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RESEARCH PAPER · Journal of the American Chemical Society · 2024

Algorithm-Driven Robotic Discovery of Polyoxometalate-Scaffolding Metal–Organic Frameworks

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Algorithm-Driven Robotic Discovery of Polyoxometalate-Scaffolding Metal–Organic FrameworksOriginalComprehensive overview of machine learning applications in MOFs: from modeling processes to latest applications and design classifications26From synthesis to properties: expanding the horizons of machine learning in nanomaterials research39Roadmap of exploring self-assembly and the self-organization of nanoscale polyoxometalate clusters1Robotic exploration of amino-acid functionalised molybdenum blue polyoxometalate nanoclusters3Experimental and Theoretical Study of Two 3D Difunctional Electrocatalytic Hybrid Vanadate-Containing Metal–Organic Motifs0Artificial Intelligence Meets Laboratory Automation in Discovery and Synthesis of Metal–Organic Frameworks: A Review41Iminodiacetic acid stabilized 3d-4f clusters: Synthesis, structure, and magnetism14A Multiagent-Driven Robotic AI Chemist Enabling Autonomous Chemical Research On Demand167Thermodynamically‐Driven Phase Engineering and Reconstruction Deduction of Medium‐Entropy Prussian Blue Analogue Nanocrystals31Science acceleration and accessibility with self-driving labs83Predict before You Precipitate: Learning Templating Effects in Hybrid Antimony and Bismuth Halides4Modulation of electron transfer properties in two-dimensional nanomaterials for enhanced therapeutic efficacy5Machine Learning Guided Assembly of a Nested Gd 20 @Gd 32 @Ni 36 Cluster via Urea Controlled Carbonate Release7Machine Learning Guided Assembly of a Nested Gd 20 @Gd 32 @Ni 36 Cluster via Urea Controlled Carbonate Release0Data‐Driven Polyoxometalate Chemistry5Assembly of TM−Containing Polyoxotungstates−Based on Metal−Organic frameworks with catalytic oxidation performances for various sulfides0The evolution of MOF discovery for CO2 capture: From high-throughput screening to AI design and automated laboratories9Electrospinning technology combined with MOFs: Bridging the development of high-performance zinc-air batteries7A comprehensive understanding of the use of machine learning in polyoxometalates0Application and prospects of artificial intelligence in condensed matter structural chemistry0Machine learning-guided design principles for single-atom catalysts in persulfate-based advanced oxidation processes1Mapping the crystallization landscape of rare earth MOFs: a high-throughput investigation of structure, kinetics, and selectivity0Functionalized Metal–Organic Frameworks Integrated with Plasmonic Nanoparticles: From Synthesis to Applications6Application of polyoxometalate-based metal-organic framework modified magnetic black phosphorus nanosheets for phosphoproteome analysis0Covalent Functionalization of Dawson-Type Polyoxometalates to Achieve a Zero to Three-Dimensional Transition for Enhanced Proton Conductivity5A “trinity” polyoxometalate-functionalized covalent organic framework (Ru-POCOF) for intelligent heavy metal ions sensing0AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation2From Crystalline Frameworks to Dynamic Networks: Artificial Intelligence-Guided Design of Metal–Organic Materials0A Large Scale Multi‐Modal Workflow for Battery Characterization: From Concept to Implementation0A Light‐Switchable Polyoxometalate “Electron Pump” in a One‐Dimensional Copper Coordination Polymer: Near‐Unity Selective CO 2 Photoreduction to Methane0A Light‐Switchable Polyoxometalate “Electron Pump” in a One‐Dimensional Copper Coordination Polymer: Near‐Unity Selective CO 2 Photoreduction to Methane0Empowering Polymeric Materials Discovery by Artificial Intelligence2AI agents for MOFs and COFs discovery0Polyoxometalates for redox chemistry0

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