Article
Chemistry, Physical
Marie-Claire Bellissent-Funel
Summary: This paper aims to analyze selected examples of confined water's structure and dynamics based on temperature. Examples are presented to illustrate the interactions between water molecules and model systems with hydrophilic/hydrophobic interactions or both, as well as biological macromolecules. The static and transport properties of confined water are compared to those of bulk water.
JOURNAL OF MOLECULAR LIQUIDS
(2023)
Article
Chemistry, Medicinal
Leonard Dick, Barbara Kirchner
Summary: In this paper, a Python code called CONAN is presented to study the interaction between liquids and solid structures. The program allows for generating different structures and analyzing the structural properties of liquids. The abilities of the tool are demonstrated by studying an ionic liquid in carbon nanotubes of different sizes.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Review
Chemistry, Multidisciplinary
Xiaojun Wei, Shilong Li, Wenke Wang, Xiao Zhang, Weiya Zhou, Sishen Xie, Huaping Liu
Summary: Structural control of single-wall carbon nanotubes (SWCNTs) is crucial for their property modulation and functional design. Various separation techniques have been developed to achieve high-purity semiconducting/metallic SWCNTs, single-chirality species, and even their enantiomers. These advancements have promoted property modulation and development of SWCNT-based optoelectronic devices.
Article
Biochemistry & Molecular Biology
Michael Fardis, Marina Karagianni, Lydia Gkoura, George Papavassiliou
Summary: Confined liquids, especially bulk water, serve as model systems for studying the metastable supercooled state. However, the onset of crystallization below 230 K makes it difficult to apply experimental techniques. Confined water exhibits drastically different properties at the nanoscale due to the nature of the confining environment and the interactions with the confining matrix. This study demonstrates that the translational mobility of water molecules, particularly in the supercooled state, can distinguish between hydrophilic and hydrophobic environments. Nuclear magnetic resonance and quasi-elastic neutron scattering are effective experimental methods for assessing water dynamics.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Chemistry, Physical
Wen Zhao, Hu Qiu, Wanlin Guo
Summary: In this study, a machine learning potential for water confined in graphene nanocapillaries was developed using deep neural networks trained on quantum mechanical density-functional theory (DFT) calculations. This potential offers near-DFT accuracy at a much lower computational cost and accurately reproduces a wide range of properties, opening the door to simulations of nanoconfined water with large system sizes and time scales at near-DFT accuracy.
JOURNAL OF PHYSICAL CHEMISTRY C
(2022)
Article
Chemistry, Physical
Laiyang Wei, Qi Bai, Xiaojiao Li, Ziyuan Liu, Chenruyuan Li, Yanhong Cui, Lin Shen, Chongqin Zhu, Weihai Fang
Summary: In this study, a stable monolayer ice structure called pZZMI was discovered by performing molecular dynamics simulations. This structure is formed by puckering the zigzag water chains of ZZMI in the direction perpendicular to the chains. Unlike other structures, each water molecule in pZZMI satisfies the ice rule and can form four hydrogen bonds.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Chemistry, Multidisciplinary
Marie-Claire Pignie, Viacheslav Shcherbakov, Thibault Charpentier, Melanie Moskura, Cedric Carteret, Sergey Denisov, Mehran Mostafavi, Antoine Thill, Sophie Le Caer
Summary: Imogolite nanotubes exhibit curvature-induced, efficient charge separation under irradiation, with electrons driven outward in the presence of very few external water molecules, leading to the formation of quasi-free electrons and ultimately dihydrogen. As the water content increases, electron solvation becomes more dominant, resulting in dihydrogen production to a lesser extent compared to quasi-free electrons. This study demonstrates the potential of imogolite nanotubes as co-photocatalysts due to their spontaneous charge separation behavior.
Article
Mechanics
Rong-Yao Yang, Pei-Ying Huo, Qi-Lin Zhang, Yong Jiang, Wei-Zhou Jiang
Summary: This paper reveals that water molecules confined in carbon nanotubes can enhance the absorption efficiency of mid-infrared (MIR) radiations by two times compared to bulk water absorption. The amplified absorption is attributed to the unidirectional alignment of water molecules under nanotube confinement, which increases the transition probability for MIR absorption. The confinement effect of a (6,6) carbon nanotube is found to be as strong as a 5 V/nm static electric field. These findings have implications for designing energy-efficient nanodevices and understanding the functioning of biological channels.
Article
Chemistry, Physical
Frederico G. Alabarse, Benoit Baptiste, Monica Jimenez-Ruiz, Benoit Coasne, Julien Haines, Jean-Blaise Brubach, Pascale Roy, Henry E. Fischer, Stefan Klotz, Livia E. Bove
Summary: The study found that water molecules in AlPO4-54 do not crystallize at temperatures as low as 10 K, and there are two different types of water networks present. Water near the zeolite pore wall exhibits a highly ordered arrangement, while water in the pore core is denser and more disordered.
JOURNAL OF PHYSICAL CHEMISTRY C
(2021)
Article
Chemistry, Multidisciplinary
Fabian L. Thiemann, Christoph Schran, Patrick Rowe, Erich A. Muller, Angelos Michaelides
Summary: This study investigates water transport in carbon nanotubes and boron nitride nanotubes using machine learning-based molecular dynamics simulations. The simulations reveal that water experiences less friction on carbon surfaces compared to boron nitride, resulting in faster water flow in carbon nanotubes. The difference in friction arises from different mechanisms, with oxygen motion playing a role in carbon nanotubes and hydrogen-nitrogen interactions in boron nitride nanotubes.
Article
Physics, Multidisciplinary
Sun Zhi-Wei, He Yan, Tang Yuan-Zheng
Summary: Carbon nanotubes are considered as nano-channels for various molecular substances, especially nanoscaled aqueous solutions. The study of water structures in confined spaces of carbon nanotubes is of theoretical importance in chemistry, biology, and materials science. Molecular dynamic simulation is used to investigate the effects of CNT diameter, CNT chirality, and temperature on the water structure and distribution in the confined space, revealing that the stability of the ordered water structure is temperature-dependent and influenced by the CNT diameter.
ACTA PHYSICA SINICA
(2021)
Article
Materials Science, Multidisciplinary
Shuang Liu, Hai-yan Li, Zhen Yao, Shuangchen Lu
Summary: The N-10@(8, 0)CNT structure has high polymeric nitrogen ratio and energy density, with a high energy barrier and decomposition temperature, and strong stability.
MATERIALS TODAY COMMUNICATIONS
(2021)
Article
Chemistry, Physical
Sohaib Mohammed, Hassnain Asgar, Chris J. Benmore, Greeshma Gadikota
Summary: The anomalous thermodynamic properties of confined water have motivated research on the structure of confined water as a function of pore size and temperature. Experimental and simulation results provide comprehensive insights underlying the organization of confined water and ice in silica nanopores and the underlying physico-chemical interactions that contribute to the observed structures.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2021)
Article
Chemistry, Multidisciplinary
Sally Jiao, Lynn E. Katz, M. Scott Shell
Summary: This study presents a computational inverse design approach to optimize the transport properties of membrane materials by spatially designing chemical functional group patterns. The research discovered that patterning specific functional groups can hinder solute transport and utilize unexpected diffusion mechanisms. This work provides new routes for the design of membrane materials with novel functionalities.
ACS CENTRAL SCIENCE
(2022)
Article
Chemistry, Physical
Weilu Gao, Davoud Adinehloo, Xinwei Li, Ali Mojibpour, Yohei Yomogida, Atsushi Hirano, Takeshi Tanaka, Hiromichi Kataura, Ming Zheng, Vasili Perebeinos, Junichiro Kono
Summary: This study investigates the chirality-dependent electronic transport properties of single-chirality SWCNT films, revealing pronounced electronic localization phenomena and providing insights for designing and deploying macroscopic SWCNT solid-state devices. The research highlights the importance of understanding chirality-dependent behaviors in SWCNTs for various applications.
Article
Chemistry, Physical
April M. Cooper, Johannes Kaestner, Alexander Urban, Nongnuch Artrith
NPJ COMPUTATIONAL MATERIALS
(2020)
Article
Chemistry, Physical
Nongnuch Artrith, Zhexi Lin, Jingguang G. Chen
Article
Biochemistry & Molecular Biology
Tobias Morawietz, Nongnuch Artrith
Summary: Recent advances in machine learning methods have significantly expanded the applicability range of quantum mechanical simulations, allowing for more accurate calculations, reduced costs, and access to length and time scales that were previously inaccessible. The benefits of ML-accelerated atomistic simulations in industrial R&D processes have been showcased in pharmaceuticals and energy materials, demonstrating their important impact on various industries.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2021)
Article
Chemistry, Physical
Michael S. Chen, Tobias Morawietz, Hideki Mori, Thomas E. Markland, Nongnuch Artrith
Summary: The study developed two interfaces that link MLPs with sampling software TINKER and LAMMPS, enabling low-cost and efficient accurate simulations of large and complex systems. The parallel efficiency of the AE net-TINKER interface is nearly optimal on shared-memory systems, while the AE net-LAMMPS interface achieves excellent parallel efficiency on highly parallel distributed-memory systems.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Editorial Material
Chemistry, Multidisciplinary
Nongnuch Artrith, Keith T. Butler, Francois-Xavier Coudert, Seungwu Han, Olexandr Isayev, Anubhav Jain, Aron Walsh
Summary: In chemistry research, statistical tools based on machine learning are being integrated to train reliable, repeatable, and reproducible models. Guidelines for machine learning reports are recommended to ensure the quality of the models.
Review
Energy & Fuels
Haoyue Guo, Qian Wang, Annika Stuke, Alexander Urban, Nongnuch Artrith
Summary: Machine learning has proven to be versatile in accelerating material property modeling and design in solid-state batteries, particularly for various components involved in solid-state batteries.
FRONTIERS IN ENERGY RESEARCH
(2021)
Article
Multidisciplinary Sciences
Jose Antonio Garrido Torres, Vahe Gharakhanyan, Nongnuch Artrith, Tobias Hoffmann Eegholm, Alexander Urban
Summary: This study combines quantum-mechanics based calculations with machine learning to accurately predict high-temperature reaction free energies in oxides. The hybrid approach is computationally efficient and provides accurate predictions for unseen oxides, surpassing more demanding first-principles simulations. This method offers a general paradigm for capturing temperature dependence of reaction free energies when experimental data is limited.
NATURE COMMUNICATIONS
(2021)
Article
Materials Science, Multidisciplinary
Nongnuch Artrith, Jose Antonio Garrido Torres, Alexander Urban, Mark S. Hybertsen
Summary: This article presents a systematic method to determine parameters and optimize the errors of semilocal density-functional theory (DFT) methods for transition-metal oxides phase diagrams. By considering thermochemical data of a set of compounds and using leave-one-out cross validation, the proposed correction terms reduce the errors in the formation energies of binary and ternary oxides by up to 75% and achieve an error reduction of 30% using a simplified scheme.
PHYSICAL REVIEW MATERIALS
(2022)
Article
Chemistry, Physical
Xinhao Li, Qian Wang, Haoyue Guo, Nongnuch Artrith, Alexander Urban
Summary: This study presents a first-principles methodology for predicting the surface reconstructions of intercalation electrode particles in lithium-ion batteries. The surface phase diagrams of LiNiO2 (001) and (104) surfaces are reported, and the impact of temperature and voltage range on the charge/discharge mechanism is discussed.
ACS APPLIED ENERGY MATERIALS
(2022)
Article
Chemistry, Physical
Haoyue Guo, Qian Wang, Alexander Urban, Nongnuch Artrith
Summary: In this study, the LPS phase diagram was mapped using first-principles and artificial intelligence methods. The relationship between LPS glass/ceramic phases and local structural motifs was determined. Based on the discovered trends, a candidate solid-state electrolyte composition with high ionic conductivity and stability was proposed.
CHEMISTRY OF MATERIALS
(2022)
Correction
Physics, Multidisciplinary
Allan S. Johnson, Daniel Perez-Salinas, Khalid M. Siddiqui, Sungwon Kim, Sungwook Choi, Klara Volckaert, Paulina E. Majchrzak, Soren Ulstrup, Naman Agarwal, Kent Hallman, Richard F. Haglund, Christian M. Guenther, Bastian Pfau, Stefan Eisebitt, Dirk Backes, Francesco Maccherozzi, Ann Fitzpatrick, Sarnjeet S. Dhesi, Pierluigi Gargiani, Manuel Valvidares, Nongnuch Artrith, Frank de Groot, Hyeongi Choi, Dogeun Jang, Abhishek Katoch, Soonnam Kwon, Sang Han Park, Hyunjung Kim, Simon E. Wall
Article
Physics, Multidisciplinary
Allan S. Johnson, Daniel Perez-Salinas, Khalid M. Siddiqui, Sungwon Kim, Sungwook Choi, Klara Volckaert, Paulina E. Majchrzak, Soren Ulstrup, Naman Agarwal, Kent Hallman, Richard F. Haglund, Christian M. Guenther, Bastian Pfau, Stefan Eisebitt, Dirk Backes, Francesco Maccherozzi, Ann Fitzpatrick, Sarnjeet S. Dhesi, Pierluigi Gargiani, Manuel Valvidares, Nongnuch Artrith, Frank de Groot, Hyeongi Choi, Dogeun Jang, Abhishek Katoch, Soonnam Kwon, Sang Han Park, Hyunjung Kim, Simon E. Wall
Summary: Using time- and spectrally resolved coherent X-ray imaging, the researchers track the prototypical light-induced insulator-to-metal phase transition in vanadium dioxide on the nanoscale with femtosecond time resolution. They observe that the early-time dynamics are independent of the initial spatial heterogeneity and show a 200 fs switch to the metallic phase. Heterogeneous response emerges only after hundreds of picoseconds.
Article
Chemistry, Physical
Jon Lopez-Zorrilla, Xabier M. Aretxabaleta, In Won Yeu, Inigo Etxebarria, Hegoi Manzano, Nongnuch Artrith
Summary: In this work, a PyTorch-based implementation for training interatomic potentials is presented. This implementation allows for direct training on forces and significantly reduces training time compared to the CPU implementation. The results demonstrate that including between 10% and 20% of the force information is sufficient for achieving accurately optimized interatomic potentials.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Review
Computer Science, Artificial Intelligence
April M. Miksch, Tobias Morawietz, Johannes Kaestner, Alexander Urban, Nongnuch Artrith
Summary: This article discusses recent progress and challenges in using machine-learning interatomic potentials for modeling complex atomic systems, providing a tutorial overview of strategies for constructing artificial neural network potentials. The aim is to help computational chemists and materials scientists accelerate the adoption of this method by equipping them with the necessary background knowledge.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2021)
Editorial Material
Materials Science, Multidisciplinary
Nongnuch Artrith