Engineering Papers⌕ Search

Engineering topics

Chen, Haoyuan

Publications and source records attributed to Chen, Haoyuan.

8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Avoiding pitfalls in molecular simulation of vapor sorption: Example of propane and isobutane in metal–organic frameworks for adsorption cooling applications

This study introduces recommendations for conducting molecular simulations of vapor adsorption, with an emphasis on enhancing the accuracy, reproducibility, and comparability of results. The first aspect we address is consistency in the implementation of some details of typical molecular models, including tail corrections and cutoff distances, due to their significant influence on generated data. We highlight the importance of explicitly calculating the saturation pressures at relevant temperatures using methods such as Gibbs ensemble Monte Carlo simulations and illustrate some pitfalls in extrapolating saturation pressures using this method. For grand canonical Monte Carlo (GCMC) simulations, the input fugacity is usually calculated using an equation of state, which often requires the critical parameters of the fluid. We show the importance of using critical parameters derived from the simulation with the same model to ensure internal consistency between the simulated explicit adsorbate phase and the implicit bulk phase in GCMC. We show the advantages of presenting isotherms on a relative pressure scale to facilitate easier comparison among models and with experiment. Extending these guidelines to a practical case study, we evaluate the performance of various isoreticular metal–organic frameworks (MOFs) in adsorption cooling applications. This includes examining the advantages of using propane and isobutane as working fluids and identifying MOFs with a superior performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Simulating water adsorption in metal–organic frameworks with open metal sites using the 12-6-4 Lennard–Jones potential

Metal-organic frameworks (MOFs) with coordinatively unsaturated open metal sites (OMSs) are promising sorbent materials in atmospheric water harvesting (AWH) systems at low relative humidity (RH) due to their strong interactions with water molecules. However, accurate computational modelling of water adsorption in those materials are challenging, as standard force fields (FFs) based on the 12-6 Lennard-Jones (L-J) potential cannot properly describe the water-OMS interactions. In biomolecular simulations, the 12-6-4 L-J potential has been successfully used to model metal ion-water interactions in which the extra 1/r 4 -term is for charge-induced dipole electrostatics. In this work, we adopted this strategy and used the 12-6-4 L-J potential to model water-OMS interactions in MOFs for low RH AWH applications. Notably, without any modifications, the parameters used for aqueous metal ions were able to greatly improve the accuracy in predicting water adsorption isotherms in MOF-74, which highlights the simplicity and transferability of this method.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

MOFX-DB: An Online Database of Computational Adsorption Data for Nanoporous Materials

Machine learning and data mining coupled with molecular modeling have become powerful tools for materials discovery. Metal-organic frameworks (MOFs) are a rich area for this due to their modular construction and numerous applications. Here, we make data from several previous large-scale studies in MOFs and zeolites from our groups (and new data for N 2 and Ar adsorption in MOFs) easily accessible in one place. The database includes over 3 million simulated adsorption data points for H 2 , CH 4 , CO 2 , Xe, Kr, Ar, and N 2 in over 160 000 MOFs and zeolites, textural properties like pore sizes and surface areas, and the structure file for each material. We include metadata about the Monte Carlo simulations to enable reproducibility. The database is searchable by MOF properties, and the data are stored in a standardized JSON format that that is interoperable with the NIST adsorption database. We also identify several MOFs that meet high performance targets for multiple applications, such as high storage capacity for both hydrogen and methane or high CO 2 capacity plus good Xe/Kr selectivity. Here, by providing this data publicly, we hope to facilitate machine learning studies on these materials, leading to new insights on adsorption in MOFs and zeolites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine learning using host/guest energy histograms to predict adsorption in metal–organic frameworks: Application to short alkanes and Xe/Kr mixtures

A machine learning (ML) methodology that uses a histogram of interaction energies has been applied to predict gas adsorption in metal–organic frameworks (MOFs) using results from atomistic grand canonical Monte Carlo (GCMC) simulations as training and test data. In this work, the method is first extended to binary mixtures of spherical species, in particular, Xe and Kr. In addition, it is shown that single-component adsorption of ethane and propane can be predicted in good agreement with GCMC simulation using a histogram of the adsorption energies felt by a methyl probe in conjunction with the random forest ML method. Here, the results for propane can be improved by including a small number of MOF textural properties as descriptors. We also discuss the most significant features, which provides physical insight into the most beneficial adsorption energy sites for a given application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Selective Photodimerization in a Cyclodextrin Metal–Organic Framework

For the most part, enzymes contain one active site wherein they catalyze in a serial manner chemical reactions between substrates both efficiently and rapidly. Imagine if a situation could be created within a chiral porous crystal containing trillions of active sites where substrates can reside in vast numbers before being converted in parallel into products. Here, we report how it is possible to incorporate 1-anthracenecarboxylate (1-AC – ) as a substrate into a γ-cyclodextrin-containing metal–organic framework (CD-MOF-1), where the metals are K + cations, prior to carrying out [4+4] photodimerizations between pairs of substrate molecules, affording selectively one of four possible regioisomers. One of the high-yielding regioisomers exhibits optical activity as a result of the presence of an 8:1 ratio of the two enantiomers following separation by high-performance liquid chromatography. The solid-state superstructure of 1-anthracenecarboxylate potassium salt (1-ACK), which is co-crystallized with γ-cyclodextrin, reveals that pairs of substrate molecules are not only packed inside tunnels between spherical cavities present in CD-MOF-1, but also stabilized—in addition to hydrogen-bonding to the C-2 and C-3 hydroxyl groups on the d-glucopyranosyl residues present in the γ-cyclodextrin tori—by combinations of hydrophobic and electrostatic interactions between the carboxyl groups in 1-AC– and four K + cations on the waistline between the two γ-cyclodextrin tori in the tunnels. Here, these non-covalent bonding interactions result in preferred co-conformations that account for the highly regio- and enantioselective [4+4] cycloaddition during photoirradiation. Theoretical calculations, in conjunction with crystallography, support the regio- and stereochemical outcome of the photodimerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗