We present a quasiparticle self-consistent $GW$ (QSGW) implementation for periodic systems based on crystalline Gaussian basis sets. Our QSGW approach is based on a full-frequency analytic continuation GW scheme with Brillouin zone sampling and employs the Gaussian density fitting technique. We benchmark our QSGW implementation on a set of weakly-correlated semiconductors and insulators as well as strongly correlated transition metal oxides including MnO, FeO, CoO, and NiO. Band gap, band structure, and density of states are evaluated using finite size corrected QSGW. We find that although QSGW systematically overestimates band gaps of tested semiconductors and transition metal oxides, it completely removes the dependence on the choice of density functionals and provides more consistent prediction of spectral properties than $G_0W_0$ across a wide range of solids. This work paves the way for utilizing QSGW in ab initio quantum embedding for solids.
Single iron atoms supported on nitrogen-doped graphene (Fe–N–C) have shown promise in catalyzing electrochemical reduction of CO2 to CO with low overpotential and high selectivity. However, the nature of its rate-limiting step and the effect of active-site environment on catalytic activity are still under debate. Previous theoretical studies exclusively rely on density functional theory (DFT), but their predictions are limited by inherent errors in DFT functionals, leading to diverging conclusions on catalytic mechanisms. Herein, we employ an efficient quantum embedding strategy to enable high-level coupled-cluster (CCSD(T)) simulations of the thermodynamics of Fe–N–C-catalyzed CO2 reduction reaction (CO2RR) and its competing hydrogen evolution reaction. Our calculations accurately predict experimental CO binding energy, onset potential, and potential of maximal Faradaic efficiency (FE) with FeN4 as the catalytic active site. We find that the thermodynamic-limiting step is the formation of a *COOH intermediate at low overpotential, which becomes CO2 adsorption and CO desorption at higher overpotential. Our simulation reveals that the potential-dependent high selectivity of FeN4 originates from the higher charge capacity of *COOH compared to *H. Furthermore, our calculations elucidate distinct roles of active-site environments, including vacancy defect and nitrogen doping. Particularly, graphitic nitrogen doping simultaneously lowers the CO2RR onset potential and allows a wider potential range for high CO FE. This work highlights the importance of robust many-body quantum chemical simulations in achieving quantitative understanding of multistep electrocatalytic reaction mechanisms.
Converting CO2 into fuels and other value-added chemicals via an electrochemical reduction method has recently attracted great interest. However, there are still challenges to find suitable catalysts with high selectivity toward the formic acid formation. Here, we report the bimetallic CuSn-based catalyst to reduce CO2 to formic acid by optimizing the ratio of Cu to Sn to achieve the optimal selectivity. The catalyst is generated on laser-induced graphene. Among the catalysts, CuSn-4 with Cu/Sn atomic ratio close to 1:2 shows a faradaic efficiency of 99% toward formic acid with a high partial current density of 26 mA/cm2. Density functional theory calculations demonstrate that OCHO* intermediate formation is more favorable than that of COOH* on Sn sites, while OCHO* intermediate formation is moderate on Cu sites. The synergetic catalytic effect between Cu and Sn would further favor HCOOH formation. This study provides significant insight into the mechanism of formic acid formation.
The role of additives in facilitating the growth of conventional semiconducting thin films is well-established. Apparently, their presence is also decisive in the growth of two-dimensional transition metal dichalcogenides (TMDs), yet their role remains ambiguous. In this work, we show that the use of sodium bromide enables synthesis of TMD monolayers via a surfactant-mediated growth mechanism, without introducing liquefaction of metal oxide precursors. We discovered that sodium ions provided by sodium bromide chemically passivate edges of growing molybdenum disulfide crystals, relaxing in-plane strains to suppress 3D islanding and promote monolayer growth. To exploit this growth model, molybdenum disulfide monolayers were directly grown into desired patterns using predeposited sodium bromide as a removable template. The surfactant-mediated growth not only extends the families of metal oxide precursors but also offers a way for lithography-free patterning of TMD monolayers on various surfaces to facilitate fabrication of atomically thin electronic devices.
Abstract Thermo-sensitive hydrogel is a smart soft material that undergoes significant volume deformation in response to temperature changes, making it highly applicable in soft smart actuators. However, traditional thermo-sensitive hydrogel bilayer structures are often characterized by slow response rates and limited unidirectional bending capabilities. To overcome these limitations, a new thermo-sensitive hydrogel bilayer structure with faster response and bidirectional deformation is proposed in this work. This structure consists of two active thermo-sensitive hydrogel layers with different thermo-sensitive effect, in which one shrinks and the other swells when the temperature changes. The hydrogels with the fastest temperature response are identified by optimizing the monomer fraction and used to create the bilayer structure. The deformation states of the dual thermo-sensitive hydrogel bilayer structure are controlled by regulating the phase state of the both layers, resulting in different deformation patterns under varied temperature in experiments. We have established a model to describe the deformation of the bilayer structure. Finally, the capability of the bilayer structure to mimic human body movements and the blooming and wilting of flowers is demonstrated. This work reveals the deformation mechanism for a novel dual thermo-sensitive hydrogel bilayer structure, which holds great significance for the advancement of soft smart actuators.
Hydrocarbon conversion to advanced carbon nanomaterials with concurrent hydrogen production holds promise for clean energy technologies. This has been largely enabled by the floating catalyst chemical vapor deposition (FCCVD) growth of carbon nanotubes (CNTs), where commonly catalytic iron nanoparticles are formed from ferrocene decomposition. However, the catalyst formation mechanism and the effect of the chemical environment, especially hydrogen, remain elusive. Here, by employing atomistic simulations, we demonstrate how (i) hydrogen accelerates the ferrocene decomposition and (ii) prevents catalyst encapsulation. A subsequent catalytic dehydrogenation of methane on a liquid Fe nanoparticle showed that carbon dimers tend to be the dominant on-surface species. Such atomistic insights help us better understand the catalyst formation and CNT nucleation in the early stages of the FCCVD growth process and optimize it for potential scaleup.
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