Results 91 to 100 of about 8,369 (238)

Parallel unconstrained minimization of potential energy in LAMMPS

, 1997
This report describes a new minimization capability added to LAMMPS V4.0. Minimization of potential energy is used to find molecular conformations that are close to structures found in nature.
Plantenga, T.
core   +1 more source

Engineering Na‐Rich P2‐Type Layered Oxides Through Li/Ti Dual Doping for Oxygen Redox Activation and Superior Structural Stability

Advanced Energy Materials, EarlyView.
P2‐type sodium layered oxides have potential for high‐voltage operation but suffer from structural instability and capacity fading. This work demonstrates that synergistic Li and Ti co‐doping enhances sodium inventory, suppresses detrimental phase transitions, and activates reversible lattice oxygen redox.
Rishika Jakhar, Shrestha Ghosh, Adesh Rohan Mishra, Shristi Pradhan, Debalina Sarkar, Yuanlong Bill Zheng, Zengqing Zhuo, Tianyi Li, Lu Ma, Minghao Zhang, Shyue Ping Ong, Matthew Li, Leeann Sun, Prabhat Thapliyal, Jing Wang, Abhik Banerjee, Ying Shirley Meng   +16 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Decoupling Quasi‐Solid‐State Sulfur Conversion Mechanisms in Weakly Solvating and Locally High Concentration Electrolytes

Advanced Energy Materials, EarlyView.
Weakly solvating CME–TTE and localized high‐concentration G2–TTE electrolytes redirect lithium–sulfur chemistry toward quasi‐solid‐state conversion through distinct coordination environments. Molecular dynamics and multimodal electrochemical and spectroscopic measurements show that G2–TTE couples multidentate solvent coordination, anion participation ...
Boyi Pang, Huanxin Li, Liam Bird, Yiming Guo, Bochen Li, Xiaoxia Guo, Roby Soni, Yi Zeng, Paul R. Shearing, Thomas S. Miller, Rhodri Jervis, Alexander J. Kibler, James B. Robinson   +12 more
wiley   +1 more source

O pacote LAMMPS como uma ferramenta para o ensino de transição de fases [PDF]

Revista Brasileira de Ensino de Física
A interpretação e descrição dos fenômenos naturais, intrínseca à Ciência, demanda abstração conceitual, utilizando observações e construções teóricas.
Thiago Puccinelli, Murilo Sodré Marques, José Rafael Bordin   +2 more
doaj   +1 more source

ZrH Lammps Input and Structures

, 2019
Lammps input and structure files for Zr/H systems relating to modelling the effect of hydrogen on crack growth in zirconium via molecular ...
Adam Lloyd (3135498)
core   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Multiscale and Multi‐Timestep Switching of Multiple Machine Learning Force Fields for Artificial Intelligence‐Driven Materials Simulations

Advanced Intelligent Discovery, EarlyView.
Deep Potential model switching accelerates molecular dynamics by using a faster 4 Å model for most timesteps and periodically applying a high‐accuracy 6 Å model. Validation on solid TiO2 and liquid PEG shows preserved RDF correlations and stable NPT behavior, while NVE energy‐drift analyses identify cases requiring additional validation.
Ryuya Kanda, Megumu Yamazaki, Yuta Yoshimoto, Shintaro Izumi, Atsuki Inoue, Hiroshi Kawaguchi, Yasufumi Sakai   +6 more
wiley   +1 more source

Objectives and Key Results–Driven Multiagent Framework for Mechanical Design and Simulation

Advanced Intelligent Systems, EarlyView.
Objectives and key results (OKR)‐agent, an OKR‐driven multiagent framework, turns a plain‐language engineering goal into completed mechanical simulations. Three peer agents—supervisor, modeler, and simulator—share a compact board of OKR and coordinate external molecular dynamics (MD) and finite‐element solvers through a standardized tool interface. The
Jie Tian, Lin Pang, Jixin Hou, Xiao Sun, James Jaraczewski, Xianyan Chen, Kenan Song, Xiaoming Zhai, Tianming Liu, Keke Tang, Xianqiao Wang   +10 more
wiley   +1 more source

On data benchmarking and verification of discrete granular simulations

Data in Brief
Since the seminal work of Cundall and Strack (1979), the Discrete Element Method (DEM) has now become accepted as a key tool amongst researchers exploring the fundamental behavior of granular materials.
Jose Salomon, Catherine O'Sullivan, Fernando Patino-Ramirez   +2 more
doaj   +1 more source