Faraday Discussions最新文献

{"title":"Metastable layered lithium-rich niobium and tantalum oxides <i>via</i> nearly instantaneous cation exchange.","authors":"Sarah L Ko, Jordan A Dorrell, Andrew J Morris, Kent J Griffith","doi":"10.1039/d4fd00103f","DOIUrl":"https://doi.org/10.1039/d4fd00103f","url":null,"abstract":"<p><p>Lithium-rich early transition metal oxides are the source of excess removeable lithium that affords high energy density to lithium-rich battery cathodes. They are also candidates for solid electrolytes in all-solid-state batteries. These highly ionic compounds are sparse on phase diagrams of thermodynamically stable oxides, but soft chemical routes offer an alternative to explore new alkali-rich crystal chemistries. In this work, a new layered polymorph of Li₃NbO₄ with coplanar [Nb₄O₁₆]^12- clusters is discovered through ion exchange chemistry. A more detailed study of the ion exchange reaction reveals that it takes place almost instantaneously, changing the crystal volume by more than 22% within seconds. The transformation of coplanar [Nb₄O₁₆]^12- in L-Li₃NbO₄ into the supertetrahedral [Nb₄O₁₆]^12- clusters found in the stable cubic c-Li₃NbO₄ is also explored. Furthermore, this synthetic pathway is extended to access a new layered polymorph of Li₃TaO₄. NMR crystallography with ^6,7Li, ²³Na, and ⁹³Nb NMR, X-ray diffraction, neutron diffraction, and first-principles calculations is applied to A₃MO₄ (A = Li, Na; M = Nb, Ta) to identify local and long-range atomic structure, to monitor the unusually rapid reaction progression, and to track the phase transitions from the metastable layered phases to the known compounds found using high-temperature synthesis. A mechanism is proposed whereby some sodium is retained at short reaction times, which then undergoes proton exchange during water washing, forming a phase with hydrogen bonds bridging the coplanar [Nb₄O₁₆]^12- clusters. This study has implications for lithium-rich transition metal oxides and associated battery materials and for ion exchange chemistry in non-framework structures. The role of techniques that can detect light elements, local structure, and subtle structural changes in soft-chemical synthesis is emphasized.</p>","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142277402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preface.","authors":"George H Booth, Ali Alavi","doi":"10.1039/d4fd90033b","DOIUrl":"https://doi.org/10.1039/d4fd90033b","url":null,"abstract":"","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142277403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to do impactful research in artificial intelligence for chemistry and materials science.","authors":"Alan Aspuru-Guzik, Austin Cheng, Marta Skreta, Cher Tian Ser, Andres Guzman-Cordero, Luca Thiede, Andreas Burger, Sergio Pablo-García, Abdulrahman Aldossary, Shi Xuan Leong, Felix Strieth-Kalthoff","doi":"10.1039/d4fd00153b","DOIUrl":"https://doi.org/10.1039/d4fd00153b","url":null,"abstract":"Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it is still not reaching its full potential or maturity. In this perspective, we first outline the pervasive current applications. Then, we discuss how machine learning researchers view and approach problems in the field. Finally, we provide our considerations for maximizing impact when researching machine learning for chemistry.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NMR Crystallography","authors":"Lyndon Emsley","doi":"10.1039/d4fd00151f","DOIUrl":"https://doi.org/10.1039/d4fd00151f","url":null,"abstract":"Chemical function is directly related to the spatial arrangement of atoms. Consequently, the determination of atomic-level three-dimensional structures has transformed molecular and materials science over the past 60 years. In this context, solid-state NMR has emerged to become the method of choice for atomic-level characterization of complex materials in powder form. In the following we present an overview of current methods for chemical shift driven NMR crystallography, illustrated with applications to complex materials","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142208830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Making the InChI FAIR and sustainable while moving to Inorganics","authors":"Gerd Blanke, Jan Brammer, Djordje Baljozovic, Nauman Khan, Frank Lange, Felix Bänsch, Clare A. Tovee, Ulrich Schatzschneider, Richard M Hartshorn, Sonja Herres-Pawlis","doi":"10.1039/d4fd00145a","DOIUrl":"https://doi.org/10.1039/d4fd00145a","url":null,"abstract":"The InChI (International Chemical Identifier) standard stands as a cornerstone in chemical informatics, facilitating the structure-based identification and exchange of chemical compounds across various platforms and databases. The InChI as a unique canonical line notation has made chemical structures searchable on the internet at a broad scale. The largest repositories working with InChIs contain more than 1 billion structures. Central to the functionality of the InChI is its codebase, which orchestrates a series of intricate steps to generate unique identifiers for chemical compounds. Up to now, these steps have been sparsely documented and the InChI algorithm had to be seen as a black box. For the new v1.07 release, the code has been analyzed and the major steps documented, more than 3000 bugs and security issues, as well as nearly 60 Google OSS-Fuzz issues have been fixed. New test systems have been implemented that allow users to directly test the code developments. The move to GitHub has not only made the development more transparent but will also enable external contributors to join the further development of the InChI code. Motivation for this modernisation was the urgency to treat molecular inorganic compounds by the InChI in a meaningful way. Until now, no classic string representation fulfills this need of molecular inorganic chemistry. The connection of metal bonds is by definition disconnected which makes most inorganic InChIs meaningless at the moment. Herein, we propose new routines to remedy this problem in the representation of molecular inorganic compounds by the InChI.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142208832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Concluding remarks: Dense Ionic Fluids: Because Sometimes, More is More","authors":"Rob Atkin","doi":"10.1039/d4fd00150h","DOIUrl":"https://doi.org/10.1039/d4fd00150h","url":null,"abstract":"It is a formidable challenge, and a distinct privilege, to provide the concluding remarks for this Faraday Discussion on Dense Ionic Fluids (DIFs). What follows is an inherently subjective distillation of the insights that have shaped our understanding of these complex systems over the last few days, with the goal of capture the essence of the Discussion and providing suggestions for future investigations in this rapidly evolving field. DIFs are a fascinating class of electrolyte systems characterized by high ion concentrations in correlated domains. The multiscale nature of DIFs, and the challenges in connecting nanoscale phenomena to bulk properties are discussed in the context of contemporary experimental and computational methods. Next, emerging trends are explored, and then the paper concludes by identifying promising future research directions.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142208839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing electron correlation in solid-state calculations for superconducting states.","authors":"Wilver A Muriel, Trinidad Novoa, Carlos Cárdenas, Julia Contreras-García","doi":"10.1039/d4fd00073k","DOIUrl":"https://doi.org/10.1039/d4fd00073k","url":null,"abstract":"<p><p>Analyzing the electronic localization of superconductors has been recently shown to be relevant for understanding their critical temperature [<i>Nature Communications</i>, <b>12</b>, 5381, (2021)]. However, these relationships have only been shown at the Kohn-Sham density functional theory (DFT) level, where the onset of strong correlation linked to the superconducting state is missing. In this contribution, we approximate the superconducting gap in order to reconstruct the superconducting the one-reduced density matrix (1RDM) from a DFT calculation. This allows us to analyse the electron density and localization in the strong correlation regime. The method is applied to two well-known superconductors. Electron localization features along the electron-phonon coupling directions and hydrogen cluster formations are observed for different solids. However, in both cases we see that the overall localization channels are not affected by the onset of superconductivity, explaining the ability of DFT localization channels to characterize the superconducting ones.</p>","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142102305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulation of Transmembrane Current through Modulation of Biomimetic Lipid Membrane Composition","authors":"Zhiwei Shang, Jing Zhao, Mengyu Yang, Yuling Xiao, Wenjing Chu, Yilin Cai, Xiaoqing Yi, Meihua Lin, Fan Xia","doi":"10.1039/d4fd00149d","DOIUrl":"https://doi.org/10.1039/d4fd00149d","url":null,"abstract":"Ion transport through biological channels is influenced not only by the structural properties of the channels themselves but also by the composition of the phospholipid membrane, which acts as a scaffold for these nanochannels. Drawing inspiration from how lipid membrane composition modulates ion currents, as seen in the activation of the K+ channel in Streptomyces A (KcsA) by anionic lipids, we propose a biomimetic nanochannel system that integrates DNA nanotechnology with two-dimensional graphene oxide (GO) nanosheets. By modifying the length of the multibranched DNA nanowires generated through the hybridization chain reactions (HCR) and varying the concentration of the linker strands that integrate these DNA nanowire structures with the GO membrane, the composition of the membrane can be effectively adjusted, consequently impacting ion transport. This method provides a strategy for developing devices with highly efficient and tunable ion transport, suitable for applications in mass transport, environmental protection, biomimetic channels, and biosensors.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142208841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction rigidities for data-driven chemistry","authors":"Sanggyu Chong, Filippo Bigi, Federico Grasselli, Philip Loche, Matthias Kellner, Michele Ceriotti","doi":"10.1039/d4fd00101j","DOIUrl":"https://doi.org/10.1039/d4fd00101j","url":null,"abstract":"The widespread application of machine learning (ML) to the chemical sciences is making it very important to understand how the ML models learn to correlate chemical structures with their properties, and what can be done to improve the training efficiency whilst guaranteeing interpretability and transferability. In this work, we demonstrate the wide utility of prediction rigidities, a faimily of metrics derived from the loss function, in understanding the robustness of ML model predictions. We show that the prediction rigidities allow the assessment of the model not only at the global level, but also on the local or the component-wise level at which the intermediate (e.g. atomic, body-ordered, or range-separated) predictions are made. We leverage these metrics to understand the learning behavior of different ML models, and to guide efficient dataset construction for model training. We finally implement the formalism for a ML model targeting a coarse-grained system to demonstrate the applicability of the prediction rigidities to an even broader class of atomistic modeling problems.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142208831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CO adsorption on Pt(111) studied by periodic coupled cluster theory.","authors":"Johanna P Carbone, Andreas Irmler, Alejandro Gallo, Tobias Schäfer, William Z Van Benschoten, James J Shepherd, Andreas Grüneis","doi":"10.1039/d4fd00085d","DOIUrl":"10.1039/d4fd00085d","url":null,"abstract":"<p><p>We present an application of periodic coupled-cluster theory to the calculation of CO adsorption energies on the Pt(111) surface for different adsorption sites. The calculations employ a range of recently developed theoretical and computational methods. In particular, we use a recently introduced coupled-cluster ansatz, denoted as CCSD(cT), to compute correlation energies of the metallic Pt surface with and without adsorbed CO molecules. The convergence of Hartree-Fock adsorption energy contributions with respect to randomly shifted <i>k</i>-meshes is discussed. Recently introduced basis set incompleteness error corrections make it possible to achieve well-converged correlation energy contributions to the adsorption energies. We show that CCSD(cT) theory predicts the correct order of adsorption energies for the considered adsorption sites. Furthermore, we find that binding of the CO molecule to the top and fcc site is dominated by Hartree-Fock and correlation energy contributions, respectively.</p>","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11339635/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142015641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}