Literature DB >> 24394864

Optimizing nanoporous materials for gas storage.

Cory M Simon1, Jihan Kim, Li-Chiang Lin, Richard L Martin, Maciej Haranczyk, Berend Smit.   

Abstract

In this work, we address the question of which thermodynamic factors determine the deliverable capacity of methane in nanoporous materials. The deliverable capacity is one of the key factors that determines the performance of a material for methane storage in automotive fuel tanks. To obtain insights into how the molecular characteristics of a material are related to the deliverable capacity, we developed several statistical thermodynamic models. The predictions of these models are compared with the classical thermodynamics approach of Bhatia and Myers [Bhatia and Myers, Langmuir, 2005, 22, 1688] and with the results of molecular simulations in which we screen the International Zeolite Association (IZA) structure database and a hypothetical zeolite database of over 100,000 structures. Both the simulations and our models do not support the rule of thumb that, for methane storage, one should aim for an optimal heat of adsorption of 18.8 kJ mol(-1). Instead, our models show that one can identify an optimal heat of adsorption, but that this optimal heat of adsorption depends on the structure of the material and can range from 8 to 23 kJ mol(-1). The different models we have developed are aimed to determine how this optimal heat of adsorption is related to the molecular structure of the material.

Entities:  

Year:  2014        PMID: 24394864     DOI: 10.1039/c3cp55039g

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  10 in total

Review 1.  Big-Data Science in Porous Materials: Materials Genomics and Machine Learning.

Authors:  Kevin Maik Jablonka; Daniele Ongari; Seyed Mohamad Moosavi; Berend Smit
Journal:  Chem Rev       Date:  2020-06-10       Impact factor: 60.622

2.  Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties.

Authors:  Cory M Simon; Efrem Braun; Carlo Carraro; Berend Smit
Journal:  Proc Natl Acad Sci U S A       Date:  2017-01-03       Impact factor: 11.205

3.  Computational Investigation of Correlations in Adsorbate Entropy for Pure-Silica Zeolite Adsorbents.

Authors:  Christopher Rzepa; Daniel W Siderius; Harold W Hatch; Vincent K Shen; Srinivas Rangarajan; Jeetain Mittal
Journal:  J Phys Chem C Nanomater Interfaces       Date:  2020       Impact factor: 4.126

Review 4.  Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation.

Authors:  Cigdem Altintas; Omer Faruk Altundal; Seda Keskin; Ramazan Yildirim
Journal:  J Chem Inf Model       Date:  2021-04-29       Impact factor: 4.956

5.  Quantifying similarity of pore-geometry in nanoporous materials.

Authors:  Yongjin Lee; Senja D Barthel; Paweł Dłotko; S Mohamad Moosavi; Kathryn Hess; Berend Smit
Journal:  Nat Commun       Date:  2017-05-23       Impact factor: 14.919

6.  Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage.

Authors:  Aaron W Thornton; Cory M Simon; Jihan Kim; Ohmin Kwon; Kathryn S Deeg; Kristina Konstas; Steven J Pas; Matthew R Hill; David A Winkler; Maciej Haranczyk; Berend Smit
Journal:  Chem Mater       Date:  2017-03-08       Impact factor: 9.811

Review 7.  Probing Gas Adsorption in Zeolites by Variable-Temperature IR Spectroscopy: An Overview of Current Research.

Authors:  Edoardo Garrone; Montserrat R Delgado; Barbara Bonelli; Carlos O Arean
Journal:  Molecules       Date:  2017-09-15       Impact factor: 4.411

8.  High-Throughput Screening Approach for Nanoporous Materials Genome Using Topological Data Analysis: Application to Zeolites.

Authors:  Yongjin Lee; Senja D Barthel; Paweł Dłotko; Seyed Mohamad Moosavi; Kathryn Hess; Berend Smit
Journal:  J Chem Theory Comput       Date:  2018-07-30       Impact factor: 6.006

9.  Discovery of High-Performing Metal-Organic Frameworks for On-Board Methane Storage and Delivery via LNG-ANG Coupling: High-Throughput Screening, Machine Learning, and Experimental Validation.

Authors:  Seo-Yul Kim; Seungyun Han; Seulchan Lee; Jo Hong Kang; Sunghyun Yoon; Wanje Park; Min Woo Shin; Jinyoung Kim; Yongchul G Chung; Youn-Sang Bae
Journal:  Adv Sci (Weinh)       Date:  2022-05-07       Impact factor: 17.521

10.  Quantitative Structure-Property Relationship Analysis for the Prediction of Propylene Adsorption Capacity in Pure Silicon Zeolites at Various Pressure Levels.

Authors:  Li Zhao; Qi Zhang; Chang He; Qinglin Chen; Bing J Zhang
Journal:  ACS Omega       Date:  2022-09-14
  10 in total

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