Photocatalytic degradation mechanismFigure S1 displays the mechanism for the photocatalytic degradation involved in the operation of the TiO 2 /Au/Mg-micromotor. The new micromotors consist of a photoactive TiO 2 surface layer embedded with Au nanoparticles for photodecomposition. Under UV irradiation, the photogenerated positive holes react with adsorbed water and produce strong oxidizing hydroxyl radicals. In addition, the photogenerated free electrons react with adsorbed molecular O 2 to produce superoxide anions that could also contribute to the production of peroxide radicals, hydroxyl radicals, and hydroxyl anions. The complete mineralization of CWAs has been achieved due to coupled oxidation-reduction carried out by the highly active radicals and anions.The presence of the Au nanoparticles can effectively shift the Fermi level of TiO 2 and enhance the charge carrier separation to extend the lifetime of the generated radicals and anions, which results in an enhanced photocatalytic efficiency.

Twelve different equiatomic five-metal carbides of group IVB, VB, and VIB refractory transition metals are synthesized via high-energy ball milling and spark plasma sintering. Implementation of a newly developed ab initio entropy descriptor aids in selection of candidate compositions for synthesis of high entropy and entropy stabilized carbides. Phase formation and composition uniformity are analyzed via XRD, EDS, S/TEM-EDS, and EXAFS. Nine of the twelve candidates form true single-phase materials with the rocksalt (B1) structure when sintered at 2473 K and can therefore be investigated as high entropy carbides (HECs). The composition (V 0.2 Nb 0.2 Ta 0.2 Mo 0.2 W 0.2)C is presented as a likely candidate for further investigation as an entropy stabilized carbide. Seven of the carbides are examined for mechanical properties via nanoindentation. The HECs show significantly enhanced hardness when compared to a rule of mixtures average of the constituent binary carbides and to the highest hardness of the binary constituents. The mechanical properties are correlated to the electronic structure of the solid solutions, offering a future route to tunability of the mechanical properties of carbide ceramics via exploration of a new complex composition space.

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Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications, predicting their formation remains a hindrance for rational discovery of new systems. Experimental approaches are based on physical intuition and/or expensive trial and error strategies. Most computational methods rely on the availability of sufficient experimental data and computational power. Machine learning (ML) applied to materials science can accelerate development and reduce costs. In this study, we propose an ML method, leveraging thermodynamic and compositional attributes of a given material for predicting the synthesizability (i.e., entropy-forming ability) of disordered metal carbides. The relative importance of the thermodynamic and compositional features for the predictions are then explored. The approach's suitability is demonstrated by comparing values calculated with density functional theory to ML predictions. Finally, the model is employed to predict the entropy-forming ability of 70 new compositions; several predictions are validated by additional density functional theory calculations and experimental synthesis, corroborating the effectiveness in exploring vast compositional spaces in a highthroughput manner. Importantly, seven compositions are selected specifically, because they contain all three of the Group VI elements (Cr, Mo, and W), which do not form room temperature-stable rock-salt monocarbides. Incorporating the Group VI elements into the rock-salt structure provides further opportunity for tuning the electronic structure and potentially material performance.