Every reference with a DOI in the deposited reference list resolved to a known
work in Crossref or DataCite at the dated check, and none carried a retraction,
withdrawal, or removal notice.
The 52 checked references that resolve
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resolves10.1039/c0ee00347fHigh density hydrogen storage in superactivated carbons from hydrothermally carbonized renewable organic materials
resolves10.1016/j.jpcs.2009.11.017Preparation and hydrogen storage of activated rayon-based carbon fibers with high specific surface area
resolves10.1016/j.micromeso.2006.12.033Synthesis, characterization and hydrogen storage properties of microporous carbons templated by cation exchanged forms of zeolite Y with propylene and butylene as carbon precursors
resolves10.1016/j.cej.2019.122367Flexible nanoporous activated carbon cloth for achieving high H2, CH4, and CO2 storage capacities and selective CO2/CH4 separation
resolves10.1039/C7EE02616ACigarette butt-derived carbons have ultra-high surface area and unprecedented hydrogen storage capacity
resolves10.1021/acssuschemeng.5b00351Valorization of Lignin Waste: Carbons from Hydrothermal Carbonization of Renewable Lignin as Superior Sorbents for CO<sub>2</sub> and Hydrogen Storage
resolves10.1021/acssuschemeng.9b02734Hierarchically Porous Carbon Derived from <i>Neolamarckia cadamba</i> for Electrochemical Capacitance and Hydrogen Storage
resolves10.1039/C9TA06308KPre-mixed precursors for modulating the porosity of carbons for enhanced hydrogen storage: towards predicting the activation behaviour of carbonaceous matter
resolves10.1021/ja9054838Hydrogen Storage in High Surface Area Carbons: Experimental Demonstration of the Effects of Nitrogen Doping
resolves10.1016/j.jclepro.2020.122915Machine learning exploration of the critical factors for CO2 adsorption capacity on porous carbon materials at different pressures
resolves10.1016/j.ijhydene.2006.08.040Molecular dynamics study of hydrogen adsorption in carbonaceous microporous materials and the effect of oxygen functional groups
resolves10.1021/nl070530uCarbon Nanoscrolls: A Promising Material for Hydrogen Storage
resolves10.1016/j.ijhydene.2020.11.139Grand canonical Monte Carlo simulation on the hydrogen storage behaviors of the cup-stacked carbon nanotubes at room temperature
resolves10.1021/ct300143aPhysisorption, Diffusion, and Chemisorption Pathways of H<sub>2</sub> Molecule on Graphene and on (2,2) Carbon Nanotube by First Principles Calculations
resolves10.1016/j.ijhydene.2020.07.039Molecular and atomic adsorptions of hydrogen, oxygen, and nitrogen on defective carbon nanotubes: A first-principles study
resolves10.1016/j.ijhydene.2019.01.261Machine learning based prediction of metal hydrides for hydrogen storage, part I: Prediction of hydrogen weight percent
resolves10.1021/acs.jpcc.8b09420Attainable Volumetric Targets for Adsorption-Based Hydrogen Storage in Porous Crystals: Molecular Simulation and Machine Learning
resolves10.1039/C8ME00005KA simple constrained machine learning model for predicting high-pressure-hydrogen-compressor materials
resolves10.1016/j.mtla.2019.100366Application of data science tools to determine feature correlation and cluster metal hydrides for hydrogen storage
resolves10.1016/j.aap.2019.105405Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis
resolves10.1016/j.engstruct.2020.110927Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach
resolves10.1007/s10822-020-00314-0Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions
The 11 references without a DOI — listed, not checked
no DOI — not checked10.1016/j.carbon.2021.04.036_bib2
no DOI — not checked10.1016/j.carbon.2021.04.036_bib5
no DOI — not checkedHydrogen storage in CO 2-activated amorphous nanofibers and their monoliths, Carbon N
no DOI — not checkedToward sustainable hydrogen storage and carbon dioxide capture in post-combustion conditions
no DOI — not checked10.1016/j.carbon.2021.04.036_bib21
no DOI — not checked10.1016/j.carbon.2021.04.036_bib54
no DOI — not checkedA unified approach to interpreting model predictions
no DOI — not checked17. A value for n-person games
no DOI — not checked10.1016/j.carbon.2021.04.036_bib60
no DOI — not checked10.1016/j.carbon.2021.04.036_bib61
no DOI — not checked10.1016/j.carbon.2021.04.036_bib62
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