Machine-Learning-Accelerated DFT Conformal Sampling of Catalytic Processes.

Computational modeling of catalytic processes at gas/solid interfaces plays an increasingly important role in chemistry, enabling accelerated materials and process optimization and rational design. However, efficiency, accuracy, thoroughness, and throughput must be enhanced to maximize its practical impact. By combining interpolation of DFT energetics via highly accurate Machine-Learning Potentials with conformal techniques for building the training database, we present here an original approach (that we name Conformal Sampling of Catalytic Processes, CSCP), to accelerate and achieve an accurate and thorough sampling of novel systems by exporting existing information on a worked-out case.

Unraveling the Source of Self-Induced Diastereomeric Anisochronism in Chiral Dipeptides.

Mastering of analytical methods for accurate quantitative determinations of enantiomeric excess is a crucial aspect in asymmetric catalysis, chiral synthesis, and pharmaceutical applications. In this context, the phenomenon of Self-Induced Diastereomeric Anisochronism (SIDA) can be exploited in NMR spectroscopy for accurate determinations of enantiomeric composition, without using a chiral auxiliary that could interfere with the spectroscopic investigation. This phenomenon can be particularly useful for improving the quantitative analysis of mixtures with low enantiomeric excesses, where direct integration of signals can be tricky.

Covalent surface modification of single-layer graphene-like BCN nanosheets with reactive nitrenes for selective ammonia sensing via DFT modeling.

Novel graphene-like nanomaterials with a non-zero bandgap are important for the design of gas sensors. The selectivity toward specific targets can be tuned by introducing appropriate functional groups on their surfaces. In this study, we use first-principles simulations, in the form of density functional theory (DFT), to investigate the covalent functionalization of a single-layer graphitized BCN with azides to yield aziridine-functionalized adducts and explore their possible use to realize ammonia sensors.

Combined experimental and computational study of the photoabsorption of the monodoped and nondoped nanoclusters AuPt(SR), AgPt(SR), and Ag(SR).

Assessing the accuracy of first-principles computational approaches is instrumental to predict electronic excitations in metal nanoclusters with quantitative confidence. Here we describe a validation study on the optical response of a set of monolayer-protected clusters (MPC). The photoabsorption spectra of Ag(DMBT), AgPt(DMBT) and AuPt(SCH), where DMBT is 2,4-dimethylbenzenethiolate and SCH is -butylthiolate, have been obtained at low temperature and compared with accurate TDDFT calculations.

Dichroism of plasmonic chiral nanoalloys by rational design.

Time-dependent density functional theory (TDDFT) simulations are conducted on a series of chiral gold/silver alloy nanowires to explore whether silver doping can produce an enhancement of circular dichroism at the plasmon resonance in these systems, and to identify the quantum-mechanical origin of the observed effects. We find a strong plasmonic dichroism when one or two helixes of gold atoms are substituted by silver in a linear chiral nanotube, whose pure gold counterpart does not display any plasmonic dichroism, and we rationalize this finding in terms of "decoupling" the destructive interference of excitations in the pure gold nanotube via alloying. However, further attempts to increase the plasmonic dichroism by considering multi-shell gold nanowires in which one entire shell is doped with silver did not produce the desired effect, but rather a decrease in circular dichroism.