Results 131 to 140 of about 377,401 (276)

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

Practical fixed-time stabilization for discrete-time impulsive switched port-controlled Hamiltonian systems

Nonlinear Analysis
This paper is concerned with practical fixed-time (FT) stabilization problem of discretetime impulsive switched port-controlled Hamiltonian systems (DISPCH).
Xiangyu Chen, Weiwei Sun, Xinci Gao, Dehay Yu   +3 more
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

Applications of the Kosambi–Cartan–Chern Theory to Hamiltonian Systems on a Cotangent Bundle: Linking Geometric Quantities to the Self-Similar Motions of Three Point Vortices

Mathematics
This study presents a differential geometric framework for Hamiltonian systems expressed in terms of first-order differential equations. For systems governed by second-order ordinary differential equations on tangent bundles, such as Euler–Lagrange ...
Yuma Hirakui, Takahiro Yajima
doaj   +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

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

Quadrature Based Neural Network Learning of Stochastic Hamiltonian Systems

Mathematics
Hamiltonian Neural Networks (HNNs) provide structure-preserving learning of Hamiltonian systems. In this paper, we extend HNNs to structure-preserving inversion of stochastic Hamiltonian systems (SHSs) from observational data.
Xupeng Cheng, Lijin Wang, Yanzhao Cao
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

On the Structure and Redox Behavior of Ni and Cu Single Atoms Supported on Carbon Nitride

Angewandte Chemie, EarlyView.
Magnetic and electronic spectroscopies, combined with DFT, establish the MN4 binding site of Ni and Cu single atoms on carbon nitride and elucidate their redox photochemistry. Ni undergoes geometry‐preserving, reversible M2+/M+ cycling, whereas Cu collapses to an irreversible low‐coordinate Cu+ state, suppressing photocatalysis.
Giovanni Colonnello, Ksenija Maver, Arianna Actis, Gaia Grando, Giacomo Filippini, Tiziano Montini, Michele Melchionna, Paolo Fornasiero, Lucia Nasi, Iztok Arčon, Lorenzo Donà, Bartolomeo Civalleri, Enrico Salvadori, Mario Chiesa   +13 more
wiley   +2 more sources

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