Microbes in marine ecosystems are known to produce secondary metabolites. One of which
are carotenoids, which have numerous industrial applications, hence their demand will …

Inspired by the recent work from Noé and coworkers on the development of machine
learning based implicit solvent model for the simulation of solvated peptides [Chen et al., J …

Classical molecular dynamics is a computer simulation technique that is in widespread use
across many areas of science, from physics and chemistry to materials, biology, and …

Boron neutron capture therapy (BNCT) is a highly targeted, selective and effective technique
to cure various types of cancers, with less harm to the healthy cells. In principle, BNCT …

In this work, we review recent studies in the field of computational solvation. Methods at
different scales from ab initio to force field calculations with both implicit solvent and explicit …

Abstract Integrated Computational Materials Engineering (ICME) has been widely
articulated and pursued over the past decade. Recognition of the need to ensure reliability …

Biotransformation of Fipronil forms three metabolites: fipronil sulfone, fipronil sulfide and
fipronil desulfinyl. Among the triad of metabolites, fipronil sulfone exhibits quantitatively …

Compressive-sensing--based uncertainty quantification methods have become a powerful
tool for problems with limited data. In this work, we use the sliced inverse regression (SIR) …

Compressive sensing has become a powerful addition to uncertainty quantification when
only limited data are available. In this paper, we provide a general framework to enhance …

We report an evaluation of a semi-empirical quantum chemical method PM7 from the
perspective of uncertainty quantification. Specifically, we apply Bound-to-Bound Data …