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RESEARCH PAPER · Energy storage materials · 2019

Predicting the hydrogen release ability of LiBH 4 -based mixtures by ensemble machine learning

Zhao Ding, Zhiqian Chen, Tianyi Ma, Chang‐Tien Lu, Wenhui Ma, Leon L. Shaw

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Predicting the hydrogen release ability of LiBH 4 -based mixtures by ensemble machine learningOriginalNew insights into the solid-state hydrogen storage of nanostructured LiBH4-MgH2 system279Clean and effective utilization of moldy peel as a biomass waste resource in the gasification process of petroleum coke6Mechanism of hydrogen storage on Fe 3 B27Review of Silicon Recovery and Purification from Saw Silicon Powder69Adsorption characteristics of acid gases (NO, NO2, SO2 and SO3) on different single-atom nickel adsorbent: A first-principles study43Occurrence State and Dissolution Mechanism of Metallic Impurities in Diamond Wire Saw Silicon Powder39A Nanosensor for Naked-Eye Identification and Adsorption of Cadmium Ion Based on Core–Shell Magnetic Nanospheres1Silicon separation and purification process from hypereutectic aluminum-silicon for organosilicon use5Influence of the Grinding Media Applying in the Soft Coal and Waste Biomass on the Carbothermic Reduction Process of Silica7Mechanism study on CO2 reforming of methane over platinum cluster doped graphene: A DFT calculation21Microstructure evolution of precipitates during solidification in metallurgical grade silicon11Hydrogen generation during the purification of metallurgical-grade silicon19Silicon recovery from diamond wire saw silicon powder waste with hydrochloric acid pretreatment: An investigation of Al dissolution behavior88Investigation of Na2CO3–CaO–NaCl (or Na3AlF6) additives for the remanufacturing of silicon from diamond wire saw silicon powder waste43The Effect of Silica and Reducing Agent on the Contents of Impurities in Silicon Produced15Machine learning-based prediction of supercapacitor performance for a novel electrode material: Cerium oxynitride100Silicon recycling and iron, nickel removal from diamond wire saw silicon powder waste: Synergistic chlorination with CaO smelting treatment70Artificial Intelligence Application in Solid State Mg-Based Hydrogen Energy Storage23Study of Controlled Aluminum-Vanadium Alloy Prepared by Vacuum Resistance Furnace7Effect of Silica and Carbon-Reducing Agents on Ni and Ti Impurities during Silicon Production6Construction of transition metal-decorated boron doped twin-graphene for hydrogen storage: A theoretical prediction112Review of resource and recycling of silicon powder from diamond-wire sawing silicon waste63Effect of Carbonaceous Reducers on Carbon Emission during Silicon Production in SAF of 8.5 MVA and 12.5 MVA4Offline and Online Blended Machine Learning for Lithium-Ion Battery Health State Estimation118Photocatalytic H2 evolution by AgNP@PSi/SiNS composite derived from diamond-wire sawing silicon waste12Finite-Element Modelling of Double-Roller Clamping Spinning of Wind Concentrator0Zone melting under vacuum purification method for high-purity aluminum28Novel CrFeCoNiSi6/Si System for Boron Removal from Metallurgical Silicon Feedstock1Study on Si-P-Fe and Si-P-Al ternary System Interactions Applied by MIVM Model for the Process of Specific Actual Production3Improved MgH2 kinetics and cyclic stability by fibrous spherical NiMoO4 and rGO29Formation Mechanism of SiC in the Diffusion Couple Interface during the MG-Si Production Process9A new sustainable concept for silicon recovery from diamond wire saw silicon powder waste: Source control and comprehensive conservation33Prediction of Li-ion battery capacity degradation considering polarization recovery with a hybrid ensemble learning model44Crystal structure, phase transitions, and thermodynamic properties of magnesium metavanadate (MgV2O6)27The effect of Ni on Fe and Al impurities by MIVM model for the silicon production19Predicting the Heat of Hydride Formation by Graph Neural Network ‐ Exploring the Structure–Property Relation for Metal Hydrides23Prediction of Pressure-Composition-Temperature Curves of AB2-Type Hydrogen Storage Alloys by Machine Learning40Recycling the diamond-wire saw silicon powder for preparing the regulable Si3N4 materials by non-catalytic nitridation16Solvothermal Synthesis, Structural Characterization and Optical Properties of Pr-Doped CeO2 and Their Degradation for Acid Orange 714Synthesis of Superparamagnetic Fe3O4 Nano-Adsorbent Using an Energy-Saving and Pollution-Reducing Strategy for the Removal of Xylenol Orange Dye in Water11The use of vacuum refining to separate Ca, Al, and P from crude metallurgical grade silicon18Non-Metal-Doped Porous Carbon Nitride Nanostructures for Photocatalytic Green Hydrogen Production64Paving the Way to the Fuel of the Future—Nanostructured Complex Hydrides17A data-driven interpretable method to predict capacities of metal ion doped TiO 2 anode materials for lithium-ion batteries using machine learning classifiers40A novel lithium decorated N-doped 4,6,8-biphenylene for reversible hydrogen storage: Insights from density functional theory64Machine learning-based high-throughput screening of Mg-containing alloys for hydrogen storage and energy conversion applications41Computational analysis of the hydrogen dispersion in semi-confined spaces46Exploration and design of Mg alloys for hydrogen storage with supervised machine learning73Yield Strength-Plasticity Trade-off and Uncertainty Quantification for Machine-learning-based Design of Refractory High-Entropy Alloys3Recent advances in kinetic and thermodynamic regulation of magnesium hydride for hydrogen storage177Machine learning enabled customization of performance-oriented hydrogen storage materials for fuel cell systems72Multi-output ensemble deep learning: A framework for simultaneous prediction of multiple electrode material properties24Analysis and Evaluation of Migration and Transformation of Impurity Elements and Production Benefits in Silicon Smelting0Removal of Sio2, Al, and Ni from Diamond Wire Saw Silicon Powder Waste: An Investigation of Chlorination Refining with Bacl2·2h2o1Connectionist technique estimates of hydrogen storage capacity on metal hydrides using hybrid GAPSO-LSSVM approach29Phase transitions, lattice dynamics, thermal transport, and thermodynamic properties of Mg2V2O7 from experiments and first-principle calculations19Prediction of Supercapacitor Performance for Cobalt Oxide and Its Derivatives using Machine Learning Techniques0Carbon-based materials for Mg-based solid-state hydrogen storage strategies43Recent Advances in the Preparation Methods of Magnesium-Based Hydrogen Storage Materials50Magnesium-Based Hydrogen Storage Alloys: Advances, Strategies, and Future Outlook for Clean Energy Applications92Advancing integrated high–energy metal–gas batteries5Modification research on the hydrogen storage performance of bimetallic oxide Zn2Ti3O8 on MgH221Unraveling the Potential of Solid-State Hydrogen Storage Materials: Insights from First Principle Calculations57Rare-Earth Metal Trigger Enhanced Generation Kinetics of Lithium Borohydride5Hydrogen storage in Ti doped 4-6-8 biphenylene (Ti.C468): Insights from density functional theory22Crystal Structure Prediction and Performance Assessment of Hydrogen Storage Materials: Insights from Computational Materials Science40Advances in cerium dioxide nanomaterials: Synthesis strategies, property modulation, and multifunctional applications47AI-driven development of high-performance solid-state hydrogen storage42Advancements in sorption-based materials for hydrogen storage and utilization: A comprehensive review101Removal of SiO2, Al, and Ni from diamond wire saw silicon powder waste: An investigation of chlorination refining with BaCl2·2H2O8Advanced Carbon Architectures for Hydrogen Storage: From Synthesis to Performance Enhancement18Engineering LiBH4-Based Materials for Advanced Hydrogen Storage: A Critical Review of Catalysis, Nanoconfinement, and Composite Design20Transition metal-engineered magnesium-based materials for advanced hydrogen storage: From multifaceted mechanisms to state-of-the-art systems15Machine Learning in Solid‐State Hydrogen Storage Materials: Challenges and Perspectives92Accelerating the exploration of novel perovskite-structured metal borohydrides with enhanced dehydrogenation performance through machine learning5Hierarchical interface engineering for advanced magnesium-based hydrogen storage: synergistic effects of structural design and compositional modification132Understanding and engineering rare earth elements in magnesium-based hydrogen storage systems: A multiscale perspective6Enhancing hydrogen storage efficiency in LaNi4.75Al0.25-based metal hydride reactors using advanced machine learning techniques13Materials on the frontier: A review on groundbreaking solutions for hydrogen storage applications26Machine learning descriptor-assisted exploration of metal-modified graphene hydrogen storage materials10Artificial Intelligence‐Driven Innovations in Hydrogen Storage Technology33Economic and effective regeneration of LiBH4 from its direct hydrolytic products using Al-rich alloys3Tailoring Hollow Silica Spheres for Enhanced Hydrogen Adsorption Performance: Role of Synthesis Parameters2Recycling of silicon powder waste and enhancing their purity by the hydrofluoric acid-based leaching process for photovoltaic applications5Interpretable machine learning enables high performance of magnesium borohydride hydrogen storage system11Machine-learning and first-principles investigation of lightweight medium-entropy alloys for hydrogen-storage applications11Implementing machine learning solutions in hydrogen projects0Machine learning-assisted prediction and design of biomass-derived N-doped porous carbon for zinc-ion hybrid capacitors1Generative Adversarial Network-Enhanced Heterogeneous Ensemble Learning for Interpretable Prediction of CO2-to-Methanol Catalyst Performance3Predicting green hydrogen yield and gross energy quantity from water hyacinth images: Deep learning approach0Unraveling the contrasting poisoning mechanisms of AB5- and AB2-type hydrogen storage materials under different impurity gases9Ambient-condition hydrogen storage: Accelerating the development of high-capacity hydrides via a quantitative interpretable machine learning framework6Yield Strength-Plasticity Trade-Off and Uncertainty Quantification for Machine-Learning-Based Design of Refractory High-Entropy Alloys0Recent advances in nanostructure modification to enhance hydrogen storage performance of magnesium-based alloys12A workflow-centric review of artificial intelligence in solid-state hydrogen storage: toward trustworthy AI for materials design0XPEAK: an XRD-driven machine learning platform for predicting the catalyst-enhanced dehydrogenation peak temperature of MgH 28Breaking small sample data barriers: Machine learning prediction of hydrogen storage capacity in Mg-based alloys via data augmentation0Toward intelligent design of solid-state hydrogen storage: trends, challenges, and machine learning insights6Machine learning and non-thermal external fields: A dual-track paradigm for engineering high-performance of Mg-based hydrogen storage materials2Artificial intelligence-driven discovery and design of solid-state hydrogen storage materials8Design and performance modulation of V-based hydrogen storage alloys: a review2Multiscale regulation of thermodynamics and kinetics in high-entropy body-centered cubic type hydrogen storage alloys1Predictive machine learning framework for optimizing hydrogen storage in La–Ni–Al hydrides0Dual‐Metal Co‐Doping Strategy Enhances the Hydrogen Dissociation and Hydrogen Release Performance of LiBH 4 Assisted by Ensemble Learning0Thermodynamic modification of Mg-based hydrogen storage alloys: Strategies, mechanisms, and prospects0Accelerating the discovery of high-capacity solid-state hydrogen storage materials: A predictive machine learning framework0

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