The potential for machine learning in hybrid QM/MM calculations.

Hybrid quantum-mechanics/molecular-mechanics (QM/MM) simulations are popular tools for the simulation of extended atomistic systems, in which the atoms in a core region of interest are treated with a QM calculator and the surrounding atoms are treated with an empirical potential. Recently, a number of atomistic machine-learning (ML) tools have emerged that provide functional forms capable of reproducing the output of more expensive electronic-structure calculations; such ML tools are intriguing candidates for the MM calculator in QM/MM schemes. Here, we suggest that these ML potentials provide several natural advantages when employed in such a scheme. In particular, they may allow for newer, simpler QM/MM frameworks while also avoiding the need for extensive training sets to produce the ML potential. The drawbacks of employing ML potentials in QM/MM schemes are also outlined, which are primarily based on the added complexity to the algorithm of training and re-training ML models. Finally, two simple illustrative examples are provided which show the power of adding a retraining step to such "QM/ML" algorithms.

Oxidation suppression during hydrothermal phase reversion allows synthesis of monolayer semiconducting MoS2 in stable aqueous suspension.

This letter demonstrates a simple method to achieve high-yields of 1H semiconducting MoS2 monolayers in concentrated, colloidally-stable aqueous suspension. The method is based on oxidation suppression during the hydrothermal processing step used for metal-to-semiconductor phase reversion. Accompanying DFT calculations on elementary steps in the MoS2 wet oxidation reaction suggest that a two-site corrosion mechanism is responsible for the observed high reactivity and low stability of 1T metallic MoS2.

Oxygen-induced changes to selectivity-determining steps in electrocatalytic CO2 reduction.

The state of the electrocatalyst surface-including the oxidation state of the catalyst and the presence of spectator species-is investigated on Cu surfaces with density functional theory in order to understand predicted ramifications on the selectivity and efficiency of CO2 reduction. We examined the presence of oxygen-based species, including the fully oxidized Cu2O surface, the partially oxidized Cu(110)-(2 × 1)O surface, and the presence of OH spectators. The relative oxygen binding strength among these surfaces can help to explain the experimentally observed selectivity change between CH4 and CH3OH on these electrodes; this suggests that the oxygen-binding strength may be a key parameter which predicts the thermodynamically preferred selectivity for pathways proceeding through a methoxy (CH3O) intermediate. This study shows the importance of the local surface environment in the product selectivity of electrocatalysis, and suggests a simple descriptor that can aid in the design of improved electrocatalytic materials.

Active and selective conversion of CO2 to CO on ultrathin Au nanowires.

In this communication, we show that ultrathin Au nanowires (NWs) with dominant edge sites on their surface are active and selective for electrochemical reduction of CO2 to CO. We first develop a facile seed-mediated growth method to synthesize these ultrathin (2 nm wide) Au NWs in high yield (95%) by reducing HAuCl4 in the presence of 2 nm Au nanoparticles (NPs). These NWs catalyze CO2 reduction to CO in aqueous 0.5 M KHCO3 at an onset potential of -0.2 V (vs reversible hydrogen electrode). At -0.35 V, the reduction Faradaic efficiency (FE) reaches 94% (mass activity 1.84 A/g Au) and stays at this level for 6 h without any noticeable activity change. Density functional theory (DFT) calculations suggest that the excellent catalytic performance of these Au NWs is attributed both to their high mass density of reactive edge sites (≥16%) and to the weak CO binding on these sites. These ultrathin Au NWs are the most efficient nanocatalyst ever reported for electrochemical reduction of CO2 to CO.

Faster nucleation at lower pH: amorphous phase mediated nucleation kinetics.

Faster nucleation of hydroxyapatite (HAP) at lower pH (with lower supersaturation) contradicts classical understanding. We find that the residue calcium ion in the mother liquor is the key to trigger ACP phase transformation, which gives an understanding of nonclassical nucleation kinetics of ACP-mediated crystallization and sheds light on biomineralization.