NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for

Neutral geometries optimized with the mPW2PLYP scheme. The Pm–Si bond

HOMO-LUMO gaps (in eV) of LuSin (n = 3–10) calculated at the TPSSh

Size dependences of a atomization energy (AE), b second energy

Two-step machine learning algorithm involving adaptive design (AD).

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

The application of machine learning to air pollution research: A bibliometric analysis - ScienceDirect

The application of machine learning to air pollution research: A bibliometric analysis - ScienceDirect

Automated exploitation of the big configuration space of large adsorbates on transition metals reveals chemistry feasibility

Frontiers Determining the Adsorption Energetics of 2,3-Butanediol on RuO2(110): Coupling First-Principles Calculations With Global Optimizers

Monte Carlo-Simulated Annealing and Machine Learning-Based Funneled Approach for Finding the Global Minimum Structure of Molecular Clusters

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems