Carbon nanostructures formed through physical synthesis come in a variety of sizes and shapes. With the end goal of rationalizing synthetic pathways of carbon nanostructures as a function of tunable parameters in the synthesis, we investigate how the initi ...
We mine from the literature experimental data on the CO2 electrochemical reduction selectivity of Cu single crystal surfaces. We then probe the accuracy of a machine learning model trained to predict faradaic efficiencies for 11 CO2 reduction reaction prod ...
Atomic simulations using machine learning interatomic potential (MLIP) have gained a lot of popularity owing to their accuracy in comparison to conventional empirical potentials. However, the transferability of MLIP to systems outside the training set pose ...
In committee of experts strategies, small datasets are extracted from a larger one and utilised for the training of multiple models. These models' predictions are then carefully weighted so as to obtain estimates which are dominated by the model(s) that ar ...
Li-S batteries are a promising alternative to Li-ion batteries, offering large energy storage capacity and wide operating temperature range. However, their performance is heavily affected by the Li-polysulfide (LiPS) shuttling. Computational screening of L ...
A non-trivial interplay rules the relationship between the structure and the chemophysical properties of a nanoparticle. In this context, characterization experiments, molecular dynamics simulations and electronic structure calculations may allow the varia ...
The focus of this short review is directed towards investigations of the dynamics of nanostructured metallic heterogeneous catalysts and the evolution of interfaces during reaction-namely, the metal-gas, metal-liquid, and metal-support interfaces. Indeed, ...
We show that, contrary to popular assumptions, predictions from machine learning potentials built upon highdimensional atom-density representations almost exclusively occur in regions of the representation space which lie outside the convex hull defined by ...
Colloidal atomic layer deposition (c-ALD) enables the growth of hybrid organic/inorganic oxide shells with tunable thickness at the nanometer scale around ligand-functionalized inorganic nanoparticles (NPs). This recently developed method has demonstrated ...
