Recent trends in computational tools and data-driven modeling for advanced materials

Abstract

The paradigm of advanced materials has grown exponentially over the last decade, with their new dimensions ranging from digital design, dynamics, and functions. Materials’ modeling such as properties and behavior...

Computational investigations of stable multiple-cage-occupancy He clathrate-like hydrostructures

“…This has enabled the availability of multiple datasets for an incredibly huge number of molecules, which nowadays, with the advancements in machine learning techniques, elicits a revolution in the field. 2,3 The combination of computational methods and data-driven techniques results in reduction of time and cost, and multiple studies have already been reported in assorted areas, such as molecular design [4][5][6][7] and force-field development. 8,9 One of the systems that is in the spotlight for these novel technologies is the clathrate hydrates.…”

Machine Learning-Guided Protein Engineering

“…Many research fields are undergoing a gradual transition from near-exclusive reliance on experimental work to hybrid approaches that incorporate computational simulations and data-driven methods. − In the past, researchers would accumulate observations from individual experiments and use the resulting data to formulate fundamental rules. They then created simulations based on these rules to better understand the system under investigation.…”

From Monofluorophosphates A2PO3F to Difluorophosphates APO2F2 (A = alkali metal): Design of a Potential Deep-Ultraviolet Nonlinear Optical Materials System with a Shortened Phase-Matching Wavelength

“…In this work, to address the above questions, we obtained structural templates for alkali metal monofluorophosphates/difluorophosphates by means of computational design, which has become a powerful tool to accelerate materials discovery with the development of high-performance computing resources and the improved accuracy of the first-principles methods. − A number of thermodynamically stable/metastable alkali metal monofluorophosphate/difluorophosphate structures were designed by both the structural analogy technique and evolutionary algorithms. By high-throughput screening, 34 structures are identified as potential UV/DUV NLO structures, among which 6 dynamically stable difluorophosphates are DUV NLO structures.…”