Quantifying and understanding errors in molecular geometries

Quantifying and understanding errors in molecular geometries | 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 Article Quantifying and understanding errors in molecular geometries Stefan Vuckovic, Kieron Burke This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-47294/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Nov, 2020 Read the published version in The Journal of Physical Chemistry Letters → Version 1 posted You are reading this latest preprint version Abstract Electronic structure calculations are ubiquitous in most branches of chemistry, but all have errors in both energies and equilibrium geometries. Quantifying errors in possibly dozens of bond angles and bond lengths is a Herculean task. A single natural measure of geometric error is introduced, the geometry energy offset (GEO). GEO links many disparate aspects of geometry errors: a new ranking of different methods, quantitative insight into errors in specific geometric parameters, and insight into trends with different methods. GEO can also reduce the cost of high-level geometry optimizations and shows when geometric errors distort the overall error of a method. Results, including some surprises, are given for both covalent and weak interactions. Physical sciences/Chemistry/Theoretical chemistry/Quantum chemistry Physical sciences/Chemistry/Theoretical chemistry/Computational chemistry Physical sciences/Chemistry/Theoretical chemistry/Density functional theory Physical sciences/Chemistry/Theoretical chemistry/Method development molecular geometrics electronic structure bond angles bond lengths Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Full Text Table Additional Declarations There is NO Competing Interest. Supplementary Files sup.pdf sup.pdf Cite Share Download PDF Status: Published Journal Publication published 10 Nov, 2020 Read the published version in The Journal of Physical Chemistry Letters → Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-47294","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":1003712,"identity":"c791a63d-ce58-4b7f-a807-fec9cbbdd459","order_by":0,"name":"Stefan Vuckovic","email":"","orcid":"https://orcid.org/0000-0002-0768-9176","institution":"University of California, Irvine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Vuckovic","suffix":""},{"id":1003713,"identity":"6788700e-8419-43ec-97fe-e5e8a4b75382","order_by":1,"name":"Kieron Burke","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAq0lEQVRIiWNgGAWjYBACCWYwZcPAAGLwkKAljRQtEOowhCJKi2Q787EPH3ecT+xvZ2B88LaNCC3SzGzJM2eeuZ044zADs+FcYrTIMfMYM/O23U7cwMzAJs1LnBb+z0At50Ba2H8TpUWamYcZqOUA2BZmorRINrMZM85sSzaecZixWXLOOSK0SJw//JjhY5udbH//4YMf3pQRoQUJMDaQpn4UjIJRMApGAW4AAFokLKpadPz4AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-6159-0054","institution":"Departments of Chemistry and of Physics, University of California","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Kieron","middleName":"","lastName":"Burke","suffix":""}],"badges":[],"createdAt":"2020-07-21 19:30:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-47294/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-47294/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1021/acs.jpclett.0c03034","type":"published","date":"2020-11-10T19:20:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":1720655,"identity":"c6585c1e-890d-4920-a435-e1142a7e19f3","added_by":"auto","created_at":"2020-07-29 17:40:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":126482,"visible":true,"origin":"","legend":"Why GEO is useful. Left: Exact and approximate GEO rankings for quantum chemical methods on small molecules (top), and GEO of many different methods over medium-sized organic molecules (bottom) with B2PLYP as reference. For the lists of molecules and further details, see Figs. S2-S6, and Tables S1-S3. Center: Egeo for a few methods and a few molecules (top), single and double-bond contributions to Esimple for two popular methods, showing huge difference in their accuracies (bottom). For the list of molecules, see Fig. 3. Right: GEO contours as a function of errors in the bond angle and length for the water molecule (top panel) and weakly bonded Ne2Ar (lower panel), and positions of different approximations.","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1/Figure1.jpg"},{"id":1720656,"identity":"163ee6d7-e107-40f8-baa8-27f1549b04b7","added_by":"auto","created_at":"2020-07-29 17:40:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":101869,"visible":true,"origin":"","legend":"GEO analysis for formaldehyde. Top: (a) GEO rankings of approximations. The plots also show that Egeo is accurately approximated by Eharm geo (Eq. 3) and E\nsimple geo (Eq. 5). (b) E simple geo weights, E simple,i geo /E simple geo (see lower panels for colour legends). When all bonds are stretched by the same factor, GEO becomes E geo (see the text), and the underlying weights are marked by the arrow. (c) GEO-active and GEO-inactive modes (those that have no contribution to the r.h.s. of Eq 4). For the Eharm geo weights in normal modes, analogous to panel (b), see Fig. S28. (d)-(f) Plots showing errors in individual geometric parameters (x-axis), and how these errors translate to E simple geo terms by virtue of Eq. 5 (y-axis). The points marked by the arrows, show GEO when the bond lengths are stretched by 1%.","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1/Figure2.jpg"},{"id":1720657,"identity":"2e9648de-aa99-40ca-916f-06ae17960430","added_by":"auto","created_at":"2020-07-29 17:40:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":30532,"visible":true,"origin":"","legend":"The same plot as in the top panel of Fig. 1b but with geod (see the absolute GEO scale section) on the y-axis. For more plots comparing Egeo and EDgeo, see S7.","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1/Figure3.jpg"},{"id":1720658,"identity":"86151a9e-6ecc-4bbe-b737-c91401ea5b45","added_by":"auto","created_at":"2020-07-29 17:40:03","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":77170,"visible":true,"origin":"","legend":"GEO analysis for the Ne2 binding energies. Top panel: Binding curves of Ne2 with various methods. Lower panel: GEO for different approximations. For more details, see Figs. S35- S38.","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1/Figure4.jpg"},{"id":1720659,"identity":"05e8b239-575d-4ab6-a008-ad7b759daa04","added_by":"auto","created_at":"2020-07-29 17:40:03","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":80942,"visible":true,"origin":"","legend":"The ∆E = EX [EX ] E0 vs. GEO errors for the binding energies of the S66 complexes of MP2/CBS (top panel), PBE0 [D3] (lower panel). The complexes are classified into \"H-bonds\", \"Dispersion\" and \"Others\" as in the original S66 publication.[24]. Coloured dashed lines represent MAEs for dif- ferent S66 categories and gray dash line represents the overall S66 MAEs.\n","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1/Figure5.jpg"},{"id":13518587,"identity":"6891dfd6-8f27-4151-ad52-7fbf01fd69ae","added_by":"auto","created_at":"2021-09-17 00:20:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2350852,"visible":true,"origin":"","legend":"Article File","description":"","filename":"k13.pdf","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1_covered.pdf"},{"id":1720680,"identity":"e4db62fe-5daf-44a4-8fdc-ed3d617e1366","added_by":"auto","created_at":"2020-07-29 17:40:19","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3076773,"visible":true,"origin":"","legend":"Article File","description":"","filename":"k13.pdf","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1_stamped.pdf"},{"id":1720660,"identity":"f58ec010-8c56-422b-8d45-032bfe9506d5","added_by":"auto","created_at":"2020-07-29 17:40:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2967279,"visible":true,"origin":"","legend":"Article File","description":"","filename":"k13.pdf","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1/k13.pdf"},{"id":1720661,"identity":"aab916fe-9a76-48e7-9655-5ac4faa0a64d","added_by":"auto","created_at":"2020-07-29 17:40:05","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22905577,"visible":true,"origin":"","legend":"sup.pdf","description":"","filename":"sup.pdf","url":"https://assets-eu.researchsquare.com/files/rs-47294/v1/sup.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Quantifying and understanding errors in molecular geometries","fulltext":[{"header":"Full Text","content":"\u003cp\u003eThis preprint is available for \u003ca href='/article/rs-47294/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e.\u003c/p\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"molecular geometrics, electronic structure, bond angles, bond lengths","lastPublishedDoi":"10.21203/rs.3.rs-47294/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-47294/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Electronic structure calculations are ubiquitous in most branches of chemistry, but all have errors in both energies and equilibrium geometries. Quantifying errors in possibly dozens of bond angles and bond lengths is a Herculean task. A single natural measure of geometric error is introduced, the geometry energy offset (GEO). GEO links many disparate aspects of geometry errors: a new ranking of different methods, quantitative insight into errors in specific geometric parameters, and insight into trends with different methods. GEO can also reduce the cost of high-level geometry optimizations and shows when geometric errors distort the overall error of a method. Results, including some surprises, are given for both covalent and weak interactions.","manuscriptTitle":"Quantifying and understanding errors in molecular geometries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-07-29 17:39:30","doi":"10.21203/rs.3.rs-47294/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c0ba414c-37e8-44ac-bae6-ae95168dc38f","owner":[],"postedDate":"July 29th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":196816,"name":"Physical sciences/Chemistry/Theoretical chemistry/Quantum chemistry"},{"id":196817,"name":"Physical sciences/Chemistry/Theoretical chemistry/Computational chemistry"},{"id":196818,"name":"Physical sciences/Chemistry/Theoretical chemistry/Density functional theory"},{"id":196819,"name":"Physical sciences/Chemistry/Theoretical chemistry/Method development"}],"tags":[],"updatedAt":"2021-07-22T19:20:11+00:00","versionOfRecord":{"articleIdentity":"rs-47294","link":"https://doi.org/10.1021/acs.jpclett.0c03034","journal":{"identity":"the-journal-of-physical-chemistry-letters","isVorOnly":true,"title":"The Journal of Physical Chemistry Letters"},"publishedOn":"2020-11-10 19:20:11","publishedOnDateReadable":"November 10th, 2020"},"versionCreatedAt":"2020-07-29 17:39:30","video":"","vorDoi":"10.1021/acs.jpclett.0c03034","vorDoiUrl":"https://doi.org/10.1021/acs.jpclett.0c03034","workflowStages":[]},"version":"v1","identity":"rs-47294","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-47294","identity":"rs-47294","version":["v1"]},"buildId":"ehx78VzkSd0WSzXnipQa-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}