tunneling along both interfaces (S-C and C-D). The Shockley-Read-Hall (SRH) model estimated the temperature dependence and trap carriers at the semiconductor/oxide interface, which resulted in recombination effects and leaking drain current. The simulation process considers the AUGER model, which examines the impact of faults and traps. The Lombardi CVT mobility model estimates charge conduction by considering the parallel electric field mobility. The Fermi\u0026ndash;Dirac carrier statistics examines the Fermi model effect. For the precise estimation of different DC and RF parameters of the proposed biosensor, the aforementioned models are numerically calculated using Newton's approach. To ensure accurate TCAD Silvaco model calibration, the n-TFET is configured with exact device characteristics obtained from an experimentally designed TFET, as mentioned in [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The transfer characteristics for the simulated outcomes and the cited data are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The closely matching result confirms the precision of the model parameters used for testing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. RESULTS \u0026 DISCUSSION","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Analog Performance Study\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA comprehensive review for diagnosing cancer is presented by examining the drain current performance of several breast cells, both cancerous and healthy. The present sensor's I\u003csub\u003ed\u003c/sub\u003e-V\u003csub\u003egs\u003c/sub\u003e curve for different malignant cells, which are immobilized in the dual source cavity, is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(a). Four distinct types of breast tumorigenic cells, including T47D, MCF-7, HS578t, and MDA-MB-231, have been examined here. The sensor's drain current (I\u003csub\u003ed\u003c/sub\u003e) curve for healthy cells (MCF-10A) is compared to the results. At a drain bias of 1.0V, the biosensor exhibits the lowest drain current of 3.91\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e A/\u0026micro;m in the case of healthy cells at a gate bias of 1.5V. When the dual source cavity is exposed to multiple tumorigenic cells, the drain current magnitude improves substantially (by four decades). Higher capacitance coupling at the gate contact results in a stronger electric field, which causes this significant improvement in the I\u003csub\u003ed\u003c/sub\u003e magnitude. The malignant cell lines' wider k-value range (22.59\u0026ndash;32.11) results in this stronger coupling. The DSC-SPCPT displays a larger ON current (I\u003csub\u003eON\u003c/sub\u003e) of 8.72\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e A/\u0026micro;m in the case of T47D, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(a). This value is higher than the outcomes of exposure to other cancerous cells, and HS578t yields the least magnitude of 3.41\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e A/\u0026micro;m among the four malignant cells. I\u003csub\u003eON\u003c/sub\u003e magnitude with exposure to malignant cells is significantly greater than that of healthy cells. This larger difference alternately provides a greater current gradient, which subsequently aids in achieving improved drain current sensitivity. It is noteworthy that the biosensor's I\u003csub\u003eON\u003c/sub\u003e rises without affecting the leakage current (I\u003csub\u003eOFF\u003c/sub\u003e). Thus, the current ratio (I\u003csub\u003eON\u003c/sub\u003e/I\u003csub\u003eOFF\u003c/sub\u003e) improves substantially when the sensor is exposed to cancerous cells, as seen from Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(b). For malignant cells, the DSC-SPCPT sensor displays a larger I\u003csub\u003eON\u003c/sub\u003e/I\u003csub\u003eOFF\u003c/sub\u003e ratio of approximately 10\u003csup\u003e12\u003c/sup\u003e A/A because of greater I\u003csub\u003eON\u003c/sub\u003e and unaffected I\u003csub\u003eOFF\u003c/sub\u003e. This magnitude is over four decades higher than the ratio of healthy cells (2.21\u0026times;10\u003csup\u003e8\u003c/sup\u003e A/A). Additionally, this suggested biosensor offers a lower threshold voltage in the range of 0.568 V to 0.599 V for malignant cells, and this value is 20% lower than the V\u003csub\u003eth\u003c/sub\u003e magnitude in the case of healthy cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates a comparative investigation of the performance of transconductance (g\u003csub\u003em\u003c/sub\u003e) and TGF (transconductance generation factor) between healthy and four malignant breast cells. The DSC-SPCPT cancer detector yields the lowest g\u003csub\u003em\u003c/sub\u003e of 1.59\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e S/\u0026micro;m for healthy cells at a gate voltage of 1.5V, as seen from Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(a). However, g\u003csub\u003em\u003c/sub\u003e sharply improves over three decades when the tumor is exposed to the device's dual source cavities. When exposed to HS578t and T47D cells, it rises to 8.51\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e S/\u0026micro;m and 2.02\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e S/\u0026micro;m, respectively. This substantial g\u003csub\u003em\u003c/sub\u003e shift is due to a larger I\u003csub\u003ed\u003c/sub\u003e created with a higher electric field. The transconductance generation factor (TGF) follows a similar pattern, as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(b). Since the fluctuation of g\u003csub\u003em\u003c/sub\u003e/I\u003csub\u003ed\u003c/sub\u003e is greatest in the subthreshold domain, the suggested biosensor achieved its peak TGF in the subthreshold region due to a larger g\u003csub\u003em\u003c/sub\u003e/I\u003csub\u003ed\u003c/sub\u003e variation in that region. The biosensor offers a higher peak TGF of 1.94\u0026times;10\u003csup\u003e5\u003c/sup\u003e V\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in the case of T47D, and the value lowers to 2.79\u0026times;10\u003csup\u003e2\u003c/sup\u003e V\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for healthy cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(a), the energy band diagram in the ON condition is utilized to explain the interband tunneling process. The effect of the valence and conduction band variation for the DSC-SPCPT biosensor is examined with exposure to the tumorigenic cells. The simulated results of the band analysis in the case of healthy cells are compared with those of T47D malignant cells. The simulation of the band analysis is carried out by taking a cutline along the x-axis at 1nm below the gate-body interface. T47D exhibits a larger band bending at the primary tunneling junction (S-C interface) at a gate bias of 1.5V, as seen from the figure. This implies faster interband tunneling at the respective interface of the DSC-SPCPT sensor. The shortest tunneling length at the interface has a smaller magnitude due to the higher energy band bending. Thus, more charge carriers are able to tunnel through the interface as a result, increasing the interband tunneling rate (IBT) and improving Id. The shortest tunneling length (λ) is the smallest separation between the valence and conduction bands, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(a) inset. The recommended sensor's λ value is higher when healthy cells are present, and it reduces with the exposure of T47D cells. This apparent difference is due to a larger increase in the k-value of the biomolecules present in the dual-source cavity. A comparison of the peak electric field and maximum IBT generation rate between healthy and T47D cancerous breast cells is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(b). The suggested biosensor's peak absolute electric field is the lowest, measuring 1.91\u0026times;10\u003csup\u003e6\u003c/sup\u003e V/cm for healthy cells, and increases to 3.38\u0026times;10\u003csup\u003e6\u003c/sup\u003e V/cm with exposure to T47D cells. At V\u003csub\u003egs\u003c/sub\u003e = 1.5 V, the biosensor also shows a higher interband tunneling rate (IBT) of 5.62\u0026times;10\u003csup\u003e32\u003c/sup\u003e cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003es with malignant breast cells. Compared to the IBT in the case of a healthy cell, this magnitude is four decades higher. The higher IBT generation rate and larger electric field allow more carriers through the channel and provide larger band bending, further increasing I\u003csub\u003ed\u003c/sub\u003e. The recommended sensor achieves a significantly improved sensitivity as it has a larger gradient for I\u003csub\u003eON\u003c/sub\u003e, I\u003csub\u003eON\u003c/sub\u003e/I\u003csub\u003eOFF\u003c/sub\u003e parameters with exposure to cancerous cells. A thorough sensitivity investigation is provided in the next section.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Sensitivity Investigation\u003c/h2\u003e \u003cp\u003eThis section investigates the sensitivity of the suggested biosensor in terms of drain current and switching ratio. Sensitivity is an essential criterion for evaluating the efficacy of tumor detectors. Sensors of a high-sensitivity nature can easily and rapidly identify tumours, and early identification increases the probability of disease recovery. Sensitivity is estimated as the ratio of the unit change of different parameters to the reference (air). The gradient change is the difference between the active state and the reference condition. The air-filled source cavity serves as the reference condition. The term \"active state (act)\" refers to the sensor's exposure to healthy and cancerous cells. Equations\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)-(\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) provide the mathematical expression for assessing the sensitivity.\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{S}_{Id}=\\:\\frac{{{I}_{d\\:}}_{\\left(act\\right)}-\\:{{I}_{d\\:}}_{\\left(air\\right)}}{{{I}_{d\\:}}_{\\left(air\\right)}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{S}_{ratio}=\\:\\frac{{\\left[\\frac{{I}_{ON}}{{I}_{OFF}}\\right]}_{\\left(act\\right)}-\\:{\\left[\\frac{{I}_{ON}}{{I}_{OFF}}\\right]}_{\\left(air\\right)}}{{\\left[\\frac{{I}_{ON}}{{I}_{OFF}}\\right]}_{\\left(air\\right)}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:{S}_{gm}=\\:\\frac{{{g}_{m\\:}}_{\\left(act\\right)}-\\:{{g}_{m\\:}}_{\\left(air\\right)}}{{{g}_{m\\:}}_{\\left(air\\right)}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{S}_{vth}=\\:\\frac{{{V}_{th\\:}}_{\\left(act\\right)}-\\:{{V}_{th\\:}}_{\\left(air\\right)}}{{{V}_{th\\:}}_{\\left(air\\right)}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe suggested sensor's drain current sensitivity (S\u003csub\u003eId\u003c/sub\u003e) in the presence of malignant and healthy cells is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(a). The biosensor offers a higher value of S\u003csub\u003eId\u003c/sub\u003e for all conditions (healthy and four tumorigenic cells) at a gate bias of 1.00 V. For healthy cells, the DSC-SPCPT offers the lowest peak S\u003csub\u003eId\u003c/sub\u003e of magnitude 9.85\u0026times;10\u003csup\u003e6\u003c/sup\u003e, and with the exposure to cancerous cells, it increases by four decades. This sharp rise is caused by a greater drain current gradient at a higher dielectric constant. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(b) compares the peak S\u003csub\u003eId\u003c/sub\u003e of the biosensor for different malignant cells. A peak S\u003csub\u003eid\u003c/sub\u003e of 1.03\u0026times;10\u003csup\u003e12\u003c/sup\u003e is achieved for T47D cells and drops to 3.26\u0026times;10\u003csup\u003e11\u003c/sup\u003e in the case of HS578t. In addition, the sensor with a higher k-value (T47D) provides a much-enhanced current ratio sensitivity (S\u003csub\u003eratio\u003c/sub\u003e) than the results for healthy cells, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(b). T47D has a greater S\u003csub\u003eratio\u003c/sub\u003e of 3.31\u0026times;10\u003csup\u003e9\u003c/sup\u003e; for HS578t, the magnitude progressively decreases by 55% (1.48\u0026times;10\u003csup\u003e9\u003c/sup\u003e). The healthy cell provides the least S\u003csub\u003eratio\u003c/sub\u003e of 1.44\u0026times;10\u003csup\u003e5\u003c/sup\u003e, four decades lower than the tumorigenic cell.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(a) displays the transconductance sensitivity (S\u003csub\u003egm\u003c/sub\u003e) as a function of V\u003csub\u003egs\u003c/sub\u003e at a constant V\u003csub\u003eds\u003c/sub\u003e. The sensitivity curve will follow the S\u003csub\u003eId\u003c/sub\u003e curve as obtained in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(a), as it is estimated from g\u003csub\u003em\u003c/sub\u003e (1st order differentiation of I\u003csub\u003ed\u003c/sub\u003e). The proposed cancer detector produces a peak S\u003csub\u003egm\u003c/sub\u003e of 3.46\u0026times;10\u003csup\u003e11\u003c/sup\u003e when exposed to T47D cell lines, steadily decreasing to 1.19\u0026times;10\u003csup\u003e11\u003c/sup\u003e for HS578t. For a healthy cell, the sensor exhibits the lowest peak S\u003csub\u003egm\u003c/sub\u003e of 7.97\u0026times;10\u003csup\u003e6\u003c/sup\u003e. The comparison between regular and malignant cells' peak transconductance sensitivity (S\u003csub\u003egm\u003c/sub\u003e) and threshold voltage sensitivity (S\u003csub\u003evth\u003c/sub\u003e) is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(b). The V\u003csub\u003eth\u003c/sub\u003e sensitivity analysis displays a steadily rising trend with a greater k-value for various tumorigenic cells. In the case of T47D exposure, the sensor's S\u003csub\u003evth\u003c/sub\u003e is 0.299. However, a minimum S\u003csub\u003evth\u003c/sub\u003e of 0.070 is found for the non-tumorigenic cell, which is four times lower than cancerous cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Impact of variation in the cavity thickness and length\u003c/h2\u003e \u003cp\u003eThis section investigates the influence of cavity parameters upon the sensitivity performance of the recommended cancer detector. We have considered a nanocavity of length 30 nm and thickness of 5 nm etched in the source region of the double-gate charge plasma TFET. The cavity parameters play a critical role in optimizing the sensitivity as it is exposed to both healthy and cancerous biomolecules. Here, we have varied the cavity thickness (t\u003csub\u003ecav\u003c/sub\u003e) from 3 nm to 5 nm and cavity length (L\u003csub\u003ecav\u003c/sub\u003e) from 20 nm to 30 nm.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the impact of cavity thickness variation upon the drain current sensitivity of the suggested sensor. The study is conducted with three different t\u003csub\u003ecav\u003c/sub\u003e values, 3 nm, 4 nm, and 5 nm, keeping L\u003csub\u003ecav\u003c/sub\u003e = 30 nm. The drain current sensitivity vs gate voltage for a healthy cell with variation in t\u003csub\u003ecav\u003c/sub\u003e is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e(a), and the results are compared with one of the malignant T47D cells. It can be seen that the sensor exhibits a higher value of peak S\u003csub\u003eid\u003c/sub\u003e for both cases at a lower thickness. The sensor offers a larger current gradient due to the higher I\u003csub\u003eds\u003c/sub\u003e performance with reduced cavity thickness. The suggested DSC-SPCPT offers a peak S\u003csub\u003eid\u003c/sub\u003e of 1.72\u0026times;10\u003csup\u003e7\u003c/sup\u003e and 1.74\u0026times;10\u003csup\u003e12\u003c/sup\u003e for healthy and T47D, respectively, for t\u003csub\u003ecav\u003c/sub\u003e = 3 nm. The magnitude decreases gradually with an increase in t\u003csub\u003ecav\u003c/sub\u003e. The change in peak S\u003csub\u003eid\u003c/sub\u003e in the case of all four malignant cells with respect to thickness is illustrated in a comparative way in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e(b). For T47D, the peak S\u003csub\u003eid\u003c/sub\u003e is 1.74\u0026times;10\u003csup\u003e12\u003c/sup\u003e at 3 nm and reduces to 1.03\u0026times;10\u003csup\u003e12\u003c/sup\u003e at 5 nm. The same scenario can also be seen for MCF-7, HS578t, and MDA-MB-231 malignant biomolecules.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe effect of cavity length variation on the proposed sensor's drain current sensitivity is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. With t\u003csub\u003ecav\u003c/sub\u003e = 5 nm, the study is carried out using three distinct values of L\u003csub\u003ecav\u003c/sub\u003e: 20 nm, 25 nm, and 30 nm. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e(a) illustrates the S\u003csub\u003eid\u003c/sub\u003e performance with respect to gate voltage with variation in L\u003csub\u003ecav\u003c/sub\u003e. The outcomes of a healthy cell are compared with the results of one of the malignant T47D cells. In both situations, the sensor shows a bit higher peak S\u003csub\u003eid\u003c/sub\u003e value at a higher cavity length. The slightly increased I\u003csub\u003eON\u003c/sub\u003e at larger L\u003csub\u003ecav\u003c/sub\u003e results in a somewhat greater current gradient offered by the biosensor. For L\u003csub\u003ecav\u003c/sub\u003e = 30 nm, the DSC-SPCPT provides a peak S\u003csub\u003eid\u003c/sub\u003e of 9.85\u0026times;10\u003csup\u003e6\u003c/sup\u003e for healthy and 1.03\u0026times;10\u003csup\u003e12\u003c/sup\u003e for T47D cells. A drop in L\u003csub\u003ecav\u003c/sub\u003e causes a slowish fall in S\u003csub\u003eid\u003c/sub\u003e magnitude. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e(b) provides a comparative illustration of the change in peak S\u003csub\u003eid\u003c/sub\u003e with L\u003csub\u003ecav\u003c/sub\u003e for each of the four cancer cells. At 30 nm length, the peak S\u003csub\u003eid\u003c/sub\u003e for T47D is 1.03\u0026times;10\u003csup\u003e12\u003c/sup\u003e, while at 20 nm, it slightly decreases to 9.99\u0026times;10\u003csup\u003e11\u003c/sup\u003e. Other cancerous biomolecules, MCF-7, HS578t, and MDA-MB-231, exhibit a similar situation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Influence of temperature variation\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe I\u003csub\u003eds\u003c/sub\u003e-V\u003csub\u003egs\u003c/sub\u003e characteristics of the proposed biosensor when exposed to both tumorigenic and healthy T47D cells are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e at a broader temperature range (T) of 200 K to 400 K. The DSC-SPCPT's drain current analysis is carried out at a temperature step change of 50 K. The sensor's leakage current (I\u003csub\u003eOFF\u003c/sub\u003e) is largely influenced by temperature variation compared to the ON current (I\u003csub\u003eON\u003c/sub\u003e), as seen from both figures. The suggested biosensor exhibits a much lower I\u003csub\u003eOFF\u003c/sub\u003e of 5.61\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;18\u003c/sup\u003e A/\u0026micro;m at 200 K in the case of a healthy cell, and it rises sharply with an increase in temperature, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e(a). The I\u003csub\u003eOFF\u003c/sub\u003e magnitude is 1.90\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e A/\u0026micro;m at 400 K, three decades larger than the result at 200 K. The I\u003csub\u003eON\u003c/sub\u003e of the device will also increase marginally with T rise as seen in the inset Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e(a). For T47D malignant cells, the I\u003csub\u003eOFF\u003c/sub\u003e and I\u003csub\u003eON\u003c/sub\u003e variations due to the temperature change are very similar. As per Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e(b), the magnitude of I\u003csub\u003eOFF\u003c/sub\u003e is 5.47\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;18\u003c/sup\u003e A/\u0026micro;m and 1.88\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e A/\u0026micro;m for 200 K and 400 K, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e(a) illustrates the DSC-SPCPT\u0026rsquo;s drain current sensitivity (S\u003csub\u003eid\u003c/sub\u003e) performance with a broader temperature range as a function of gate voltage. A comparison is made between the results of the malignant T47D cells and those of a healthy cell. The sensor displays a greater peak S\u003csub\u003eid\u003c/sub\u003e at a lower T (200 K) in both cases. This higher S\u003csub\u003eid\u003c/sub\u003e magnitude is because of the greater drain current gradient in the subthreshold regime, as seen from Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e(a). With an increase in the T value, the magnitude progressively falls. The magnitude of the peak S\u003csub\u003eid\u003c/sub\u003e as a function of temperature, ranging from 200 K to 400 K, is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e(b). For T\u0026thinsp;=\u0026thinsp;200 K, the DSC-SPCPT provides a peak S\u003csub\u003eid\u003c/sub\u003e of 1.52\u0026times;10\u003csup\u003e13\u003c/sup\u003e for T47D cells, and the magnitude reduces by three decades to 3.83\u0026times;10\u003csup\u003e10\u003c/sup\u003e at 400 K. The healthy cell exhibits a peak S\u003csub\u003eid\u003c/sub\u003e of 9.85\u0026times;10\u003csup\u003e6\u003c/sup\u003e and 2.70\u0026times;10\u003csup\u003e6\u003c/sup\u003e for 200 K and 400 K, respectively. It is worth mentioning that the malignant cells are severely affected by temperature variation than the regular/noncancerous cells. Other malignant cells, MCF-7, HS578 T, and MDA-MB-231, were also significantly affected by T variation.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. CONCLUSION","content":"\u003cp\u003eHere, the suggested DSC-SPCPT sensor was used to detect four malignant breast cells (MDA-MB-231, MCF-7, Hs578T, and T47D) and distinguish them from a healthy cell (MCF-10). Dielectric value (k-value) variation in the case of different malignant cells is the key principle behind this investigation. Different sensitivity parameters such as S\u003csub\u003eId\u003c/sub\u003e, S\u003csub\u003eratio\u003c/sub\u003e, S\u003csub\u003egm\u003c/sub\u003e and S\u003csub\u003evth\u003c/sub\u003e were estimated when exposed to both kinds of cells. The recommended biosensor offers a larger S\u003csub\u003eId\u003c/sub\u003e of 1.03\u0026times;10\u003csup\u003e12\u003c/sup\u003e, S\u003csub\u003eratio\u003c/sub\u003e of 3.31\u0026times;10\u003csup\u003e9\u003c/sup\u003e and S\u003csub\u003egm\u003c/sub\u003e of 3.46\u0026times;10\u003csup\u003e11\u003c/sup\u003e compared to the healthy cell. An in-depth analysis was also conducted to examine the effect of cavity length and thickness on the sensor's sensitivity. Due to its early detection capabilities, lack of doping fluctuations, ease of manufacture, optimised transduction process, and compatibility with MOS technology, such a biosensor may be a suitable option for diagnosing breast cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding Information:\u003c/h2\u003e \u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS. Dash has designed and simulated all the results. Further, he wrote the manuscript and did all the analysis.\u003c/p\u003e\u003ch2\u003eAcknowledgment:\u003c/h2\u003e \u003cp\u003eThe author acknowledges the support from the Device Simulation Laboratory, Institute of Technical Education and Research, Siksha 'O' Anusandhan Deemed to be University, Bhubaneswar, Odisha, India, for facilitating the Silvaco TCAD simulation software to carry out the research.\u003c/p\u003e\u003ch2\u003eData availability statement:\u003c/h2\u003e \u003cp\u003eAll data that support the findings of this study are included within the article (and any supplementary files).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBreast Cancer Statistics And Resources (1993). [Online]. 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Complementary tunneling transistor for low power application. \u003cem\u003eSolid-State Electronics\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e, 2281\u0026ndash;2286. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.sse.2004.04.006\u003c/span\u003e\u003cspan address=\"10.1016/j.sse.2004.04.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"sensing-and-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssta","sideBox":"Learn more about [Sensing and Imaging](http://link.springer.com/journal/11220)","snPcode":"11220","submissionUrl":"https://submission.nature.com/new-submission/11220/3","title":"Sensing and Imaging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Breast cancer, biosensor, SiGe pocket, sensitivity, malignant cells","lastPublishedDoi":"10.21203/rs.3.rs-8131934/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8131934/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study proposes a source pocket-based charge plasma TFET with a dual source cavity (DSC-SPCPT) sensor for detecting various cancerous breast cells. A compound SiGe source pocket in the charge plasma TFET offers a higher drain current than TFET as a result of its wider band bending and shorter tunneling length. The breast cells get immobile within the etched nanocavity beneath both source metals. The source cavity's dielectric constant changes with exposure to four tumorigenic breast cells (MCF-7, Hs578T, T47D, and MDA-MB-231) and a healthy cell (MCF-10A). The energy band diagram, threshold voltage, drain current, and transconductance are among the analogue metrics analysed when exposed to malignant cells. This study further estimates the biosensor's sensitivity considering parameters such as drain current, current ratio, transconductance, and threshold voltage, when exposed to both kinds of cells. The proposed sensor is significantly more sensitive to T47D malignant cells in terms of peak drain current (1.03\u0026times;10\u003csup\u003e12\u003c/sup\u003e), transconductance (3.46\u0026times;10\u003csup\u003e11\u003c/sup\u003e), and current ratio (3.31\u0026times;10\u003csup\u003e9\u003c/sup\u003e). This magnitude is more than four decades higher than the result of healthy breast cells. The effects of temperature on the sensitivity performance are also thoroughly examined.\u003c/p\u003e","manuscriptTitle":"Design \u0026amp; Analysis of a Highly Sensitive Biosensor for Detecting Breast Malignancy using a Charge Plasma TFET with SiGe Pocket ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 17:06:32","doi":"10.21203/rs.3.rs-8131934/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-23T16:25:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-22T16:03:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T15:37:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-20T10:35:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-17T10:05:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T19:27:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T11:48:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41447516159494553495355782353692190438","date":"2025-12-12T07:26:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216879890769294385755631551708072407340","date":"2025-12-11T05:02:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306654671226747827651379142762746313763","date":"2025-12-11T04:18:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12713025735542032956423473354527962399","date":"2025-12-11T04:09:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65532262936838617492075864052170219183","date":"2025-12-11T03:15:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218211126554753044205078449854928201168","date":"2025-12-11T03:02:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61956398752979710440227846431417968998","date":"2025-12-11T01:56:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-11T00:36:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-27T14:40:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-18T05:33:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Sensing and Imaging","date":"2025-11-17T06:51:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"sensing-and-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssta","sideBox":"Learn more about [Sensing and Imaging](http://link.springer.com/journal/11220)","snPcode":"11220","submissionUrl":"https://submission.nature.com/new-submission/11220/3","title":"Sensing and Imaging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d001a47c-d607-4b26-bc88-5e079cfa5e4b","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2025-12-23T16:38:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 17:06:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8131934","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8131934","identity":"rs-8131934","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}