Faraday Discussions最新文献_第7页

Characterization of Ephedrine HCl and Pseudoephedrine HCl Using Quadrupolar NMR Crystallography Guided Crystal Structure Prediction 利用四极核磁共振晶体学指导晶体结构预测表征盐酸麻黄碱和盐酸伪麻黄碱

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-24 DOI: 10.1039/d4fd00089g

Carl Fleischer, Sean Thomas Holmes, Kirill Levin, Stas L Veinberg, Rob Schurko

{"title":"Characterization of Ephedrine HCl and Pseudoephedrine HCl Using Quadrupolar NMR Crystallography Guided Crystal Structure Prediction","authors":"Carl Fleischer, Sean Thomas Holmes, Kirill Levin, Stas L Veinberg, Rob Schurko","doi":"10.1039/d4fd00089g","DOIUrl":"https://doi.org/10.1039/d4fd00089g","url":null,"abstract":"Quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) is a nascent protocol for predicting, solving, and refining crystal structures. QNMRX-CSP employs a combination of solid-state NMR data from quadrupolar nuclides (i.e., nuclear spin > 1/2), static lattice energies and electric field gradient (EFG) tensors from dispersion-corrected density functional theory (DFT-D2*) calculations, and powder X-ray diffraction (PXRD) data; however, it has so far been applied only to organic HCl salts with small and rigid organic components, using 35Cl EFG tensor data for both structural refinement and validation. Herein, the QNMRX-CSP protocol is extended to ephedrine HCl (Eph) and pseudoephedrine HCl (Pse), which are diastereomeric compounds that feature distinct space groups and organic components that are larger and more flexible. A series of benchmarking calculations are used to generate structural models that can be validated against experimental data, and to explore the impacts of the (i) starting structural models (i.e., geometry-optimized fragments based on either a known crystal structure or an isolated gas-phase molecule) and (ii) selection of unit cell parameters and space groups. Finally, we use QNMRX-CSP to predict the structure of Pse in the dosage form Sudafed using only 35Cl SSNMR data as experimental input. This proof-of-concept work suggests the possibility of employing QNMRX-CSP protocols to solve the structures of organic HCl salts in dosage forms – something which is often beyond the capabilities of conventional, diffraction-based characterization methods.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"19 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501893","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}

引用次数: 0

The essential synergy of MD simulation and NMR in understanding amorphous drug forms MD 模拟和 NMR 在理解无定形药物形态方面的重要协同作用

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-20 DOI: 10.1039/d4fd00097h

Jamie Liam Guest, Esther A. E. Bourne, Martin A. Screen, Mark Richard Wilson, Tran N. Pham, Paul Hodgkinson

引用次数: 0

Electrochemical Kinetic Fingerprinting of Single-Molecule Cooridations in the Confined Nanopores 封闭纳米孔中单分子共沉淀的电化学动力学指纹图谱

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-19 DOI: 10.1039/d4fd00133h

Chaonan Yang, Wei Liu, Haotian Liu, Jichang Zhang, Yi-Tao Long, Yi-Lun Ying

{"title":"Electrochemical Kinetic Fingerprinting of Single-Molecule Cooridations in the Confined Nanopores","authors":"Chaonan Yang, Wei Liu, Haotian Liu, Jichang Zhang, Yi-Tao Long, Yi-Lun Ying","doi":"10.1039/d4fd00133h","DOIUrl":"https://doi.org/10.1039/d4fd00133h","url":null,"abstract":"Metal centers are essential for enzyme catalysis, stabilizing the active site, facilitating electron transfer, and maintaining the structure through coordination with amino acids. In this study, K238H-AeL nanopores with histidine sites were designed for the first time as single-molecule reactors for the measurement of single-molecule coordination reactions. The coordination mechanism of Au(Ⅲ) with histidine and glutamate in nano-confined biological nanopores was explored. Specifically, Au(Ⅲ) interacts with the nitrogen (N) atom in the histidine imidazole ring of the K238C-AeL nanopore and the oxygen (O) atom in glutamate to form a stable K238H-Au-Cl2 complex. The formation mechanism of this complex was further validated through single-molecule nanopore analysis, mass spectrometry, and molecular dynamics simulations. By introducing histidine and glutamic acid into different positions within the nanopore revealed that the formation of the histidine-Au coordination bond in the confined space requires a distance within 2.5 Å between the ligand and the central metal atom. By analyzing the association and dissociation rates of single Au(Ⅲ) ions under the applied voltages, it was found that a confined nanopore increased the bonding rate of Au(Ⅲ)-Histidine coordination reactions by around 105 times compared to the bulk solution, and the optimal voltage for single-molecule coordination., providing valuable insights for designing reaction pathways in electrochemical catalysis. This research revealed a novel mechanism for metal coordination and amino acid residues in protein nanoconfined space, highlighting the dynamic interactions between metal ions and amino acid residues and the importance of the confined effect, providing insights for developing efficient, eco-friendly electrocatalytic nanomaterials.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"213 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141527892","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}

引用次数: 0

Temperature-induced mobility in Octacalcium Phosphate impacts crystal symmetry: water dynamics studied by NMR crystallography 温度诱导的磷酸八钙流动性对晶体对称性的影响：核磁共振晶体学研究的水动力学

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-19 DOI: 10.1039/d4fd00108g

Adam Nelson, Wassilios Papawassiliou, Subhradip Paul, Sabine Hediger, Ivan Hung, Zhehong Gan, Amrit Venkatesh, W. Trent Trent Franks, Mark Edmund E Smith, David Gajan, Gaël De Paëpe, Christian Bonhomme, Danielle Laurencin, Christel Gervais

{"title":"Temperature-induced mobility in Octacalcium Phosphate impacts crystal symmetry: water dynamics studied by NMR crystallography","authors":"Adam Nelson, Wassilios Papawassiliou, Subhradip Paul, Sabine Hediger, Ivan Hung, Zhehong Gan, Amrit Venkatesh, W. Trent Trent Franks, Mark Edmund E Smith, David Gajan, Gaël De Paëpe, Christian Bonhomme, Danielle Laurencin, Christel Gervais","doi":"10.1039/d4fd00108g","DOIUrl":"https://doi.org/10.1039/d4fd00108g","url":null,"abstract":"Octacalcium phosphate (OCP, Ca8(PO4)4(HPO4)2.5H2O) is a notable calcium phosphate due to its biocompatibility, making it a widely studied material for bone substitution. It is known to be a precursor of bone mineral, but its role in biomineralisation remains unclear. While the structure of OCP has been the subject of thorough investigations (including using Rietveld refinements of X-ray diffraction data, and NMR crystallography studies), important questions regarding the symmetry and H-bonding network in the material remain. In this study, it is shown that OCP undergoes a lowering of symmetry below 200 K, evidenced by 1H, 17O, 31P and 43Ca solid state NMR experiments. Using ab-initio molecular dynamics (MD) simulations and Gauge Including Projected Augmented Wave (GIPAW) DFT calculations of NMR parameters, the presence of rapid motion of the water molecules in the crystal cell at room temperature is proved. This information leads to an improved description of the OCP structure at both low and ambient temperatures, and helps explain long-standing issues of symmetry. Remaining challenges related to the understanding of the structure of OCP are then discussed.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"27 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141527983","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}

引用次数: 0

Revealing the Diverse Electrochemistry of Nanoparticles with Scanning Electrochemical Cell Microscopy 利用扫描电化学细胞显微镜揭示纳米粒子的多样化电化学特性

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-17 DOI: 10.1039/d4fd00115j

Lachlan Gaudin, Cameron Luke Bentley

{"title":"Revealing the Diverse Electrochemistry of Nanoparticles with Scanning Electrochemical Cell Microscopy","authors":"Lachlan Gaudin, Cameron Luke Bentley","doi":"10.1039/d4fd00115j","DOIUrl":"https://doi.org/10.1039/d4fd00115j","url":null,"abstract":"The next generation of electroactive materials will depend on advanced nanomaterials, such as nanoparticles (NPs) for improved function and reduced cost. As such, the development of structure-function relationships for these NPs has become a prime focus for researchers from many fields, including materials science, catalysis, energy storage, photovoltaics, environmental/biomedical sensing, etc. The technique of scanning electrochemical cell microscopy (SECCM) has naturally positioned itself as a premier experimental methodology for the investigation of electroactive NPs, due to its unique capability to encapsulate individual, spatially distinct entities, and to apply a potential to (and measure the resulting current of) single-NPs. Over the course of conducting these single-NP investigations, a number of unexpected (i.e. rarely-reported) results have been collected, including fluctuating current responses, and carrying of the NP by the SECCM probe, hypothesised to be due to insufficient NP-surface interaction. Additionally, locations with measurable electrochemical activity have been found to contain no associated NP, and conversely locations with no activity have been found to contain NPs. Through presenting and discussing these findings, this article seeks to highlight the complications associated with single-NP SECCM measurements in order to endorse the broad inclusivity of data.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"38 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501896","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}

引用次数: 0

Non-sticky SiNx nanonets for single protein denaturation analysis 用于单个蛋白质变性分析的非粘性氮化硅纳米网

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-07 DOI: 10.1039/d4fd00117f

Yuanhao Wang, Nan An, Bintong Huang, Yueming Zhai

引用次数: 0

Are we fitting data or noise? Analysing the predictive power of commonly used datasets in drug-, materials-, and molecular-discovery. 我们是在拟合数据还是噪音？分析药物、材料和分子发现中常用数据集的预测能力。

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-04 DOI: 10.1039/d4fd00091a

Daniel Crusius, Flaviu Cipcigan, Philip Biggin

{"title":"Are we fitting data or noise? Analysing the predictive power of commonly used datasets in drug-, materials-, and molecular-discovery.","authors":"Daniel Crusius, Flaviu Cipcigan, Philip Biggin","doi":"10.1039/d4fd00091a","DOIUrl":"https://doi.org/10.1039/d4fd00091a","url":null,"abstract":"Data-driven techniques for establishing quantitative structure property relations are a pillar of modern materials and molecular discovery. Fuelled by the recent progress in deep learning methodology and the abundance of new algorithms, it is tempting to chase benchmarks and incrementally build ever more capable machine learning (ML) models. While model evaluation has made significant progress, the intrinsic limitations arising from the underlying experimental data are often overlooked. In the chemical sciences data collection is costly, thus datasets are small and experimental errors can be significant. These limitations of such datasets affect their predictive power, a fact that is rarely considered in a quantitative way. In this study, we analyse commonly used ML datasets for regression and classification from drug discovery, molecular discovery, and materials discovery. We derived maximum and realistic performance bounds for nine such datasets by introducing noise based on estimated or actual experimental errors. We then compared the estimated performance bounds to the reported performance of leading ML models in the literature. Out of the nine datasets and corresponding ML models considered, four were identified to have reached or surpassed dataset performance limitations and thus, they may potentially be fitting noise. More generally, we systematically examine how data range, the magnitude of experimental error, and the number of data points influence dataset performance bounds. Alongside this paper, we release the Python package NoiseEstimator and provide a web- based application for computing realistic performance bounds. This study and the resulting tools will help practitioners in the field understand the limitations of datasets and set realistic expectations for ML model performance. This work stands as a reference point, offering analysis and tools to guide development of future ML models in the chemical sciences.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"25 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141256072","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}

引用次数: 0

A Combined 7Li NMR, Density Functional Theory and Operando Synchrotron X-Ray Powder Diffraction to Investigate a Structural Evolution of Cathode Material LiFeV2O7 结合 7Li NMR、密度泛函理论和 Operando 同步 X 射线粉末衍射研究阴极材料 LiFeV2O7 的结构演化

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-03 DOI: 10.1039/d4fd00077c

Taiana L.E. Pereira, Jon Serrano-Sevillano, Beatriz Diaz Moreno, Joel Reid, Dany Carlier, Gillian Goward

{"title":"A Combined 7Li NMR, Density Functional Theory and Operando Synchrotron X-Ray Powder Diffraction to Investigate a Structural Evolution of Cathode Material LiFeV2O7","authors":"Taiana L.E. Pereira, Jon Serrano-Sevillano, Beatriz Diaz Moreno, Joel Reid, Dany Carlier, Gillian Goward","doi":"10.1039/d4fd00077c","DOIUrl":"https://doi.org/10.1039/d4fd00077c","url":null,"abstract":"In our recent study, we demonstrated using 7Li solid-state Nuclear Magnetic Resonance (ssNMR) and single-crystal X-ray diffraction, that the cathode LiFeV2O7 possesses a defect associated with the positioning of vanadium atoms. We proposed that this defect could be the source of extra signals detected in the 7Li NMR spectra. In this context, we now apply density functional theory (DFT) calculations to assign the experimental signals observed in 7Li NMR spectra of the pristine sample. The calculation results are in strong agreement with the experimental observations. DFT calculations are a useful tool to interpret the observed paramagnetic shifts and understand how the presence of disorder affects the spectra behavior through the spin-density transfer processes. Furthermore, we conducted a detailed study of the lithiated phase combining operando synchrotron powder X-ray diffraction (SPXRD) and DFT calculations. A noticeable volume expansion is observed through the first discharge cycle which likely contributes to the enhanced lithium dynamics in the bulk material, as supported by previously published ssNMR data. DFT calculations are used to model the lithiated phase and demonstrate that both iron and vanadium participate in the redox process. The unusual electronic structure of the V4+ -exhibits a single electron on the 3dxy orbital perpendicular to the V-O-Li bond being a source of a negative Fermi contact shift observed in the 7Li NMR of the lithiated phase.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"98 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141256069","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}

引用次数: 0

Predictive crystallography at scale: mapping, validating, and learning from 1,000 crystal energy landscapes 规模化预测晶体学：绘制、验证和学习 1,000 个晶体能量图谱

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-03 DOI: 10.1039/d4fd00105b

Christopher Taylor, Patrick Butler, Graeme Matthew Day

{"title":"Predictive crystallography at scale: mapping, validating, and learning from 1,000 crystal energy landscapes","authors":"Christopher Taylor, Patrick Butler, Graeme Matthew Day","doi":"10.1039/d4fd00105b","DOIUrl":"https://doi.org/10.1039/d4fd00105b","url":null,"abstract":"Computational crystal structure prediction (CSP) is an increasingly powerful technique in materials discovery, due to its ability to reveal trends and permit insight across the possibility space of crystal structures of a candidate molecule, beyond simply the observed structure(s). In this work, we demonstrate the reliability and scalability of CSP methods for small, rigid organic molecules by performing in-depth CSP investigations for over 1000 such compounds, the largest survey of its kind to-date. We show that this highly-efficient force-field-based CSP approach is superbly predictive, locating 99.4% of observed experimental structures, and ranking a large majority of these (74%) as among the most stable possible structures (to within uncertainty due to thermal effects). We present two examples of insights such large predicted datasets can permit, examining the space group preferences of organic molecular crystals and rationalising empirical rules concerning the spontaneous resolution of chiral molecules. Finally, we exploit this large and diverse dataset for developing transferable machine-learned energy potentials for the organic solid state, training a neural network lattice energy correction to force field energies that offers substantial improvements to the already impressive energy rankings, and a MACE equivariant message-passing neural network for crystal structure reoptimisation. We conclude that the excellent performance and reliability of the CSP workflow enables the creation of very large datasets of broad utility and explanatory power in materials design.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"36 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141256188","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}

引用次数: 0

A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR 通过 23Na/27Al 固态 NMR 对沸石中的铝分布进行动态建模的机器学习方法

IF 3.4 3区化学

Faraday Discussions Pub Date : 2024-06-03 DOI: 10.1039/d4fd00100a

Lei Chen, Carlos Bornes, Oscar Bengtsson, Andreas Erlebach, Ben Slater, Lukáš Grajciar, Christopher J. Heard

{"title":"A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR","authors":"Lei Chen, Carlos Bornes, Oscar Bengtsson, Andreas Erlebach, Ben Slater, Lukáš Grajciar, Christopher J. Heard","doi":"10.1039/d4fd00100a","DOIUrl":"https://doi.org/10.1039/d4fd00100a","url":null,"abstract":"One of the main limitations in supporting experimental characterization of Al siting/pairing via modelling is the high computational cost of ab initio calculations. For this reason, most works rely on static or very short dynamical simulations, considering limited Al pairing/siting combinations. As a result, comparison with experiment suffers from a large degree of uncertainty. To alleviate this limitation we have developed neural network potentials (NNPs) which can dynamically sample across broad configurational and chemical spaces of sodium-form aluminosilicate zeolites, preserving the level of accuracy of the ab initio (dispersion-corrected metaGGA) training set. By exploring a wide range of Al/Na arrangements and a combination of experimentally relevant Si/Al ratios, we found that the 23Na NMR spectra of dehydrated high-silica CHA zeolite offer an opportunity to assess the distribution and pairing of Al atoms. We observed that the 23Na chemical shift is sensitive not only to the location of sodium in 6- and 8MRs, but also to the Al-Sin-Al sequence length. Furthermore, neglect of thermal and dynamical contributions were found to lead to errors of several ppm, and have a profound influence on the shape of the spectra and the dipolar coupling constants, thus necessitating the long-term dynamical simulations made feasible by NNPs. Finally, we obtained a predictive regression model for 23Na chemical shift in CHA (Si/Al = 35, 17, 11) that circumvents the need for expensive NMR density functional calculations and can be easily extended to other zeolite frameworks. By combining NNPs and regression methods, we can expedite the simulations of NMR properties and capture the effect dynamics on the spectra, which is often overlooked in computational studies despite its clear manifestation in experimental setups.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"52 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141256526","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}

引用次数: 0