Computational and Experimental Insights into Hydrogen Storage in Metal-Organic Frameworks (MOFs)
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Gas Sorption, GCMC Simulation, Hydrogen Storage
Abstract
The transition to a hydrogen economy is critically dependent on the development of safe and efficient onboard hydrogen storage materials. Metal-Organic Frameworks (MOFs) have emerged as highly promising candidates due to their exceptionally high surface areas and tunable pore environments. This study aimed to combine computational modeling with experimental validation to elucidate the key structural factors governing hydrogen storage capacity in MOFs. A dual approach was employed, using Grand Canonical Monte Carlo (GCMC) simulations to predict hydrogen uptake in a series of MOFs with varying pore sizes and metal centers, followed by experimental synthesis and gas sorption analysis to validate the computational findings. The results revealed a strong correlation between the simulated and experimental data, confirming that both high surface area and optimal pore size (~10-15 Å) are crucial for maximizing physisorption. The GCMC simulations accurately predicted that MOFs with open metal sites exhibit enhanced hydrogen binding energies. This research concludes that a combined computational and experimental approach provides powerful predictive insights, confirming that tailoring pore geometry and introducing strong adsorption sites are key strategies for the rational design of next-generation MOFs for high-density hydrogen storage.
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References
Bagarello, F., Haven, E., & Khrennikov, A. (2017). A model of adaptive decision-making from representation of information environment by quantum fields. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 375(2106). Scopus. https://doi.org/10.1098/rsta.2017.0162
Crease, R. P., & Sares, J. (2021). Interview with physicist Christopher Fuchs. Continental Philosophy Review, 54(4), 541–561. Scopus. https://doi.org/10.1007/s11007-020-09525-6
Earman, J. (2020). Quantum sidelights on The Material Theory of Induction. Studies in History and Philosophy of Science Part A, 82, 9–16. Scopus. https://doi.org/10.1016/j.shpsa.2019.08.002
Fields, C. (2012). If physics is an information science, what is an observer? Information (Switzerland), 3(1), 92–123. Scopus. https://doi.org/10.3390/info3010092
Fields, C. (2013). A whole box of Pandoras: Systems, boundaries and free will in quantum theory 1. Journal of Experimental and Theoretical Artificial Intelligence, 25(3), 291–302. Scopus. https://doi.org/10.1080/0952813X.2013.782981
Friederich, S. (2011). How to spell out the epistemic conception of quantum states. Studies in History and Philosophy of Science Part B - Studies in History and Philosophy of Modern Physics, 42(3), 149–157. Scopus. https://doi.org/10.1016/j.shpsb.2011.01.002
Fuchs, C. A. (2011). Charting the shape of quantum-state space. AIP Conf. Proc., 1363, 305–314. Scopus. https://doi.org/10.1063/1.3630202
Fuchs, C. A., & Schack, R. (2011). A Quantum-Bayesian Route to Quantum-State Space. Foundations of Physics, 41(3), 345–356. Scopus. https://doi.org/10.1007/s10701-009-9404-8
Fuchs, C. A., & Schack, R. (2015). QBism and the Greeks: Why a quantum state does not represent an element of physical reality. Physica Scripta, 90(1). Scopus. https://doi.org/10.1088/0031-8949/90/1/015104
Globus, G. (2017). A quantum brain version of the quantum bayesian solution to the measurement problem. NeuroQuantology, 15(1), 4–9. Scopus. https://doi.org/10.14704/nq.2017.15.1.996
Globus, G. (2018). An existential critique of consciousness solving the existence/brain problem. Mind and Matter, 16(1), 43–52. Scopus.
Haven, E., & Khrennikov, A. (2016). Statistical and subjective interpretations of probability in quantum-like models of cognition and decision making. Journal of Mathematical Psychology, 74, 82–91. Scopus. https://doi.org/10.1016/j.jmp.2016.02.005
Helland, I. S. (2021). Epistemic processes: A basis for statistics and quantum theory: Second edition. Dalam Epistem. Process.: A Basis for Stat. And Quantum Theory: Second Ed. (hlm. 245). Springer International Publishing; Scopus. https://doi.org/10.1007/978-3-030-81923-1
Ichikawa, T. (2025). Bayesianism, Conditional Probability and Laplace Law of Succession in Quantum Mechanics. Foundations of Physics, 55(3). Scopus. https://doi.org/10.1007/s10701-025-00842-5
Khrennikov, A. (2016a). Quantum Bayesianism as the basis of general theory of decision-making. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2068). Scopus. https://doi.org/10.1098/rsta.2015.0245
Khrennikov, A. (2016b). Randomness: Quantum versus classical. International Journal of Quantum Information, 14(4). Scopus. https://doi.org/10.1142/S0219749916400098
Khrennikov, A. (2018). External Observer Reflections on QBism, Its Possible Modifications, and Novel Applications. Dalam Sci. Technol. Eng. Agric. Math. Health. (hlm. 93–118). Springer Nature; Scopus. https://doi.org/10.1007/978-3-319-74971-6_9
Leifer, M. S., & Spekkens, R. W. (2014). A Bayesian approach to compatibility, improvement, and pooling of quantum states. Journal of Physics A: Mathematical and Theoretical, 27. Scopus. https://doi.org/10.1088/1751-8113/47/27/275301
Milgrom, L. R. (2019). Entelechy, Gyroscopes, and QBism: Developing a Quantum Metaphor for the Vital Force. International Journal of High Dilution Research, 18(2), 11–11. Scopus. https://doi.org/10.51910/IJHDR.V18I02.992
Milgrom, L. R. (2022). Some Remarks on QBism and Its Relevance to Metaphors for the Therapeutic Process Based on Conventional Quantum Theory. Complementary Medicine Research, 29(4), 286–296. Scopus. https://doi.org/10.1159/000523815
Milgrom, L. R. (2023). Getting in a Spin over the Therapeutic Process: QBism and a Gyroscopic Model of the Vital Force. Complementary Medicine Research, 30(3), 185–194. Scopus. https://doi.org/10.1159/000527156
Pienaar, J. (2020). Quantum causal models via quantum Bayesianism. Physical Review A, 101(1). Scopus. https://doi.org/10.1103/PhysRevA.101.012104
Pinter, C. (2020). Mind and the cosmic order: How the mind creates the features & structure of all things, and why this insight transforms physics. Dalam Mind and the Cosm. Order: How the Mind Creat. The Features & Struct. Of All Things, and Why this Insight Transform. Phys. (hlm. 176). Springer International Publishing; Scopus. https://doi.org/10.1007/978-3-030-50083-2
Spalvieri, A. (2024). Entropy of the Canonical Occupancy (Macro) State in the Quantum Measurement Theory. Entropy, 26(2). Scopus. https://doi.org/10.3390/e26020107
Sun, C. (2024). On relationship between experiment and theory in basic scientific research. Bulletin of Chinese Academy of Sciences, 39(12), 2016–2026. Scopus. https://doi.org/10.16418/j.issn.1000-3045.20241024005
Zwirn, H. (2016). The Measurement Problem: Decoherence and Convivial Solipsism. Foundations of Physics, 46(6), 635–667. Scopus. https://doi.org/10.1007/s10701-016-9999-5
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Copyright (c) 2025 Ardi Azhar Nampira, Ava Lee, Marcus Tan
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