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Various strategies, including controls of morphology, oxidation state, defect, and doping, have been developed to improve the performance of Cu-based catalysts for CO2reduction reaction (CO2RR), generating a large amount of data. However, a unified understanding of underlying mechanism for further optimization is still lacking. In this work, combining first-principles calculations and machine learning (ML) techniques, we elucidate critical factors influencing the catalytic properties, taking Cu-based single atom alloys (SAAs) as examples. Our method relies on high-throughput calculations of 2669 CO adsorption configurations on 43 types of Cu-based SAAs with various surfaces. Extensive ML analyses reveal that low generalized coordination numbers and valence electron number are key features to determine catalytic performance. Applying our ML model with cross-group learning scheme, we demonstrate the model generalizes well between Cu-based SAAs with different alloying elements. Further, electronic structure calculations suggest surface negative center could enhance CO adsorption by back donating electrons to antibonding orbitals of CO. Finally, several SAAs, including PCu, AgCu, GaCu, ZnCu, SnCu, GeCu, InCu, and SiCu, are identified as promising CO2RR catalysts. Our work provides a paradigm for the rational design and fast screening of SAAs for various electrocatalytic reactions.

Osteoclastic inhibition using antiresorptive bisphosphonates and osteogenic promotion using antisclerostin agents represent two distinct osteoporosis treatments in clinical practice, each individual treatment suffers from unsatisfactory therapeutic efficacy due to its indirect intervention in osteoclasis and promotion of osteogenesis simultaneously. Although this issue is anticipated to be resolved by drug synergism, a tempting carrier-free dual-medication nanoassembly remains elusive. Herein, we prepare such a nanoassembly made of antiresorptive alendronate (ALN) crystal and antisclerostin polyaptamer (Apt) via a nucleic acid-driven crystallization method. This nanoparticle can protect Apt from rapid nuclease degradation, avoid the high cytotoxicity of free ALN, and effectively concentrate in the cancellous bone by virtue of the bone-binding ability of DNA and ALN. More importantly, the acid microenvironment of cancellous bone triggers the disassociation of nanoparticles for sustained drug release, from which ALN inhibits the osteoclast-mediated bone resorption while Apt promotes osteogenic differentiation. Our work represents a pioneering demonstration of nucleic acid-driven crystallization of a bisphosphonate into a tempting carrier-free dual-medication nanoassembly. This inaugural advancement augments the antiosteoporosis efficacy through direct inhibition of osteoclasis and promotion of osteogenesis simultaneously and establishes a paradigm for profound understanding of the underlying synergistic antiosteoporosis mechanism of antiresorptive and antisclerostin components. It is envisioned that this study provides a highly generalizable strategy applicable to the tailoring of a diverse array of DNA-inorganic nanocomposites for targeted regulation of intricate pathological niches.