Results 141 to 150 of about 61,302 (288)

Glycine‐Induced Unique Crystal Packing of Octacyanidetungstates With Strong Intermolecular Antiferromagnetic Interaction, Near‐Infrared Emission, and Second Harmonic Generation

Angewandte Chemie, EarlyView.
Glycine molecules induce a unique crystal packing into a supramolecular one‐dimensional columnar structure of octacyanidotungstates, which exhibits exceptionally strong antiferromagnetic superexchange interactions of J = −42.41(2) K between adjacent octacyanidotungstate units.
Tatsuya Konishi, Koji Nakabayashi, Kunal Kumar, Takeshi Suzuki, Kozo Okazaki, Masataka Kobayashi, Hidefumi Akiyama, Kouji Chiba, Shin‐ichi Ohkoshi   +8 more
wiley   +2 more sources

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +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

Polarization Control via Artificial Optical Nonlinearity in Dielectric Metasurfaces. [PDF]

ACS Nano
Yue F, Balistreri G, Montaut N, Riminucci F, Toma A, Piccoli R, Cabrini S, Morandotti R, Razzari L.   +8 more
europepmc   +1 more source

Achieving Maximum Chirality and Enhancing Third-Harmonic Generation via Quasi-Bound States in the Continuum in Nonlinear Metasurfaces. [PDF]

Nanomaterials (Basel)
Li D, Liu Y, Liang K, Yu L.
europepmc   +1 more source

Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches

Advanced Physics Research, EarlyView.
Two methods for the optimization of chiral reflection by a metamaterial made of either GaP/Air or PMMA/Air interfaces are compared, showing approaches towards fast design exploration and high‐performance results: a neural‐network pipeline and a genetic algorithm. The structures considered are characterized by a periodic, chiral texturation with a shape
Davide Filippozzi, Alexandre Mayer, Nicolas Roy, Wei Fang, Arash Rahimi‐Iman   +4 more
wiley   +1 more source

Bridging Molecular and Bulk Nonlinearities: Kerr Effect Phenomena in Transparent Ceramic Systems. [PDF]

Int J Mol Sci
Kruk A, Schabikowski M.
europepmc   +1 more source

Spin Dynamics of Excitons and Carriers in Mixed‐Cation MAxFA1–xPbI3 Perovskite Crystals: Alloy Fluctuations Probed by Optical Orientation

Advanced Physics Research, EarlyView.
The impact of alloy fluctuations on the spin dynamics of mixed‐cation MAxFA1‐xPbI3 perovskite single crystals is studied experimentally by means of polarized time‐resolved photoluminescence. The high optical orientation degree, reaching 80% for x = 0.1 and 0.8, displays a minimum of 60% for x = 0.4.
Boris F. Gribakin, Nataliia E. Kopteva, Dmitri R. Yakovlev, Ilya A. Akimov, Ina V. Kalitukha, Bekir Turedi, Maksym V. Kovalenko, Manfred Bayer   +7 more
wiley   +1 more source