Electrochemical CO2 or CO reduction to high-value C2+ liquid fuels is desirable, but its practical application is challenged by impurities from cogenerated liquid products and solutes in liquid electrolytes, which necessitates cost- and energy-intensive downstream separation processes. By coupling rational designs in a Cu catalyst and porous solid electrolyte (PSE) reactor, here we demonstrate a direct and continuous generation of pure acetic acid solutions via electrochemical CO reduction. With optimized edge-to-surface ratio, the Cu nanocube catalyst presents an unprecedented acetate performance in neutral pH with other liquid products greatly suppressed, delivering a maximal acetate Faradaic efficiency of 43%, partial current of 200 mA⋅cm−2, ultrahigh relative purity of up to 98 wt%, and excellent stability of over 150 h continuous operation. Density functional theory simulations reveal the role of stepped sites along the cube edge in promoting the acetate pathway. Additionally, a PSE layer, other than a conventional liquid electrolyte, was designed to separate cathode and anode for efficient ion conductions, while not introducing any impurity ions into generated liquid fuels. Pure acetic acid solutions, with concentrations up to 2 wt% (0.33 M), can be continuously produced by employing the acetate-selective Cu catalyst in our PSE reactor.

Understanding the structure–catalytic activity relationship is crucial for developing new catalysts with desired performance. In this contribution, we report the performance of In2O3 with different crystal phases in the reverse water gas shift (RWGS) reaction, where we observe changing activity induced by a phase transition under reaction conditions. Cubic In2O3 (c-In2O3) exhibits a higher RWGS rate than the hexagonal phase (h-In2O3) at temperatures below 350 °C because of its (1) enhanced dissociative adsorption of H2, (2) facile formation of the oxygen vacancies, and (3) enhanced ability to adsorb and activate CO2 on the oxygen vacancies, as suggested both experimentally and computationally. Density functional theory results indicate that the surface oxygen arrangement on the cubic polymorph is key to rapid H2 adsorption, which facilitates oxygen vacancy formation and subsequent CO2 adsorption to yield high RWGS reactivity. At 450 °C and above, the activity of h-In2O3 increases gradually with time on stream, which is caused by a phase transition from h-In2O3 to c-In2O3. In situ X-ray diffraction experiments show that h-In2O3 is first reduced by H2 and subsequently oxidized by CO2 to c-In2O3. These findings highlight the importance of the crystal phase in the catalytic RWGS reaction and provide a new dimension for understanding/designing RWGS catalysts.

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Three-dimensional (3D) covalent organic frameworks (COFs) possess higher surface areas, more abundant pore channels, and lower density compared to their two-dimensional counterparts which makes the development of 3D COFs interesting from a fundamental and practical point of view. However, the construction of highly crystalline 3D COF remains challenging. At the same time, the choice of topologies in 3D COFs is limited by the crystallization problem, the lack of availability of suitable building blocks with appropriate reactivity and symmetries, and the difficulties in crystalline structure determination. Herein, we report two highly crystalline 3D COFs with pto and mhq-z topologies designed by rationally selecting rectangular-planar and trigonal-planar building blocks with appropriate conformational strains. The pto 3D COFs show a large pore size of 46 Å with an extremely low calculated density. The mhq-z net topology is solely constructed from totally face-enclosed organic polyhedra displaying a precise uniform micropore size of 1.0 nm. The 3D COFs show a high CO2 adsorption capacity at room temperature and can potentially serve as promising carbon capture adsorbents. This work expands the choice of accessible 3D COF topologies, enriching the structural versatility of COFs.

Metal/oxide interactions mediated by charge transfer influence reactivity and stability in numerous heterogeneous catalysts. In this work, we use density functional theory (DFT) and statistical learning (SL) to derive models for predicting how the adsorption strength of metal atoms on MgO(100) surfaces can be enhanced by modifications of the support. MgO(100) in its pristine form is relatively unreactive, and thus is ideal for examining ways in which its electronic interactions with metals can be enhanced, tuned, and controlled. We find that the charge transfer characteristics of MgO are readily modified either by adsorbates on the surface (e.g., H, OH, F, and NO 2) or dopants in the oxide lattice (e.g., Li, Na, B, and Al). We use SL methods (i.e., LASSO, Horseshoe prior, and Dirichlet-Laplace prior) that are trained against DFT data to identify physical descriptors for predicting how the adsorption energy of metal atoms will change in response to support modification. These SL-derived feature selection tools are used to screen through more than one million candidate descriptors that are generated from simple chemical properties of the adsorbed metals, MgO, dopants, and adsorbates. Among the tested SL tools, we demonstrate that Dirichlet-Laplace prior predicts metal adsorption energies on MgO most accurately, while also identifying descriptors that are most transferable to chemically similar oxides, such as CaO, BaO, and ZnO.