Entropy prediction for H2 adsorption in metal-organic frameworks

Complexity Scaling of Liquid Dynamics

According to excess-entropy scaling, dynamic properties of liquids like viscosity and diffusion coefficient are determined by the entropy. This link between dynamics and thermodynamics is increasingly studied and of interest also for industrial applications, but hampered by the challenge of calculating entropy efficiently. Utilizing the fact that entropy is basically the Kolmogorov complexity, which can be estimated from optimal compression algorithms [Avinery et al., Phys. Rev. Lett. 123, 178102 (2019)PRLTAO0031-900710.1103/PhysRevLett.123.178102; Martiniani et al., Phys. Rev. X 9, 011031 (2019)PRXHAE2160-330810.1103/PhysRevX.9.011031], we here demonstrate that the diffusion coefficients of four simple liquids follow a quasiuniversal exponential function of the optimal compression length of a single equilibrium configuration. We conclude that "complexity scaling" has the potential to become a useful tool for estimating dynamic properties of any liquid from a single configuration.

Mg-MOF-74 Derived Defective Framework for Hydrogen Storage at Above-Ambient Temperature Assisted by Pt Catalyst

Metal-organic frameworks (MOFs) are promising candidates for room-temperature hydrogen storage materials after modification, thanks to their ability to chemisorb hydrogen. However, the hydrogen adsorption strength of these modified MOFs remains insufficient to meet the capacity and safety requirements of hydrogen storage systems. To address this challenge, a highly defective framework material known as de-MgMOF is prepared by gently annealing Mg-MOF-74. This material retains some of the crystal properties of the original Mg-MOF-74 and exhibits exceptional hydrogen storage capacity at above-ambient temperatures. The MgO5 knots around linker vacancies in de-MgMOF can adsorb a significant amount of dissociated and nondissociated hydrogen, with adsorption enthalpies ranging from -22.7 to -43.6 kJ mol-1, indicating a strong chemisorption interaction. By leveraging a spillover catalyst of Pt, the material achieves a reversible hydrogen storage capacity of 2.55 wt.% at 160 °C and 81 bar. Additionally, this material offers rapid hydrogen uptake/release, stable cycling, and convenient storage capabilities. A comprehensive techno-economic analysis demonstrates that this material outperforms many other hydrogen storage materials at the system level for on-board applications.

A Step Forward in Understanding the Hydrogen Adsorption and Compression on Activated Carbons

Hydrogen adsorption on activated carbons (ACs) is a promising alternative to compression and liquefaction for storing hydrogen. Herein, we have studied hydrogen adsorption on six commercial ACs (CACs) with surface areas ranging from 996 to 2216 m² g^-1 in a temperature range of 77 to 273 K and pressures up to 15 MPa. Excess hydrogen adsorption capacities of 2.3 to 5.8 wt % were obtained at 77 K and 4 MPa. We demonstrated that, contrary to what is normally done, hydrogen capacity is more accurately predicted by the surface area determined by the nonlocal density functional theory method applied to N₂ and CO₂ adsorption data than by the Brunauer-Emmett-Teller (BET) area. The modified Dubinin-Astakhov (MDA) equation was used to fit the experimental adsorption data, and the relationship between the MDA parameters (n_max, V_a, α, and β) and the textural properties of the CACs was determined for the first time. We concluded that the n_max and V_a parameters are related to the BET area, while the α and β parameters are related to the average micropore size and total pore volume, respectively. α and β were used to evaluate the enthalpy and entropy of adsorption and we show that these parameters can be used to assess the best carbon for hydrogen storage or compression.

Protein Solvent Shell Structure Provides Rapid Analysis of Hydration Dynamics

The solvation layer surrounding a protein is clearly an intrinsic part of protein structure-dynamics-function, and our understanding of how the hydration dynamics influences protein function is emerging. We have recently reported simulations indicating a correlation between regional hydration dynamics and the structure of the solvation layer around different regions of the enzyme Candida antarctica lipase B, wherein the radial distribution function (RDF) was used to calculate the pairwise entropy, providing a link between dynamics (diffusion) and thermodynamics (excess entropy) known as Rosenfeld scaling. Regions with higher RDF values/peaks in the hydration layer (the first peak, within 6 Å of the protein surface) have faster diffusion in the hydration layer. The finding thus hinted at a handle for rapid evaluation of hydration dynamics at different regions on the protein surface in molecular dynamics simulations. Such an approach may move the analysis of hydration dynamics from a specialized venture to routine analysis, enabling an informatics approach to evaluate the role of hydration dynamics in biomolecular function. This paper first confirms that the correlation between regional diffusive dynamics and hydration layer structure (via water center of mass around protein side-chain atom RDF) is observed as a general relationship across a set of proteins. Second, it seeks to devise an approach for rapid analysis of hydration dynamics, determining the minimum amount of information and computational effort required to get a reliable value of hydration dynamics from structural data in MD simulations based on the protein-water RDF. A linear regression model using the integral of the hydration layer in the water-protein RDF was found to provide statistically equivalent apparent diffusion coefficients at the 95% confidence level for a set of 92 regions within five different proteins. In summary, RDF analysis of 10 ns of data after simulation convergence is sufficient to accurately map regions of fast and slow hydration dynamics around a protein surface. Additionally, it is anticipated that a quick look at protein-water RDFs, comparing peak heights, will be useful to provide a qualitative ranking of regions of faster and slower hydration dynamics at the protein surface for rapid analysis when investigating the role of solvent dynamics in protein function.

Perspective: Excess-entropy scaling

This article gives an overview of excess-entropy scaling, the 1977 discovery by Rosenfeld that entropy determines properties of liquids like viscosity, diffusion constant, and heat conductivity. We give examples from computer simulations confirming this intriguing connection between dynamics and thermodynamics, counterexamples, and experimental validations. Recent uses in application-related contexts are reviewed, and theories proposed for the origin of excess-entropy scaling are briefly summarized. It is shown that if two thermodynamic state points of a liquid have the same microscopic dynamics, they must have the same excess entropy. In this case, the potential-energy function exhibits a symmetry termed hidden scale invariance, stating that the ordering of the potential energies of configurations is maintained if these are scaled uniformly to a different density. This property leads to the isomorph theory, which provides a general framework for excess-entropy scaling and illuminates, in particular, why this does not apply rigorously and universally. It remains an open question whether all aspects of excess-entropy scaling and related regularities reflect hidden scale invariance in one form or other.

Determination of Isosteric Heat of Adsorption by Quenched Solid Density Functional Theory

The heat of adsorption is one of the most important parameters characterizing energetic heterogeneity of the adsorbent surface. Heats of adsorption are either determined directly by calorimetry or calculated from adsorption isotherms measured at different temperatures using the thermodynamic Clausius-Clapeyron equation. Here, we present a method for calculating the isosteric heat of adsorption that requires as input only a single adsorption isotherm measured at one temperature. The proposed method is implemented with either nonlocal (NLDFT) or quenched solid (QSDFT) density functional theory models of adsorption that are currently widely used for calculating pore size distributions in various micro- and mesoporous solids. The pore size distribution determined from the same experimental isotherm is used for predicting the isosteric heat. The QSDFT method has advantages of taking into account two factors contributing to the structural heterogeneity of adsorbents: the molecular level roughness of the surface and the pore size distribution. The method is illustrated with examples of low temperature nitrogen and argon adsorption on selected samples of carbons of different degree of graphitization and MCM-41 mesoporous silicas of different pore size. The isosteric heat predictions from the NLDFT and QSDFT methods are compared against relevant experiments and the results of Monte Carlo (MC) simulations, with good agreement found in the cases where the surface model adequately reflects the pore surface roughness. Analyses with the QSDFT method show that the isosteric heat of adsorption significantly depends of the molecular level roughness of the adsorbent surface, which is ignored in NLDFT and MC models. The proposed QSDFT method with further verification can be used for calculating the isosteric heat as an additional parameter characterizing the adsorbent surface in parallel with routine calculations of the pore size distribution from a single adsorption isotherm.