Publications
Matlantisを用いた論文事例
- タイトル
- 著者
- 公開
- 引用方法
- Solid-liquid phase boundary of oxide solid solutions using neural network potentials
- Kazushige Hyodo et al.
- 2024
J. Alloys Compd. 1006, 176227 (2024)
- Theoretical Catalyst Screening of Multielement Alloy Catalysts for Ammonia Synthesis Using Machine Learning Potential and Generative Artificial Intelligence
- Kaoru Hisama et al.
- 2024
J. Phys. Chem. C, https://doi.org/10.1021/acs.jpcc.4c04018
- Effects of Alkyl Side Chain Length on the Structural Organization and Proton Conductivity of Sulfonated Polyimide Thin Films
- Tetsuya Honbo et al.
- 2024
ACS Appl. Polym. Mater., https://doi.org/10.1021/acsapm.4c02490
- Rise of machine learning potentials in heterogeneous catalysis: Developments, applications, and prospects
- Seokhyun Choung et al.
- 2024
Chem. Eng. J. 494, 152757 (2024)
- Intelligent Stress-Adaptive Binder Enabled by Shear-Thickening Property for Silicon Electrodes of Lithium-Ion Batteries
- Ohhyun Kwon et al.
- 2024
Adv. Energy Mater. 14, 2304085 (2024)
- Exploring Electrolyte Adsorption on the Different Types of Layered Cathode Surfaces in Lithium-Ion Batteries via a Universal Neural Network Potential Method
- Attila Taborosi et al.
- 2024
ACS Omega 9, 42116 (2024)
- Universal Neural Network Potential-Driven Molecular Dynamics Study of CO2/O2 Evolution at the Ethylene Carbonate/Charged–Electrode Interface
- Motoki Horibe et al.
- 2024
ACS Appl. Mater. Interfaces 16, 53621 (2024)
- Experimental study on Na⁺ conductivity in NaAlBr4 and atomic-scale investigation of Na+ conduction
- Reona Miyazaki et al.
- 2024
Journal of Solid State Electrochemistry, https://doi.org/10.1007/s10008-024-06086-z
- Stress-Induced Martensitic Transformation in Na3YCl6
- Akira Miura et al.
- 2024
J. Am. Chem. Soc. 146, 25263–25269 (2024)
- Effect of very slow O diffusion at high temperature on very fast H diffusion in the hydride ion conductor LaH2.75O0.125
- Yoyo Hinuma
- 2024
Computational Materials Science 246, 113368 (2024)
- Adsorption of Phosphorus-Type Anti-Wear Agents for Refrigerator Nonpolar-Oil Additives
- Hiromi YUASA et al.
- 2024
JOURNAL OF JAPANESE SOCIETY OF TRIBOLOGISTS, https://doi.org/10.18914/tribologist.24-00003
- In situ ambient pressure x-ray photoelectron spectroscopy study on O2/H2O-assisted Na–CO2 batteries
- Kevin Iputera et al.
- 2024
Journal of Energy Storage 100, 113467 (2024)
- Hydrogen production by NH3 decomposition at low temperatures assisted by surface protonics
- Yukino Ofuchi et al.
- 2024
Chem. Sci. 15, 15125 (2024)
- Mechanistic Study on NH3 Decomposition over Cu-Exchanged CHA Zeolites Using Automated Reaction Route Mapping Combined with Neural Network Potential and Density Functional Theory Calculations
- Shunsaku Yasumura et al.
- 2024
J. Phys. Chem. C 128, 12949–12959 (2024)
- A Practical and Sustainable Ni/Co-Free High-Energy Electrode Material: Nanostructured LiMnO2
- Yuka Miyaoka et al.
- 2024
ACS Central Science, https://doi.org/10.1021/acscentsci.4c00578
- Molecular dynamics of liquid–electrode interface by integrating Coulomb interaction into universal neural network potential
- Kaoru Hisama et al.
- 2024
Journal of Computational Chemistry, https://doi.org/10.1002/jcc.27487
- Machine Learning in Catalysis: Analysis and Prediction of CO Adsorption on Multi-elemental Nanoparticle using Metal Coordination-based Regression Model
- Susan Menez ASPERA et al.
- 2024
Journal of Computer Chemistry, Japan 23, 19-23 (2024)
- Universal-neural-network-potential molecular dynamics for lithium metal and garnet-type solid electrolyte interface
- Susan Menez ASPERA et al.
- 2024
Communications Materials 5, 148 (2024)
- Exploring Ti active sites in Ziegler-Natta catalysts through realistic-scale computer simulations with universal neural network potential
- Masaki Fushimi and Devaiah Damma
- 2024
Molecular Catalysis 565, 114414 (2024)
- Onset of tetrahedral interstitial formation in GaAsN alloys
- Cooper et al.
- 2024
Applied Physics Letters 124, no. 16 (2024)
- Quantitative analysis of plasma-enhanced chemical vapor deposition mechanisms: Quantum chemical and plasma-fluid dynamics investigation on tetraethoxysilane/O2 plasma
- Hu Li et al.
- 2024
J. Vac. Sci. Technol. A 42, 043002 (2024)
- Adsorption of dimethylaluminum isopropoxide (DMAI) on the Al2O3 surface: A machine-learning potential study
- Miso Kim et al.
- 2024
Journal of Science: Advanced Materials and Devices Volume 9, Issue 3, 100754 (2024)
- High-throughput investigation of stability and Li diffusion of doped solid electrolytes via neural network potential without configurational knowledge
- Ryohto Sawada et al.
- 2024
Scientific Reports 14, 11602 (2024)
- The Role of External Donors in Ziegler−Natta Catalysts through Nudged Elastic Band Simulations on Realistic-Scale Models Employing a Universal Neural Network Potential
- Masaki Fushimi and Devaiah Damma
- 2024
J. Phys. Chem. C 128, 6646 (2024)
- A New Zinc Salt Chemistry for Aqueous Zinc-Metal Batteries
- Haoran Du et al.
- 2024
Advanced Materials 35, 2210055 (2023)
- Spectroscopic and theoretical analyses of the reaction of SrO in molten chloride and fluoride salts
- Dokyu Kang et al.
- 2024
Journal of Nuclear Materials 592, 154962 (2024)
- Proton Conduction over the Zeolite with Surface Water Cluster for the Water Electrolysis at Neutral Condition
- Keigo Tashiro et al.
- 2023
ChemCatChem e202301297 (2023)
- Exploration of the mechanical properties of carbon-incorporated amorphous silica using a universal neural network potential
- Hiroki Sakakima et al.
- 2024
J. Appl. Phys. 135, 085104 (2024)
- Exploration of elastic moduli of molecular crystals via database screening by pretrained neural network potential
- Takuya Taniguchi
- 2024
CrystEngComm 26, 631-638 (2024)
- Boron coordination and three-membered ring formation in sodium borate glasses: a machine-learning molecular dynamics study
- Takeyuki Kato et al.
- 2023
J. Am. Ceram. Soc. 1–13 (2023)
- Evolutionary search for superconducting phases in the lanthanum-nitrogen-hydrogen system with universal neural network potential
- Takahiro Ishikawa et al.
- 2023
arXiv 2312.01290
- Increasing the Sodium Metal Electrode Compatibility with the Na3PS4 Solid-State Electrolyte through Heteroatom Substitution
- Lieven Bekaert et al.
- 2023
ChemSusChem e202300676 (2023)
- CO Adsorption on Ternary Nanoalloys by Universal Neural Network Potential
- Ayako TAMURA et al.
- 2023
J. Comput. Chem. Jpn. 21, 129-133 (2023)
- Using GPT-4 in Parameter Selection of Materials Informatics: Improving Predictive Accuracy Amidst Data Scarcity and ‘Ugly Duckling’ Dilemma
- Kan Hatakeyama-Sato et al.
- 2023
Digital Discovery 2, 1548-1557 (2023)
- On the Thermodynamic Stability of Alloys: Combination of Neural Network Potential and Wang-Landau Sampling
- Tien Quang Nguyen et al.
- 2023
J. Comput. Chem. Jpn. 21, 111–117 (2023)
- Assessing the Reactivity of the Na3PS4 Solid-State Electrolyte with the Sodium Metal Negative Electrode Using Total Trajectory Analysis with Neural-Network Potential Molecular Dynamics
- Lieven Bekaert et al.
- 2023
J. Phys. Chem. C 18, 8503–8514 (2023)
- Quantum Annealing Boosts Prediction of Multimolecular Adsorption on Solid Surfaces Avoiding Combinatorial Explosion
- Hiroshi Sampei et al.
- 2023
JACS Au 3, 991–996 (2023)
- Effect of HFO Refrigerants on Lubrication Characteristics (Part 2) -Adsorption Characteristics of Various Refrigerants on Nascent Iron Surfaces and Molecular Simulation Analysis-
- Yuji Shitara et al.
- 2023
Tribologist 68, 280-291 (2023)
- Effect of HFO Refrigerants on Lubrication Characteristics (Part 1) -Tribological Characteristics under Refrigerant Atmosphere and Adsorption Characteristics on Nascent Metal Surface-
- Yuji Shitara et al.
- 2022
Tribologist 67, 662-671 (2022)
- Innovation in Molecular Simulation Technologies for Tribology Using Artificial Intelligence
- Tasuku Onodera
- 2022
Computational Materials Science 218, 111955 (2022)
- Comparison of Matlantis and VASP bulk formation and surface energies in metal hydrides, carbides, nitrides, oxides, and sulfides
- Shinya Mine et al.
- 2023
arXiv 2304.10820
- Molecular dynamics of electric-field driven ionic systems using a universal neural-network potential
- Kaoru Hisama et al.
- 2022
Computational Materials Science 218, 111955 (2022)
- Cyber Catalysis: N2 Dissociation over Ruthenium Catalyst with Strong Metal-Support Interaction
- Gerardo Valadez Huerta et al.
- 2022
arXiv 2208.13385
- Calculations of Real-System Nanoparticles Using Universal Neural Network Potential PFP
- Gerardo Valadez Huerta et al.
- 2021
arXiv 2107.00963
Matlantisに関する論文
- タイトル
- 著者
- 公開
- 引用方法
- Towards universal neural network interatomic potential
- So Takamoto et al.
- 2023
Journal of Materiomics Volume 9, Issue 3, 447-454 (2023)
- Towards universal neural network potential for material discovery applicable to arbitrary combination of 45 elements
- So Takamoto et al.
- 2022
Nature Communications 13, 2991 (2022)