Understanding the interactions between lipid membranes and peptides is crucial for controlling bacterial and viral infections, and developing effective drugs. In this study, we proposed the use of electrochemiluminescence (ECL) microscopy in a solution of [Ru(bpy)3]2+ and tri-n-propylamine to monitor alterations in the lipid membranes due to peptide action. A planar artificial lipid membrane served as a model platform, and its surface was observed using ECL microscopy during exposure to melittin, a representative membrane lytic peptide. Upon exposure to melittin, the light-emitting process of the [Ru(bpy)3]2+/tri-n-propylamine system through the lipid membrane exhibited complex changes, suggesting that stepwise peptide actions can be monitored through the system. Furthermore, wide-field imaging with ECL microscopy provided an effective means of elucidating the membrane surface at the submicron level and revealing heterogeneous changes upon exposure to melittin. This complemented the spatiotemporal information that could not be obtained using conventional electrochemical measurements
{"title":"Electrochemiluminescence microscopy for the investigation of peptides interactions within planar lipid membranes","authors":"Kaoru Hiramoto, Kosuke Ino, Ibuki Takahashi, Ayumi Hirano-Iwata, Hitoshi Shiku","doi":"10.1039/d4fd00137k","DOIUrl":"https://doi.org/10.1039/d4fd00137k","url":null,"abstract":"Understanding the interactions between lipid membranes and peptides is crucial for controlling bacterial and viral infections, and developing effective drugs. In this study, we proposed the use of electrochemiluminescence (ECL) microscopy in a solution of [Ru(bpy)<small><sub>3</sub></small>]<small><sup>2+</sup></small> and tri-n-propylamine to monitor alterations in the lipid membranes due to peptide action. A planar artificial lipid membrane served as a model platform, and its surface was observed using ECL microscopy during exposure to melittin, a representative membrane lytic peptide. Upon exposure to melittin, the light-emitting process of the [Ru(bpy)<small><sub>3</sub></small>]<small><sup>2+</sup></small>/tri-n-propylamine system through the lipid membrane exhibited complex changes, suggesting that stepwise peptide actions can be monitored through the system. Furthermore, wide-field imaging with ECL microscopy provided an effective means of elucidating the membrane surface at the submicron level and revealing heterogeneous changes upon exposure to melittin. This complemented the spatiotemporal information that could not be obtained using conventional electrochemical measurements","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"56 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141864346","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}
We present here a glutamate oxidase (GluOx)-modified platinum (Pt) nanoelectrode with a planar geometry for glutamate detection. The Pt nanoelectrode was characterized using electrochemistry and scanning electron microscopy (SEM). The radius of the Pt nanoelectrode measured using SEM is ~210 nm. GluOx-modified Pt nanoelectrodes were generated by dip coating GluOx on the Pt nanoelectrode in a solution of 0.9% (wt%) bovine serum albumin (BSA), 0.126% (wt%) glutaraldehyde, and 100 U/mL GluOx. An increase in current was observed at +0.7 V vs. Ag/AgCl/1M KCl with adding increasing concentrations of glutamate. A two-sample t-test results showed that there is a significant difference for current at +0.7 V between the blank and the added lowest glutamate concentration, as well as between adjacent glutamate concentrations, confirming that the increase in current is related to the increased glutamate concentration. The experimental current-concentration curve of glutamate detection fitted well to the theoretical Michaelis-Menten curve. At the low concentration range (50 μM to 200 μM), a linear relationship between the current and glutamate concentration was observed. The Michaelis-Menten constants of Imax and Km were calculated to be 1.093 pA and 0.227 mM, respectively. Biosensor efficiency (the ratio of glutamate sensitivity to H2O2 sensitivity) is calculated to be 57.9%. Enzact (Imax /H2O2 sensitivity, an indicator of the amount of enzyme loaded on the electrode) of the GluOx-modified Pt nanoelectrode is 0.243 mM. We further compared the sensitivity of a GluOx-modified Pt nanoelectrode with a GluOx-modified carbon fiber microelectrode (7-μm diameter and a sensing length of ~350 μm). Glutamate detection on the GluOx-modified carbon fiber microelectrode fitted well to a Michaelis-Menten like response. Based on the fitting, the GluOx-modified carbon fiber microelectrode exhibited an Imax of 0.689 nA and a Km of 301.2 μM towards glutamate detection. The best linear range of glutamate detection on the GluOx-modified carbon fiber microelectrode is from 50 μM to 150 μM Glutamate. GluOx-modified carbon fiber microelectrode exhibited a higher potential requirement for glutamate detection comparing to the GluOx-modified Pt nanoelectrode.
{"title":"Enzyme-modified Pt nanoelectrodes for glutamate detection","authors":"Peibo Xu, Henry David Jetmore, Ran Chen, Mei Shen","doi":"10.1039/d4fd00138a","DOIUrl":"https://doi.org/10.1039/d4fd00138a","url":null,"abstract":"We present here a glutamate oxidase (GluOx)-modified platinum (Pt) nanoelectrode with a planar geometry for glutamate detection. The Pt nanoelectrode was characterized using electrochemistry and scanning electron microscopy (SEM). The radius of the Pt nanoelectrode measured using SEM is ~210 nm. GluOx-modified Pt nanoelectrodes were generated by dip coating GluOx on the Pt nanoelectrode in a solution of 0.9% (wt%) bovine serum albumin (BSA), 0.126% (wt%) glutaraldehyde, and 100 U/mL GluOx. An increase in current was observed at +0.7 V vs. Ag/AgCl/1M KCl with adding increasing concentrations of glutamate. A two-sample t-test results showed that there is a significant difference for current at +0.7 V between the blank and the added lowest glutamate concentration, as well as between adjacent glutamate concentrations, confirming that the increase in current is related to the increased glutamate concentration. The experimental current-concentration curve of glutamate detection fitted well to the theoretical Michaelis-Menten curve. At the low concentration range (50 μM to 200 μM), a linear relationship between the current and glutamate concentration was observed. The Michaelis-Menten constants of Imax and Km were calculated to be 1.093 pA and 0.227 mM, respectively. Biosensor efficiency (the ratio of glutamate sensitivity to H2O2 sensitivity) is calculated to be 57.9%. Enzact (Imax /H2O2 sensitivity, an indicator of the amount of enzyme loaded on the electrode) of the GluOx-modified Pt nanoelectrode is 0.243 mM. We further compared the sensitivity of a GluOx-modified Pt nanoelectrode with a GluOx-modified carbon fiber microelectrode (7-μm diameter and a sensing length of ~350 μm). Glutamate detection on the GluOx-modified carbon fiber microelectrode fitted well to a Michaelis-Menten like response. Based on the fitting, the GluOx-modified carbon fiber microelectrode exhibited an Imax of 0.689 nA and a Km of 301.2 μM towards glutamate detection. The best linear range of glutamate detection on the GluOx-modified carbon fiber microelectrode is from 50 μM to 150 μM Glutamate. GluOx-modified carbon fiber microelectrode exhibited a higher potential requirement for glutamate detection comparing to the GluOx-modified Pt nanoelectrode.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"127 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141864348","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}
Austin Mroz, Piotr N Toka, Antonio Del Rio Chanona, Kim E. Jelfs
Historically, the chemical discovery process has predominantly been a matter of trial-and-improvement, where small modifications are made to a chemical system, guided by chemical knowledge, with the aim of optimising towards a target property or combination of properties. While a trial-and-improvement approach is frequently successful, especially when assisted by the help of serendipity, the approach is incredibly time- and resource-intensive. Complicating this further, the available chemical space that could, in theory, be explored is remarkably vast. As we are faced with near infinite possibilities and limited resources, we require improved search methods to effectively move towards desired optima, e.g. chemical systems exhibiting a target property, or several desired properties. Bayesian optimisation (BO) has recently gained significant traction in chemistry, where within the BO framework, prior knowledge is used to inform and guide the search process to optimise towards desired chemical targets, e.g. optimal reaction conditions to maximise yield, or optimal catalyst exhibiting improved catalytic activity. While powerful, implementing BO algorithms in practice is largely limited to interfacing via various APIs – requiring advanced coding experience and bespoke scripts for each optimisation task. Further, it is challenging to seamlessly link these with electronic lab notebooks via a graphical user interface (GUI). Ultimately, this limits the accessibility of BO algorithms. Here, we present Web-BO, a GUI to support BO for chemical optimisation tasks. We demonstrate its performance using an open source dataset and associated emulator, and link the platform with an existing electronic lab notebook, datalab. By providing a GUI-based BO service, we hope to improve the accessibility of data-driven optimisation tools in chemistry; https://suprashare.rcs.ic.ac.uk/web-bo/.
从历史上看，化学发现过程主要是一个试验和改进的过程，即在化学知识的指导下，对化学体系进行微小的修改，目的是优化目标特性或特性组合。虽然试验和改进方法经常取得成功，尤其是在偶然性的帮助下，但这种方法需要耗费大量的时间和资源。更复杂的是，理论上可以探索的可用化学空间非常广阔。由于我们面临着近乎无限的可能性和有限的资源，我们需要改进搜索方法，以有效地实现理想的最优结果，例如，化学体系表现出一种或几种目标特性。在贝叶斯优化（BO）框架内，先验知识被用来为搜索过程提供信息和指导，以优化实现所需的化学目标，例如使产量最大化的最佳反应条件，或表现出更高催化活性的最佳催化剂。虽然 BO 算法功能强大，但在实际应用中主要局限于通过各种应用程序接口（API）进行连接，这就需要高级编码经验和为每个优化任务定制脚本。此外，通过图形用户界面（GUI）将这些算法与电子实验笔记本无缝连接起来也很有难度。最终，这限制了 BO 算法的可访问性。在此，我们提出了 Web-BO，一种支持化学优化任务中 BO 的图形用户界面。我们使用一个开源数据集和相关模拟器演示了它的性能，并将该平台与现有的电子实验笔记本 datalab 相连接。我们希望通过提供基于图形用户界面的 BO 服务，提高化学领域数据驱动优化工具的可访问性；https://suprashare.rcs.ic.ac.uk/web-bo/。
{"title":"Web-BO: Towards increased accessibility of Bayesian optimisation (BO) for chemistry","authors":"Austin Mroz, Piotr N Toka, Antonio Del Rio Chanona, Kim E. Jelfs","doi":"10.1039/d4fd00109e","DOIUrl":"https://doi.org/10.1039/d4fd00109e","url":null,"abstract":"Historically, the chemical discovery process has predominantly been a matter of trial-and-improvement, where small modifications are made to a chemical system, guided by chemical knowledge, with the aim of optimising towards a target property or combination of properties. While a trial-and-improvement approach is frequently successful, especially when assisted by the help of serendipity, the approach is incredibly time- and resource-intensive. Complicating this further, the available chemical space that could, in theory, be explored is remarkably vast. As we are faced with near infinite possibilities and limited resources, we require improved search methods to effectively move towards desired optima, e.g. chemical systems exhibiting a target property, or several desired properties. Bayesian optimisation (BO) has recently gained significant traction in chemistry, where within the BO framework, prior knowledge is used to inform and guide the search process to optimise towards desired chemical targets, e.g. optimal reaction conditions to maximise yield, or optimal catalyst exhibiting improved catalytic activity. While powerful, implementing BO algorithms in practice is largely limited to interfacing via various APIs – requiring advanced coding experience and bespoke scripts for each optimisation task. Further, it is challenging to seamlessly link these with electronic lab notebooks via a graphical user interface (GUI). Ultimately, this limits the accessibility of BO algorithms. Here, we present Web-BO, a GUI to support BO for chemical optimisation tasks. We demonstrate its performance using an open source dataset and associated emulator, and link the platform with an existing electronic lab notebook, datalab. By providing a GUI-based BO service, we hope to improve the accessibility of data-driven optimisation tools in chemistry; https://suprashare.rcs.ic.ac.uk/web-bo/.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"86 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141864347","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}
Fiona Moore, Ilka Schmueser, Jonathan G Terry, Andrew R Mount
Our previous work has established that micron resolution photolithography can be employed to make microsquare nanoband edge electrode (MNEE) arrays. The MNEE configuration enables systematic control of the parameters (electrode number, cavity array spacing, and nanoelectrode dimensions and placement) which control geometry, conferring consistent high-fidelity electrode response across the array (e.g. high signal, high signal-to-noise, low limits of detection and fast, steady-state, reproducible and quantitative response) and allowing the tuning of individual and combined electrode interactions. Building on this, in this paper we now produce and characterise a Micropore Nanoband Electrode (MNE) Array designed for flow-through detection, where an MNEE edge electrode configuration is used to form a nanotube electrode embedded in the wall of each micropore, formed as an array of pores of controlled pore size and placement through an insulating membrane of sub-micrometer thickness. The success of this approach is established by the close correspondence between experiment and simulation and the enhanced and quantitative detection of redox species flowing through the micropores over the very wide range of flow rates relevant e.g. to (bio)sensing and chromatography. Quantitative electrochemical reaction with low conversion, suitable for analysis, is demonstrated at high flow, whilst quantitative electrochemical reaction with high conversion, suitable for electrochemical product generation, is enabled at lower flow. The fundamental array response is analysed in terms of established flow theories, demonstrating the additive contributions of within pore enhanced diffusional (nanoband edge) and advective (Levich-type) currents, the control of the degree of diffusional overlap between pores through pore spacing and flow rate, the control by design across length scales ranging from nanometer through micrometer to a centimetre array and the ready determination of physicochemical parameters, enabling discussion of the potential of this breakthrough technology to addresses unmet needs in generation and analysis.
{"title":"A Micropore Nanoband Electrode Array for Enhanced Electrochemical Generation/Analysis in Flow Systems","authors":"Fiona Moore, Ilka Schmueser, Jonathan G Terry, Andrew R Mount","doi":"10.1039/d4fd00125g","DOIUrl":"https://doi.org/10.1039/d4fd00125g","url":null,"abstract":"Our previous work has established that micron resolution photolithography can be employed to make microsquare nanoband edge electrode (MNEE) arrays. The MNEE configuration enables systematic control of the parameters (electrode number, cavity array spacing, and nanoelectrode dimensions and placement) which control geometry, conferring consistent high-fidelity electrode response across the array (e.g. high signal, high signal-to-noise, low limits of detection and fast, steady-state, reproducible and quantitative response) and allowing the tuning of individual and combined electrode interactions. Building on this, in this paper we now produce and characterise a Micropore Nanoband Electrode (MNE) Array designed for flow-through detection, where an MNEE edge electrode configuration is used to form a nanotube electrode embedded in the wall of each micropore, formed as an array of pores of controlled pore size and placement through an insulating membrane of sub-micrometer thickness. The success of this approach is established by the close correspondence between experiment and simulation and the enhanced and quantitative detection of redox species flowing through the micropores over the very wide range of flow rates relevant e.g. to (bio)sensing and chromatography. Quantitative electrochemical reaction with low conversion, suitable for analysis, is demonstrated at high flow, whilst quantitative electrochemical reaction with high conversion, suitable for electrochemical product generation, is enabled at lower flow. The fundamental array response is analysed in terms of established flow theories, demonstrating the additive contributions of within pore enhanced diffusional (nanoband edge) and advective (Levich-type) currents, the control of the degree of diffusional overlap between pores through pore spacing and flow rate, the control by design across length scales ranging from nanometer through micrometer to a centimetre array and the ready determination of physicochemical parameters, enabling discussion of the potential of this breakthrough technology to addresses unmet needs in generation and analysis.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"55 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774438","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}
Anisotropy in crystals plays a pivotal role in many technological applications. For example, anisotropic electronic and thermal transport are thought to be beneficial for thermoelectric applications, while anisotropic mechanical properties are of interest for emerging metamaterials, and anisotropic dielectric materials have been suggested as a novel platform for dark matter detection. Understanding and tailoring anisotropy in crystals is therefore essential for the design of next-generation functional materials. To date, however, most data-driven approaches have focused on the prediction of scalar crystal properties, such as the spherically averaged dielectric tensor or the bulk and shear elastic moduli. Here, we adopt the latest approaches in equivariant graph neural networks to develop a model that can predict the full dielectric tensor of crystals. Our model, trained on the Materials Project dataset of c.a.~6,700 dielectric tensors, achieves state-of-the-art accuracy in scalar dielectric prediction in addition to capturing the directional response. We showcase the performance of the model by discovering crystals with almost isotropic connectivity but highly anisotropic dielectric tensors, thereby broadening our knowledge of the structure-property relationships in dielectric crystals.
{"title":"Discovery of highly anisotropic dielectric crystals with equivariant graph neural networks","authors":"Yuchen Lou, Alex M Ganose","doi":"10.1039/d4fd00096j","DOIUrl":"https://doi.org/10.1039/d4fd00096j","url":null,"abstract":"Anisotropy in crystals plays a pivotal role in many technological applications. For example, anisotropic electronic and thermal transport are thought to be beneficial for thermoelectric applications, while anisotropic mechanical properties are of interest for emerging metamaterials, and anisotropic dielectric materials have been suggested as a novel platform for dark matter detection. Understanding and tailoring anisotropy in crystals is therefore essential for the design of next-generation functional materials. To date, however, most data-driven approaches have focused on the prediction of scalar crystal properties, such as the spherically averaged dielectric tensor or the bulk and shear elastic moduli. Here, we adopt the latest approaches in equivariant graph neural networks to develop a model that can predict the full dielectric tensor of crystals. Our model, trained on the Materials Project dataset of c.a.~6,700 dielectric tensors, achieves state-of-the-art accuracy in scalar dielectric prediction in addition to capturing the directional response. We showcase the performance of the model by discovering crystals with almost isotropic connectivity but highly anisotropic dielectric tensors, thereby broadening our knowledge of the structure-property relationships in dielectric crystals.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"21 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774441","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}
Here, we report for the first time that ion current oscillation (ICO) with periodic amplitude and frequency can autonomously occur at polyimidazole brush (PvimB) modified pipettes in an asymmetric solution with pH gradient (e.g. pH 6.0/pH 8.0). Experimental results demonstrated that under a strong bias voltage, the proton responsible PvimB modified pipettes exhibited significant current switching behavior under negative bias voltages, which contributed to periodic oscillating ion current under constant biases. Based on this dynamic, the frequency and amplitude of the ICO phenomenon were regulated by adjusting the pH gradient in the asymmetric solution. ICO under different bias voltages were further explored to show the voltage-dependent nature of this phenomenon. This observation of ICO phenomena offers a new strategy that designing iontronic devices with dynamic conductivity changes induced by surface chemical interactions in spatial confinements.
{"title":"Ion Current Oscillation with Polyelectrolyte Modified Micropipettes","authors":"Tianyi Xiong, Wenjie Ma, Ping Yu","doi":"10.1039/d4fd00135d","DOIUrl":"https://doi.org/10.1039/d4fd00135d","url":null,"abstract":"Here, we report for the first time that ion current oscillation (ICO) with periodic amplitude and frequency can autonomously occur at polyimidazole brush (PvimB) modified pipettes in an asymmetric solution with pH gradient (e.g. pH 6.0/pH 8.0). Experimental results demonstrated that under a strong bias voltage, the proton responsible PvimB modified pipettes exhibited significant current switching behavior under negative bias voltages, which contributed to periodic oscillating ion current under constant biases. Based on this dynamic, the frequency and amplitude of the ICO phenomenon were regulated by adjusting the pH gradient in the asymmetric solution. ICO under different bias voltages were further explored to show the voltage-dependent nature of this phenomenon. This observation of ICO phenomena offers a new strategy that designing iontronic devices with dynamic conductivity changes induced by surface chemical interactions in spatial confinements.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"72 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774440","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}
We benchmark the rSCAN and r2SCAN exchange-correlation functionals by comparing the Nuclear Magnetic Resonance magnetic shieldings predicted by Density Functional Theory to experimentally observed chemical shifts of halide and oxide inorganic compounds. Significant improvement in accuracy is achieved compared to the Generalised Gradient Approximation at a marginally higher computational cost. When using rSCAN or r2SCAN, the correlation coefficient between computationally predicted and experimental values approaches the theoretically expected value of -1 while reducing the deviation, allowing more accurate and reliable spectrum assignments of complex compounds in experimental investigations.
{"title":"Accurate predictions of Chemical Shifts with the rSCAN and r2SCAN mGGA exchange-correlation functionals","authors":"Jonathan Robert Yates, Albert P. Bartók","doi":"10.1039/d4fd00142g","DOIUrl":"https://doi.org/10.1039/d4fd00142g","url":null,"abstract":"We benchmark the rSCAN and r2SCAN exchange-correlation functionals by comparing the Nuclear Magnetic Resonance magnetic shieldings predicted by Density Functional Theory to experimentally observed chemical shifts of halide and oxide inorganic compounds. Significant improvement in accuracy is achieved compared to the Generalised Gradient Approximation at a marginally higher computational cost. When using rSCAN or r2SCAN, the correlation coefficient between computationally predicted and experimental values approaches the theoretically expected value of -1 while reducing the deviation, allowing more accurate and reliable spectrum assignments of complex compounds in experimental investigations.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"116 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785205","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}
A nearly universal component of NMR crystallography is the ranking of candidate structures based on how well their first-principles predicted NMR parameters align with the results of solid-state NMR experiments. Here, a novel approach for assigning probabilities to candidate models is proposed that quantifies the likelihood that each model is the correct experimental structure. This method employs hierarchical Bayesian inference and leverages explicit prior probabilities derived from a uniform distribution of potential candidate structures with respect to chi-squared values. The resulting uniform chi-squared (UC) model provides a more cautious estimate of candidate probabilities compared to previous approaches, assigning decreased likelihood to the best-fit structure and increased likelihood to alternate candidates. Although developed here within the context of NMR crystallography, the UC Model represents a general method for assigning likelihoods based on chi-squared goodness-of-fit assessments.
{"title":"Uniform Chi-Squared Model Probabilities in NMR Crystallography","authors":"Leonard J Mueller","doi":"10.1039/d4fd00114a","DOIUrl":"https://doi.org/10.1039/d4fd00114a","url":null,"abstract":"A nearly universal component of NMR crystallography is the ranking of candidate structures based on how well their first-principles predicted NMR parameters align with the results of solid-state NMR experiments. Here, a novel approach for assigning probabilities to candidate models is proposed that quantifies the likelihood that each model is the correct experimental structure. This method employs hierarchical Bayesian inference and leverages explicit prior probabilities derived from a uniform distribution of potential candidate structures with respect to chi-squared values. The resulting uniform chi-squared (UC) model provides a more cautious estimate of candidate probabilities compared to previous approaches, assigning decreased likelihood to the best-fit structure and increased likelihood to alternate candidates. Although developed here within the context of NMR crystallography, the UC Model represents a general method for assigning likelihoods based on chi-squared goodness-of-fit assessments.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"94 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774442","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}
Eugene Gyasi Agyemang, Samuel Confederat, Gayathri Mohanan, Mahnaz Azimzadeh Sani, Chalmers Chau, Dylan Charnock, Christoph Walti, Kristina Tschulik, Martin Edwards, Paolo Actis
Nanopores are emerging as a powerful tool for the analysis and characterization of nanoparticles at the single entity level. Here, we report that a polymer electrolyte nanopore system enables the enhanced detection of nanoparticle at low ionic strength when a PEG-based polymer electrolyte is present inside the nanopore. We developed a numerical model that recapitulates the electrical response of the nanopore system and the model revealed that the electrical response of the glass nanopore is sensitive to the position of the polymer electrolyte interface. As proof of concept, we demonstrated the multimodal analysis of a nanoparticle sample by coupling the polymer electrolyte nanopore sensor with nanoimpact electrochemistry. This combination of techniques could deliver the multiparametric analysis of nanoparticle systems complementing electrochemical reactivity data provided by nanoimpact electrochemistry with information on size, shape and surface charge provided by nanopore measurements.
{"title":"Multimodal nanoparticle analysis enabled by a polymer electrolyte nanopore combined with nanoimpact electrochemistry","authors":"Eugene Gyasi Agyemang, Samuel Confederat, Gayathri Mohanan, Mahnaz Azimzadeh Sani, Chalmers Chau, Dylan Charnock, Christoph Walti, Kristina Tschulik, Martin Edwards, Paolo Actis","doi":"10.1039/d4fd00143e","DOIUrl":"https://doi.org/10.1039/d4fd00143e","url":null,"abstract":"Nanopores are emerging as a powerful tool for the analysis and characterization of nanoparticles at the single entity level. Here, we report that a polymer electrolyte nanopore system enables the enhanced detection of nanoparticle at low ionic strength when a PEG-based polymer electrolyte is present inside the nanopore. We developed a numerical model that recapitulates the electrical response of the nanopore system and the model revealed that the electrical response of the glass nanopore is sensitive to the position of the polymer electrolyte interface. As proof of concept, we demonstrated the multimodal analysis of a nanoparticle sample by coupling the polymer electrolyte nanopore sensor with nanoimpact electrochemistry. This combination of techniques could deliver the multiparametric analysis of nanoparticle systems complementing electrochemical reactivity data provided by nanoimpact electrochemistry with information on size, shape and surface charge provided by nanopore measurements.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"14 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737506","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}
Active Thermochemical Tables (ATcT) were successfully used to resolve the existing inconsistencies related to the thermochemistry of glycine, based on statistically analyzing and solving a thermochemical network that includes > 3350 chemical species interconnected by nearly 35,000 thermochemically-relevant determinations from experiment and high-level theory. The current ATcT results for the 298.15 K enthalpies of formation are -394.70 ± 0.55 kJ mol-1 for gas phase glycine, -528.37 ± 0.20 kJ mol-1 for solid α-glycine, -528.05± 0.22 kJ mol-1 for β-glycine, -528.64 ± 0.23 kJ mol-1 for γ-glycine, -514.22 ± 0.20 kJ mol-1 for aqueous undissociated glycine, and -470.09 ± 0.20 kJ mol-1 for fully dissociated aqueous glycine at infinite dilution. In addition, a new set of thermophysical properties of gas phase glycine was obtained from a fully corrected nonrigid rotor anharmonic oscillator (NRRAO) partition function, which includes all conformers. Corresponding sets of thermophysical properties of α-, β-, and γ-glycine are also presented.
{"title":"Accurate and Reliable Thermochemistry by Data Analysis of Complex Thermochemical Networks using Active Thermochemical Tables: The Case of Glycine Thermochemistry","authors":"Branko Ruscic, David H Bross","doi":"10.1039/d4fd00110a","DOIUrl":"https://doi.org/10.1039/d4fd00110a","url":null,"abstract":"Active Thermochemical Tables (ATcT) were successfully used to resolve the existing inconsistencies related to the thermochemistry of glycine, based on statistically analyzing and solving a thermochemical network that includes > 3350 chemical species interconnected by nearly 35,000 thermochemically-relevant determinations from experiment and high-level theory. The current ATcT results for the 298.15 K enthalpies of formation are -394.70 ± 0.55 kJ mol<small><sup>-1</sup></small> for gas phase glycine, -528.37 ± 0.20 kJ mol<small><sup>-1</sup></small> for solid α-glycine, -528.05± 0.22 kJ mol<small><sup>-1</sup></small> for β-glycine, -528.64 ± 0.23 kJ mol<small><sup>-1</sup></small> for γ-glycine, -514.22 ± 0.20 kJ mol<small><sup>-1</sup></small> for aqueous undissociated glycine, and -470.09 ± 0.20 kJ mol<small><sup>-1</sup></small> for fully dissociated aqueous glycine at infinite dilution. In addition, a new set of thermophysical properties of gas phase glycine was obtained from a fully corrected nonrigid rotor anharmonic oscillator (NRRAO) partition function, which includes all conformers. Corresponding sets of thermophysical properties of α-, β-, and γ-glycine are also presented.","PeriodicalId":76,"journal":{"name":"Faraday Discussions","volume":"58 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745587","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}
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