The development of force-responsive molecules called mechanophores is a central
component of the field of polymer mechanochemistry. Mechanophores enable the design and …

Creating fast and accurate force fields is a long-standing challenge in computational
chemistry and materials science. Recently, Equivariant Message Passing Neural Networks (MPNNs…

Due to obvious disadvantages of the classical chemical methods, green synthesis of
metallic nanoparticles has attracted tremendous attention in recent years. Numerous …

Membrane bioreactors (MBRs) have proven to be an extremely effective wastewater treatment
process combining ultrafiltration with biological processes to produce high-quality effluent…

Loss of function of the tumour suppressor p53 observed frequently in human cancers challenges
the drug-induced apoptotic elimination of cancer cells from the body. This phenomenon …

We demonstrate that fast and accurate linear force fields can be built for molecules using
the atomic cluster expansion (ACE) framework. The ACE models parametrize the potential …

A series of laboratory tests were conducted to evaluate whether denitrification would be a
suitable alternative for biorestoration of an aquifer contaminated with JP-4 jet fuel. Microcosms …

As an emerging new class, metal nanoparticles and especially silver nanoparticles hold great
potential in the field of cancer biology. Due to cancer-specific targeting, the consequently …

The rapid progress of machine learning interatomic potentials over the past couple of years
produced a number of new architectures. Particularly notable among these are the Atomic …

The MACE architecture represents the state of the art in the field of machine learning force
fields for a variety of in-domain, extrapolation, and low-data regime tasks. In this paper, we …