Results 131 to 140 of about 352,057 (287)

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

A collision operator for describing dissipation in noncanonical phase space

Fundamental Plasma Physics
The phase space of a noncanonical Hamiltonian system is partially inaccessible due to dynamical constraints (Casimir invariants) arising from the kernel of the Poisson tensor.
Naoki Sato, Philip J. Morrison
doaj   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source

A New IBM-1 Hamiltonian Parameterization Based on Dynamical Symmetry for Even-Even Se74-78, Ru104-106 and Mo106-108

East European Journal of Physics
The present study investigates the dynamical symmetries of even-even Se^74-78, Ru^104-106  and Mo^106-108  isotopes within the framework of the Interacting Boson Model-1 (IBM-1).
Berun N. Ghafoor
doaj   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

The Relationship Between Lagrangian and Hamiltonian Mechanics: The Irregular Case

Philosophy of Physics
Lagrangian and Hamiltonian mechanics are widely held to be two distinct but equivalent ways of formulating classical theories. Barrett (2019) makes this intuition precise by showing that under a certain characterization of their structure, the two ...
Clara Bradley
doaj   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Elucidating the Transition Kernel and Anharmonic Coupling in the Spin‐crossover Process of a [FeIII(qsal)2] CH3OSO3 Complex

Angewandte Chemie, EarlyView.
Ultrafast broadband transient absorption spectroscopy and multireference excited‐state nonadiabatic calculations in an open‐shell Fe(III) complex unveil the rich electronic and vibrational dynamics detailing the key reactive modes driving the spin‐crossover process.
Soumyajit Mitra, Dilara Farkhutdinova, Sebastian Mai, Stuart A. Hayes, Yifeng Jiang, Tadahiko Ishikawa, Kazuyuki Takahashi, Leticia González, R. J. Dwayne Miller   +8 more
wiley   +2 more sources

Hamiltonian transformation for accurate and efficient band structure interpolation

npj Computational Materials
Electronic band structure is a cornerstone of condensed matter physics and materials science. Conventional methods like Wannier interpolation (WI), which are commonly used to interpolate band structures onto dense k-point grids, often encounter ...
Kai Wu, Yingzhou Li, Wentiao Wu, Lin Lin, Wei Hu, Jinlong Yang   +5 more
doaj   +1 more source