Results 111 to 120 of about 9,553 (252)

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

Water, Alcohols, Amines, and Amides as Formal Hydrogen‐Atom‐Transfer Reagents Through Activation With Redox‐Active Lewis Acids

Angewandte Chemie, EarlyView.
Protic molecules containing strong O─H or N─H bonds typically resist hydrogen‐atom abstraction because of the high reactivity of the resulting heteroatom‐centered radicals. However, association of the protic molecules with redox‐active Lewis acids can provide powerful hydrogen‐atom donors or proton‐coupled‐electron‐transfer reagents.
Petra Vojáčková, Armido Studer
wiley   +2 more sources

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

A High‐Voltage Membrane‐Free Li–Organic Hybrid Flow Battery Using Eutectic Lithium Chemistry

Angewandte Chemie, EarlyView.
A high‐voltage (3.6 V) membrane‐free Li–organic hybrid flow battery is enabled by a deep‐eutectic lithium electrolyte composed of trifluoroacetamide (TFAD) and LiPF6, paired with a dichloromethane (DCM) catholyte containing phenothiazine (PTZ). The TFAD/LiPF6 eutectic provides fast Li+ transport and stable Li‐metal cycling, while the immiscible TFAD ...
Xiao Wang, Bindu Dahal, Yuhang Tang, Jack J. McGrath, Rabin Siwakoti, Feng Wang, Jun Cheng, Jianbing “Jimmy” Jiang   +7 more
wiley   +2 more sources

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Revealing charge anisotropies in metal compounds via high-purity x-ray polarimetry

Physical Review Research
Linear polarization analysis of hard x-rays is employed to probe electronic anisotropies in metal-containing complexes with high selectivity. We use polarization-resolved nuclear forward scattering (PR-NFS) of synchrotron radiation at the 14.4 keV ...
Lena Scherthan, Juliusz A. Wolny, Isabelle Faus, Olaf Leupold, Kai S. Schulze, Sebastian Höfer, Robert Loetzsch, Berit Marx-Glowna, Christopher E. Anson, Annie K. Powell, Ingo Uschmann, Hans-Christian Wille, Gerhard G. Paulus, Volker Schünemann, Ralf Röhlsberger   +14 more
doaj   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Spin-Crossover Complexes

Spin-Crossover Complexes
Spin-crossover (SCO) is a spin-state switching phenomenon between a high-spin (HS) and low-spin (LS) electronic configurations in a transition metal center.
openaire  

"Ammonia Induced Framework Transformations and Spin-Crossover in Fe(II) Hofmann MOFs". [PDF]

Inorg Chem
Pacheco M, Jesuman A, Maqueda-Márquez H, González-Platas J, Gaspar AB.   +4 more
europepmc   +1 more source

4D-Printed Spin Crossover Metamaterials with Giant Programmable Positive or Negative Thermal Expansion. [PDF]

Adv Mater
Trapali A, Zhang Y, Alavi SE, Mawassy N, Zulkarnain R, Molnár G, Salmon L, Bousseksou A.   +7 more
europepmc   +1 more source