ACS Physical Chemistry Au最新文献

Amorphous solids form an enormous and underutilized class of materials. In order to drive the discovery of new useful amorphous materials further we need to achieve a closer convergence between computational and experimental methods. In this review, we highlight some of the important gaps between computational simulations and experiments, discuss popular state-of-the-art computational techniques such as the Activation Relaxation Technique nouveau (ARTn) and Reverse Monte Carlo (RMC), and introduce more recent advances: machine learning interatomic potentials (MLIPs) and generative machine learning for simulations of amorphous matter (e.g., MAP). Examples are drawn from amorphous silicon and silica literature as well as from molecular glasses. Our outlook stresses the need for new computational methods to extend the time- and length-scales accessible through numerical simulations.

Amorphous solids form an enormous and underutilized class of materials. In order to drive the discovery of new useful amorphous materials further we need to achieve a closer convergence between computational and experimental methods. In this review, we highlight some of the important gaps between computational simulations and experiments, discuss popular state-of-the-art computational techniques such as the Activation Relaxation Technique nouveau (ARTn) and Reverse Monte Carlo (RMC), and introduce more recent advances: machine learning interatomic potentials (MLIPs) and generative machine learning for simulations of amorphous matter (e.g., MAP). Examples are drawn from amorphous silicon and silica literature as well as from molecular glasses. Our outlook stresses the need for new computational methods to extend the time- and length-scales accessible through numerical simulations.

The direct conversion of dinitrogen to nitrate is a dream reaction to combine the Haber–Bosch and Ostwald processes as well as steam reforming using electrochemistry in a single process. Regrettably, the corresponding nitrogen oxidation (NOR) reaction is hampered by a selectivity problem, since the oxygen evolution reaction (OER) is both thermodynamically and kinetically favored in the same potential range. This opens the search for the identification of active and selective NOR catalysts to enable nitrate production under anodic reaction conditions. While theoretical considerations using the computational hydrogen electrode approach have helped in identifying potential material motifs for electrocatalytic reactions over the last decades, the inherent complexity of the NOR, which consists of ten proton-coupled electron transfer steps and thus at least nine intermediate states, poses a challenge for electronic structure theory calculations in the realm of materials screening. To this end, we present a different strategy to capture the competing NOR and OER at the atomic scale. Using a data-driven method, we provide a framework to derive generalized design criteria for materials with selectivity toward NOR. This leads to a significant reduction of the computational costs, since only two free-energy changes need to be evaluated to draw a first conclusion on NOR selectivity.

The direct conversion of dinitrogen to nitrate is a dream reaction to combine the Haber-Bosch and Ostwald processes as well as steam reforming using electrochemistry in a single process. Regrettably, the corresponding nitrogen oxidation (NOR) reaction is hampered by a selectivity problem, since the oxygen evolution reaction (OER) is both thermodynamically and kinetically favored in the same potential range. This opens the search for the identification of active and selective NOR catalysts to enable nitrate production under anodic reaction conditions. While theoretical considerations using the computational hydrogen electrode approach have helped in identifying potential material motifs for electrocatalytic reactions over the last decades, the inherent complexity of the NOR, which consists of ten proton-coupled electron transfer steps and thus at least nine intermediate states, poses a challenge for electronic structure theory calculations in the realm of materials screening. To this end, we present a different strategy to capture the competing NOR and OER at the atomic scale. Using a data-driven method, we provide a framework to derive generalized design criteria for materials with selectivity toward NOR. This leads to a significant reduction of the computational costs, since only two free-energy changes need to be evaluated to draw a first conclusion on NOR selectivity.

The present study elucidated the role of both hydrogen and halogen bonds, from an electronic structure perspective, in the anion recognition process by the [2]catenane (1) containing a moiety with hydrogen bond donors entangled with another macrocyclic halogen bond donor. Spherical and nonspherical anions have been employed. The roles of different σ–hole donors have also been considered. The structure of 1 was modified by incorporating other σ–hole donors, namely bromine, chlorine, fluorine, as well as −Te–CH₃ as a chalcogen bond donor, leading to the modified [2]catenanes 2–5. Insights into anion recognition were gained by quantifying the contributions of not only the mechanical but also hydrogen and halogen/chalcogen bonds to anion recognition using the GKS-EDA energy partition scheme and homodesmostic reactions scheme. GKS-EDA reveals that the anions Cl^– and TS^– exhibit the most stabilizing interactions with the 1 binding pocket. The EDA results confirm that by changing from a stronger σ-hole donor (I) to a weaker σ-hole donor (F) will have a considerable impact on anion interaction, thereby demonstrating that the halogen bonds formed between the [2]catenane and the anion play a pivotal role.

The present study elucidated the role of both hydrogen and halogen bonds, from an electronic structure perspective, in the anion recognition process by the [2]catenane (1) containing a moiety with hydrogen bond donors entangled with another macrocyclic halogen bond donor. Spherical and nonspherical anions have been employed. The roles of different σ-hole donors have also been considered. The structure of 1 was modified by incorporating other σ-hole donors, namely bromine, chlorine, fluorine, as well as -Te-CH₃ as a chalcogen bond donor, leading to the modified [2]catenanes 2-5. Insights into anion recognition were gained by quantifying the contributions of not only the mechanical but also hydrogen and halogen/chalcogen bonds to anion recognition using the GKS-EDA energy partition scheme and homodesmostic reactions scheme. GKS-EDA reveals that the anions Cl^- and TS^- exhibit the most stabilizing interactions with the 1 binding pocket. The EDA results confirm that by changing from a stronger σ-hole donor (I) to a weaker σ-hole donor (F) will have a considerable impact on anion interaction, thereby demonstrating that the halogen bonds formed between the [2]catenane and the anion play a pivotal role.

This study introduces the penta-structured semiconductor p-CGeP₄ through density functional theory simulations, which possesses an indirect band gap transition of 3.20 eV. Mechanical analysis confirms the mechanical stability of p-CGeP₄, satisfying Born–Huang criteria. Notably, p-CGeP₄ has significant direct (e₃₁ = −11.27 and e₃₆ = −5.34 × 10^–10 C/m) and converse (d₃₁ = −18.52 and d₃₆ = −13.18 pm/V) piezoelectric coefficients, surpassing other pentagon-based structures. Under tensile strain, the band gap energy increases to 3.31 eV at 4% strain, then decreases smoothly to 1.97 eV at maximum stretching, representing an ∼38% variation. Under compressive strain, the band gap decreases almost linearly to 2.65 eV at −8% strain and then drops sharply to 0.97 eV, an ∼69% variation. Strongly basic conditions result in a promising band alignment for the new p-CGeP₄ monolayer. This suggests potential photocatalytic behavior across all tensile strain regimes and significant compression levels (ε = 0% to −8%). This study highlights the potential of p-CGeP₄ for groundbreaking applications in nanoelectronic devices and materials engineering.

This study introduces the penta-structured semiconductor p-CGeP₄ through density functional theory simulations, which possesses an indirect band gap transition of 3.20 eV. Mechanical analysis confirms the mechanical stability of p-CGeP₄, satisfying Born-Huang criteria. Notably, p-CGeP₄ has significant direct (e ₃₁ = -11.27 and e ₃₆ = -5.34 × 10^-10 C/m) and converse (d ₃₁ = -18.52 and d ₃₆ = -13.18 pm/V) piezoelectric coefficients, surpassing other pentagon-based structures. Under tensile strain, the band gap energy increases to 3.31 eV at 4% strain, then decreases smoothly to 1.97 eV at maximum stretching, representing an ∼38% variation. Under compressive strain, the band gap decreases almost linearly to 2.65 eV at -8% strain and then drops sharply to 0.97 eV, an ∼69% variation. Strongly basic conditions result in a promising band alignment for the new p-CGeP₄ monolayer. This suggests potential photocatalytic behavior across all tensile strain regimes and significant compression levels (ε = 0% to -8%). This study highlights the potential of p-CGeP₄ for groundbreaking applications in nanoelectronic devices and materials engineering.