The Journal of Physical Chemistry Letters最新文献_第5页

Coherent Electron Transfer in Cytochrome Nanowires at 300 K. 细胞色素纳米线在300 K下的相干电子转移。

IF 6.475 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31 DOI: 10.1021/acs.jpclett.5c01339

William W Parson,Peter J Dahl,Nikhil S Malvankar

引用次数: 0

Structural Feature Extraction via Topological Data Analysis. 基于拓扑数据分析的结构特征提取。

IF 6.475 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31 DOI: 10.1021/acs.jpclett.5c01831

Bingxu Wang,Bin Feng,Linpeng Lv,Shunning Li,Feng Pan

{"title":"Structural Feature Extraction via Topological Data Analysis.","authors":"Bingxu Wang,Bin Feng,Linpeng Lv,Shunning Li,Feng Pan","doi":"10.1021/acs.jpclett.5c01831","DOIUrl":"https://doi.org/10.1021/acs.jpclett.5c01831","url":null,"abstract":"With the advancement of artificial intelligence models, the development of scientifically grounded and structurally appropriate feature extraction methods has become critical for machine learning-based structure prediction and materials design. In recent years, there has been growing dissatisfaction with inefficient empirical descriptors and black-box feature extraction processes that require extensive training. This article introduces a topological data analysis-based framework for extracting structural features of materials, offering an informative perspective on structure-property relationships and predictive strategies. Emphasis is placed on the predictive power and interpretability of topological features, highlighting their advantages in uncovering structure-property correlations and providing physical insights into material behavior. This approach establishes a mathematically rigorous and computationally efficient paradigm for the discovery and design of advanced materials, achieving up to 55% reduction in prediction error for defect-sensitive properties and a notable improvement in MOF gas uptake prediction accuracy (e.g., R2 from 0.74 to 0.85), thus demonstrating both theoretical clarity and practical performance.","PeriodicalId":62,"journal":{"name":"The Journal of Physical Chemistry Letters","volume":"719 1","pages":"8056-8067"},"PeriodicalIF":6.475,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144747982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Polaritonic Control of Blackbody Infrared Radiative Dissociation. 黑体红外辐射解离的极化控制。

IF 4.6 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31 Epub Date: 2025-07-18 DOI: 10.1021/acs.jpclett.5c01475

Enes Suyabatmaz, Gustavo J R Aroeira, Raphael F Ribeiro

引用次数: 0

Optimizing SPION Labeling for Single-Cell Magnetic Microscopy. 单细胞磁显微镜SPION标记的优化。

IF 4.6 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31 Epub Date: 2025-07-21 DOI: 10.1021/acs.jpclett.5c01446

Andre Pointner, Daniela Thalheim, Sarah Belasi, Lukas Heinen, Cristian Bonato, Tobias Luehmann, Jan Meijer, Rainer Tietze, Christoph Alexiou, Regine Schneider-Stock, Roland Nagy

{"title":"Optimizing SPION Labeling for Single-Cell Magnetic Microscopy.","authors":"Andre Pointner, Daniela Thalheim, Sarah Belasi, Lukas Heinen, Cristian Bonato, Tobias Luehmann, Jan Meijer, Rainer Tietze, Christoph Alexiou, Regine Schneider-Stock, Roland Nagy","doi":"10.1021/acs.jpclett.5c01446","DOIUrl":"10.1021/acs.jpclett.5c01446","url":null,"abstract":"This study explores the correlation between the iron mass on cell surfaces and the resultant magnetic field. Human colorectal cancer cells (HT29 line) were labeled with varying concentrations of superparamagnetic iron oxide nanoparticles (SPIONs) and imaged via an NV center widefield magnetic microscope. To assess the labeling efficacy, a convolutional neural network trained on simulated magnetic dipole data was utilized to reconstruct key labeling parameters on a cell-by-cell basis, including cell diameter, sensor proximity, and the iron mass associated with surface-bound SPIONs. Our analysis provided quantitative metrics for these parameters across a range of labeling concentrations. The findings indicated that increasing the SPION concentration enhances both the cell-surface iron mass and magnetic field strength, demonstrating a saturation effect. This methodology offers a coherent framework for the quantitative, high-throughput characterization of magnetically labeled cells, presenting significant implications for the fields of cell biology and magnetic sensing applications.","PeriodicalId":62,"journal":{"name":"The Journal of Physical Chemistry Letters","volume":" ","pages":"7584-7590"},"PeriodicalIF":4.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144673386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Reaction Exploration Reveals Strong Kinetic Filtering in Li-Ion Battery Electrolyte Degradation. 反应探索揭示锂离子电池电解液降解中的强动力学过滤。

IF 4.6 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31 Epub Date: 2025-07-22 DOI: 10.1021/acs.jpclett.5c01123

Hsuan-Hao Hsu, Tianfan Jin, Brett M Savoie

{"title":"Reaction Exploration Reveals Strong Kinetic Filtering in Li-Ion Battery Electrolyte Degradation.","authors":"Hsuan-Hao Hsu, Tianfan Jin, Brett M Savoie","doi":"10.1021/acs.jpclett.5c01123","DOIUrl":"10.1021/acs.jpclett.5c01123","url":null,"abstract":"A solid electrolyte interphase (SEI) forms spontaneously during the first few recharging cycles of a lithium-ion battery (LIB) due to electrolyte degradation at the electrodes. The properties of the SEI critically affect the lifespan and stability of LIBs, but the degradation reactions governing SEI formation are challenging to resolve, and broadly applicable computational methods for prediction remain limited. In this study, we demonstrate that automated reaction exploration methods can predict major degradation products of common electrolytes without relying on experimental data, revealing how kinetic barriers create strong filtering effects that constrain the observable degradation chemistry from a multitude of theoretically possible pathways. The degradation chemistry of a traditional LIB electrolyte, consisting of ethylene carbonate (EC) and lithium hexafluorophosphate (LiPF6), is analyzed out to a depth of five reactions as a benchmark. Despite the multitude of theoretically possible reaction pathways, our computational chemical reaction network (CRN) reveals strong kinetic selectivity toward lithium ethylene monocarbonate (LEMC) and lithium ethylene dicarbonate (LEDC), including several previously unreported routes to these key SEI organic species. The resulting network provides a unified explanation for how reaction barriers and kinetics drive the competing formation of LEMC and LEDC and clarifies the influence of moisture on SEI aging. Generated entirely on the basis of computational transition state searches, this comprehensive CRN demonstrates the potential of reaction exploration methods to uncover mechanistic insights governed by kinetic filtering and enable rational electrolyte design.","PeriodicalId":62,"journal":{"name":"The Journal of Physical Chemistry Letters","volume":" ","pages":"7685-7694"},"PeriodicalIF":4.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

IF 4.6 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31

Yaxin Wang, and , Zhigang Shuai*,

引用次数: 0

Complexing Agent-Assisted Membraneless Zinc-Iodine Aqueous Batteries. 络合剂辅助无膜锌碘水电池。

IF 6.475 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31 DOI: 10.1021/acs.jpclett.5c01959

Yutong Wu,Maxim Zhelyabovskiy,Zhitao Chen,Karam Eeso,Alexandros Filippas,Haochen Yang,Guang Yang,Nian Liu

引用次数: 0

IF 4.6 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31

Chien-Lun Hung, Wen-Hsien Wang, Yu-Chuan Chang, Yei-Chen Lai* and Yun-Wei Chiang*,

引用次数: 0

IF 4.6 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31

Zihui Zhou, Tao Li*, Pingyuan Yan, Zhongqi Xie, Chengqiang Wang, Muyan Zhu, Heng Li and ChuanXiang Sheng*,

引用次数: 0

IF 4.6 2区化学

The Journal of Physical Chemistry Letters Pub Date : 2025-07-31

Margareth S. Baidun, Alexander A. Kolganov, Anastassia N. Alexandrova and Evgeny A. Pidko*,

引用次数: 0