Evaluation of Lightning Flash Rate Parameterizations in a Cloud‐Resolved WRF‐Chem Simulation of the 29–30 May 2012 Oklahoma Severe Supercell System Observed During DC3 [PDF]
Kristin A. Cummings +14 more
openalex +1 more source
Advanced Intelligent Discovery, EarlyView.Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar +3 more
wiley +1 more source
A Variational Quantum Eigensolver Based on the Measurement Scheme Tailored to Multiband Tight-Binding Simulations. [PDF]
J Chem Theory ComputLee D, Ryu H.
europepmc +1 more source
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 +5 more
wiley +1 more source
Broadband Terahertz Holography Using Nonlinear Plasmonic Metasurfaces. [PDF]
Nano LettHu Z +4 more
europepmc +1 more source
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
Advanced Intelligent Discovery, EarlyView.We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Electronic Consequences of the Formation of Local Tilting in Halide Perovskites. [PDF]
J Phys Chem LettJung YK, Dubajic M, Stranks SD.
europepmc +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
Advanced Intelligent Discovery, EarlyView.We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
Elucidating the Thermal Properties of Partially Chlorinated Graphene Using Molecular Dynamics Simulations. [PDF]
J Phys Chem C Nanomater InterfacesVarillas J, Kalbáč M.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.We discovered novel materials with giant dielectric constants by combining first‐principles phonon calculations and machine learning. Screening 525 perovskites identified six candidates. RbNbO3 was synthesized under pressure and showed ε ≈ 800–1000. This validates our framework as a powerful tool for high‐performance dielectric materials discovery.
Hiroki Moriwake +9 more
wiley +1 more source