Results 101 to 110 of about 649,054 (286)
Hydrostatic bearings excel in high‐precision applications, but their performance hinges on a continuous external supply. This study evaluates various material combinations for sliding surfaces to mitigate damage during supply failures or misalignment and to discover the most effective materials identified for enhancing the reliability and efficiency of
Michal Michalec +6 more
wiley +1 more source
Open-Source Machine Learning in Computational Chemistry. [PDF]
Hagg A, Kirschner KN.
europepmc +1 more source
Current Applications of Computational Chemistry in JACS—Molecules, Mechanisms, and Materials [PDF]
Weston Thatcher Borden
openalex +1 more source
A Different Perspective on the Solid Lubrication Performance of Black Phosphorus: Friend or Foe?
Researchers investigate black phosphorus (BP) as a standalone solid lubricant coating through ball‐on‐disc linear‐reciprocating sliding experiments in dry conditions. Testing on different metals shows BP doesn't universally reduce friction and wear. However, it achieves 33% friction reduction on rougher iron surfaces and 23% wear reduction on aluminum.
Matteo Vezzelli +5 more
wiley +1 more source
Chemical research projects office: An overview and bibliography, 1975-1980 [PDF]
The activities of the Chemical Research Projects Office at Ames Research Center, Moffett Field, California are reported. The office conducts basic and applied research in the fields of polymer chemistry, computational chemistry, polymer physics, and ...
Heimbuch, A. H. +2 more
core +1 more source
Machine Learning Applied to High Entropy Alloys under Irradiation
Designing alloys for extreme environments demands fast, trustworthy prediction. This review charts how machine learning—especially machine‐learned interatomic potentials and predictive models based on experiment‐informed datasets—captures the complexity of high‐entropy alloys in extreme environments, predicts phase formation, mechanical properties, and
Amin Esfandiarpour +8 more
wiley +1 more source
Linear-Scaling Quantum Circuits for Computational Chemistry. [PDF]
Magoulas I, Evangelista FA.
europepmc +1 more source

