Login / Signup

Establishing ZIF-8 as a reference material for hydrogen cryoadsorption: An interlaboratory study.

Jose A VillajosRafael Balderas-XicohtencatlAli N Al ShakhsAngel Berenguer-MurciaCraig E BuckleyDiego Cazorla-AmorósGeorgia CharalambopoulouFabrice CouturasFermín CuevasDavid Fairen-JimenezKaren N HeinselmanTerry D HumphriesStefan KaskelHyunlim KimJuan P Marco-LozarHyunchul OhPhilip A ParillaMark PaskeviciusIrena SenkovskaSarah ShuldaJoaquín Silvestre-AlberoTheodore A SteriotisChristos TampaxisMichael HirscherMichael Maiwald
Published in: Chemphyschem : a European journal of chemical physics and physical chemistry (2024)
Hydrogen storage by cryoadsorption on porous materials has the advantages of low material cost, safety, fast kinetics, and high cyclic stability. The further development of this technology requires reliable data on the H 2 uptake of the adsorbents, however, even for activated carbons the values between different laboratories show sometimes large discrepancies. So far no reference material for hydrogen cryoadsorption is available. The metal-organic framework ZIF-8 is an ideal material possessing high thermal, chemical, and mechanical stability that reduces degradation during handling and activation. Here, we distributed ZIF-8 pellets synthesized by extrusion to 9 laboratories equipped with 15 different experimental setups including gravimetric and volumetric analyzers. The gravimetric H 2 uptake of the pellets was measured at 77 K and up to 100 bar showing a high reproducibility between the different laboratories, with a small relative standard deviation of 3-4 % between pressures of 10-100 bar. The effect of operating variables like the amount of sample or analysis temperature was evaluated, remarking the calibration of devices and other correction procedures as the most significant deviation sources. Overall, the reproducible hydrogen cryoadsorption measurements indicate the robustness of the ZIF-8 pellets, which we want to propose as a reference material.
Keyphrases
  • metal organic framework
  • visible light
  • machine learning
  • artificial intelligence
  • neural network