Aitomia: An Agentic Framework for AI-Driven Atomistic and Quantum Chemical Simulations [0.03%]
基于人工智能的原子级和量子化学模拟代理框架Aitomia
Jinming Hu,Hassan Nawaz,Yi-Fan Hou et al.
Jinming Hu et al.
We present Aitomia, an agentic framework for AI-driven atomistic and quantum chemical (QC) simulations that helps experts and nonexperts alike set up and run calculations, analyze results, and summarize them in textual and graphical forms t...
TorchDisorder: A Differentiable Framework for Generating Physically Realistic Disorder Structures from Experimental Diffraction Data [0.03%]
基于实验衍射数据生成物理上真实的无序结构的可微框架
Advait Gore,Xander Gouws,Conrard Giresse Tetsassi Feugmo
Advait Gore
Determining the atomic structure of amorphous materials remains a fundamental challenge in condensed-matter physics and materials science. Unlike crystalline solids, disordered systems lack long-range periodicity, which makes conventional d...
Integrating Charge Equilibration with Equivariant Machine-Learning Interatomic Potentials [0.03%]
带电平衡的等变机器学习势能模型
Martin Vondrák,William J Baldwin,Gábor Csányi et al.
Martin Vondrák et al.
Machine-learning interatomic potentials (MLIPs) based on local atomic environments have achieved remarkable accuracy and efficiency, yet they often struggle in systems where long-range electrostatics, charge transfer, and nonlocal electroni...
Bias in Universal Machine-Learned Interatomic Potentials and Its Effects on Fine-Tuning [0.03%]
机器学习势函数的偏差及其对微调的影响
Nicolas H Wong,Julia H Yang
Nicolas H Wong
Universal machine learned interatomic potentials (uMLIPs) embody a growing area of interest due to their transferability across the periodic table, displaying an error of about 0.6 kcal/mol against the Matbench Discovery test set. However, ...
Modeling Xanthophyll Excited States via Cost-Effective Quantum Chemistry methods and Property-Based Diabatization [0.03%]
基于属性的双态化及低成本量子化学方法构建叶黄素激发态模型
Amanda Arcidiacono,Valentino Martini,Lorenzo Cupellini et al.
Amanda Arcidiacono et al.
Xanthophyll carotenoids play essential roles in photosynthetic light harvesting and photoprotection in biological systems, yet the accurate description of their excited states at a feasible computational cost remains challenging due to thei...
How Long Is Long Enough? Extrapolation of Machine-Learning Interatomic Potentials for Oligomeric and Polymeric Systems [0.03%]
够长吗？机器学习多体势能的外推用于低聚物和聚合物体系
Natalie E Hooven,Arthur Y Lin,Charles H Carroll et al.
Natalie E Hooven et al.
Machine-learning interatomic potentials (MLIPs) have surged in popularity due to their promise of expanding the spatiotemporal scales possible for simulating molecules with high fidelity. The accuracy of any MLIP is dependent on the data us...
Monte Carlo-Based Prediction of Residual Dipolar Couplings in Weakly Aligned Molecules [0.03%]
基于蒙特卡罗的弱取向分子剩余 dipolar耦合预测
David Elsing,Fabian Hoffmann,Burkhard Luy et al.
David Elsing et al.
For the determination of the relative configuration in chiral molecules aligned by an alignment medium, the measurement and analysis of residual dipolar couplings (RDCs) is an established method. However, the agreement of in silico predicte...
A Deterministic Framework for Neural Network Quantum States in Quantum Chemistry [0.03%]
量子化学中神经网络量子状态的确定性框架
Zheng Che
Zheng Che
We present a deterministic optimization framework for neural network quantum states (NQS) designed to bypass the sampling variance and slow mixing issues inherent in stochastic optimization. By projecting a neural backflow ansatz onto dynam...
Multi-Objective Optimization of Conceptual DFT Reactivity Descriptors in Open-Shell Radicals by Reinforcement Learning [0.03%]
利用强化学习优化开壳烯烃概念DFT反应性描述符的多目标优化
Debojyoti Das,Preeti Christina Beck,Debdutta Chakraborty
Debojyoti Das
Open-shell organic radicals underpin catalysis, energy materials, and spin-based technologies, yet rational design is hindered by the difficulty of tuning electronic reactivity while preserving chemically meaningful local response. Here, a ...
From Localized to Delocalized OH···O Hydrogen Bonds: Benchmark of Hierarchical Quantum Chemical Methods against Rotational Spectroscopy [0.03%]
从局域化到非局域化的OH···O氢键：基于转动光谱学的分层量子化学方法基准测试研究
Lina Uribe,Luigi Crisci,Federico Lazzari et al.
Lina Uribe et al.
Intramolecular OH···O hydrogen bonds remain difficult to describe at spectroscopic accuracy. Electronic correlation, vibrational averaging, and conformational flexibility all influence the same rotational constants and the corresponding ...