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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Simplifying computational workflows with the Multiscale Atomic Zeolite Simulation Environment (MAZE)

Zeolites, an important class of 3-dimensional nanoporous materials, have been widely explored for a variety of applications including gas storage, separations, and catalysis. As the properties of these aluminosilicate materials depend on a number of factors (e.g., framework topology, Si/Al ratio, extra-framework cations etc.), detailed experiments (e.g., catalytic properties, adsorption capacities etc.) are often limited to only a handful of materials. Computational methods have played an important role in (1) providing molecular level insights to rationalize experimental observations, and (2) screening large libraries of zeolites to identify promising candidates for experimental synthesis and validation. Different levels of theory and computational chemistry codes are necessary to describe the range of relevant phenomena such as adsorption (e.g., grand canonical Monte Carlo), diffusion (e.g., molecular dynamics), and chemical reactions (e.g., density functional theory). Manipulation of atomic structures, handling of input files, and developing robust workflows becomes quite cumbersome. To mitigate these challenges, we describe the development of the Multiscale Atomic Zeolite Simulation Environment (MAZE) – a Python package that simplifies zeolite-specific calculation workflows by providing a user-friendly interface for systematically manipulating zeolite structures

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Reticular Chemistry for Highly Porous Metal–Organic Frameworks: The Chemistry and Applications

Current global crises related to clean energy and the environment entail the development of materials that are capable of addressing these challenges. Metal–organic frameworks (MOFs), a class of functional materials assembled from metal-containing nodes and organic ligands via coordination bonds, have been successfully developed for various applications, including catalysis, toxic chemical removal, and gas storage and separation, as a result of their highly tailorable nature and precisely engineered pore structures. In particular, the exceptionally high surface areas and porosities of MOFs are two of their most attractive characteristics and place them among the best porous materials for the storage of clean energy gases, such as hydrogen and methane. Reticular chemistry stands out as a prominent approach to the design of MOFs as this strategy allows for the rational top-down design of frameworks guided by topological nets to afford extended framework structures with precise architectural arrangements at the molecular level. Furthermore, bridging the gap between reticular chemistry design strategies and highly porous MOFs can facilitate the development of next-generation high-performance materials through state-of-the-art chemical design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chemically Controllable Porous Polymer–Nanocrystal Composites with Hierarchical Arrangement Show Substrate Transport Selectivity

Functional organic–inorganic hybrid materials with tunable properties are useful across many application areas, ranging from gas storage to electronics, flame retardants, separations, and catalysis. Combining polymers, with a suite of functional groups and conformational flexibility, and inorganic nanoparticles, with tunable surface chemistry and composition, yields hybrids with novel functional properties. Specifically, in catalysis, control of the electronic environment at a metal interface is paramount in determining the catalytic properties. In this contribution, we describe a modular process to prepare porous polymer–nanocrystal (NC) composites in a hierarchical, multilayered synthesis, in which multiple parameters can be accurately tuned: polymer functional groups and the corresponding pore structure, the polymer layer thickness, and the NC size, shape, and composition. This process provides for a variety of controlled materials with high surface area, tunable chemistry, and thermal and chemical stabilities. Furthermore, we demonstrate their utility for shape- and size-selective catalytic conversions both in oxidation and hydrogenation reactions, where they show increased selectivity by orders of magnitude compared to conventional polymer-supported metal catalysts. In light of the high degree of control in the composite structure, this method allows for the design and realization of catalysts for several reactions and reaction environments and for nanomaterials with other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Porous Liquids: Versatile Fusion of Porosity and Fluidity

Porous liquids and fluids with permanent porosity have been explored over the past decade as transformative functional materials for several sustainable chemical processes. This perspective tracks the evolution of porous liquids and summarizes recent advances in the development of porous liquids for several applications, such as sorptive separations, catalysis, etc. Finally, the latter section discusses the prospects of porous liquids in several novel applications (bio applications, gas storage, heat insulation) and machine learning guided pathways for task-specific design and synthesis of porous liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Confinement-Driven Heterogeneous Benzene Crystallization in Silica Nanopores

Nanoconfinement alters the thermodynamics, dynamics, and kinetics of fluids hosted in nanoscale solid nanopores to an extent that depends on the characteristics of the confining space and the chemistry of the confined fluids. Confinement-induced alterations in the phase behavior of confined energetic fluids under high pressure or low temperature are highly relevant to subsurface and subsea phenomena such as fluid flow in porous media, hydrate formation and dissociation, and gas storage capacity. Although extensive efforts have been directed toward understanding the phase behavior of confined fluids, the role of solid-liquid interfaces in the phase transitions of organic liquids has not been resolved yet. Here, we explore the onset and growth of benzene crystallization confined in 6 nm sized SBA-15 silica nanopores in the temperature range 300-200 K using in situ extended range small-angle and wide-angle X-ray scattering (SAXS/WAXS) measurements and atomistic classical molecular dynamics (MD) simulations. The crystallization onset of confined benzene depresses to 265 K compared to the freezing point of bulk benzene ( ~278 K), followed by the continuous growth of the emerged crystals in the pore space with complete crystallization at 200 K. The orientation of the emerged benzene crystals is dominated by parallel (π-π stacking) and perpendicular (T-shape stacking) orientations along the cylindrical pore radius and pore length, respectively. The onset of benzene crystals occurs heterogeneously on the pore surface and grows continuously toward the pore center. Further, confined benzene undergoes a dynamical crossover from fragile to strong dynamics behavior, inferred from the rotational and translational diffusion. The insights provided by this study have significant implications for the phase transitions of confined organic liquids that are relevant to a wide range of applications in the biological, geological, environmental, and chemical fields.

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

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ~ 0.94–0.99) for predicting single-component adsorption capacity in metal–organic frameworks (MOFs). Here, we consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Molecular Structure and Thermodynamics of CO 2 and Water Adsorption on Mica

The adsorption of CO 2 and water on clay surfaces plays a key role in applications, such as gas storage in saline aquifers and depleted hydrocarbon reservoirs, but is not yet fully understood. Here, we study the adsorption of CO 2 and water vapor using Grand Canonical Monte Carlo and molecular dynamics simulations. At a bulk pressure of 100 bar, pure CO 2 adsorbs strongly on mica and forms extensive layers next to it. CO 2 adsorption is lowered substantially if introducing water vapor above mica and is largely eliminated when the relative humidity (RH) approaches about 60%. When pure water vapor is introduced above a mica surface, a subnanometer thick liquid water film develops on it to form apparent liquid–solid and liquid–vapor interfaces simultaneously. Using the identification of truly interfacial molecules (ITIM) analysis, we delineate how individual water layers develop in this film as RH increases. We highlight that the water film is spatially heterogeneous and the true liquid–vapor interface emerges only at an RH of 60–80%. Introducing 100 bar of CO 2 into the water vapor above the mica surface modulates water adsorption nonlinearly: at RH = 0.01%, the water adsorption is reduced by ∼30%; as RH increases, the reduction is weakened, and eventually, enhancement of water adsorption by about 7% occurs at RH = 90%. These variations are attributed to the interplay of film thinning by high-pressure CO 2 , competition of mica surface sites by CO 2 molecules, and energetic and entropic stabilization of interfacial water by CO 2 molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Molecular simulation is an invaluable tool to predict and understand the usage of metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges, commonly obtained from density functional theory (DFT) calculations, are often required to model the electrostatic interactions between the MOF and adsorbates, especially when the adsorbates have dipole or quadrupole moments, such as water and CO 2 . Machine learning (ML) models have been previously employed to predict partial charges and avoid the computational cost associated with DFT calculations. However, previous ML models suffer from small training data sets, which limit their scope of application. In this work, we introduce two novel machine learning models, PACMOF2-neutral and PACMOF2-ionic, aimed at predicting the density-derived electrostatic and chemical (DDEC6) partial atomic charges for both neutral and ionic MOFs. These models not only yield DFT-level accuracy at a fraction of the computational cost but also demonstrate a remarkable improvement in prediction of adsorption, as validated with grand canonical Monte Carlo simulations. Furthermore, the robustness and fast computational time of the PACMOF2 models, along with their transferability to other porous materials such as covalent organic frameworks and zeolites, underscores their potential in high-throughput screening of MOFs for diverse applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-throughput screening of hypothetical metal-organic frameworks for thermal conductivity

Thermal energy management in metal-organic frameworks (MOFs) is an important, yet often neglected, challenge for many adsorption-based applications such as gas storage and separations. Despite its importance, there is insufficient understanding of the structure-property relationships governing thermal transport in MOFs. To provide a data-driven perspective into these relationships, here we perform large-scale computational screening of thermal conductivity k in MOFs, leveraging classical molecular dynamics simulations and 10,194 hypothetical MOFs created using the ToBaCCo 3.0 code. We found that high thermal conductivity in MOFs is favored by high densities (> 1.0 g cm -3 ), small pores (< 10 Å), and four-connected metal nodes. We also found that 36 MOFs exhibit ultra-low thermal conductivity (< 0.02 W m -1 K -1 ), which is primarily due to having extremely large pores (~65 Å). Furthermore, we discovered six hypothetical MOFs with very high thermal conductivity (>10 Wm -1 K -1 ), the structures of which we describe in additional detail.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Computational investigation of hysteresis and phase equilibria of n-alkanes in a metal-organic framework with both micropores and mesopores

Abstract Adsorption hysteresis is a phenomenon related to phase transitions that can impact applications such as gas storage and separations in porous materials. Computational approaches can greatly facilitate the understanding of phase transitions and phase equilibria in porous materials. In this work, adsorption isotherms for methane, ethane, propane, and n-hexane were calculated from atomistic grand canonical Monte Carlo (GCMC) simulations in a metal-organic framework having both micropores and mesopores to better understand hysteresis and phase equilibria between connected pores of different size and the external bulk fluid. At low temperatures, the calculated isotherms exhibit sharp steps accompanied by hysteresis. As a complementary simulation method, canonical (NVT) ensemble simulations with Widom test particle insertions are demonstrated to provide additional information about these systems. The NVT+Widom simulations provide the full van der Waals loop associated with the sharp steps and hysteresis, including the locations of the spinodal points and points within the metastable and unstable regions that are inaccessible to GCMC simulations. The simulations provide molecular-level insight into pore filling and equilibria between high- and low-density states within individual pores. The effect of framework flexibility on adsorption hysteresis is also investigated for methane in IRMOF-1.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A historical overview of the activation and porosity of metal–organic frameworks

Since the first reports of metal–organic frameworks (MOFs), this unique class of crystalline, porous materials has garnered increasing attention in a wide variety of applications such as gas storage and separation, catalysis, enzyme immobilization, drug delivery, water capture, and sensing. A fundamental feature of MOFs is their porosity which provides space on the micro- and meso-scale for confining and exposing their functionalities. Therefore, designing MOFs with high porosity and developing suitable activation methods for preserving and accessing their pore space have been a common theme in MOF research. Reticular chemistry allows for the facile design of MOFs from highly tunable metal nodes and organic linkers in order to realize different pore structures, topologies, and functionalities. With the hope of shedding light on future research endeavors in MOF porosity, it is worthwhile to examine the development of MOFs, with an emphasis on their porosity and how to properly access their pore space. In this review, we will provide an overview of the historic evolution of porosity and activation of MOFs, followed by a synopsis of the strategies to design and preserve permanent porosity in MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Rational design of stable functional metal–organic frameworks

Functional porous metal–organic frameworks (MOFs) have been explored for a number of potential applications in catalysis, chemical sensing, water capture, gas storage, and separation. MOFs are among the most promising candidates to address challenges facing our society related to energy and environment, but the successful implementation of functional porous MOF materials are contingent on their stability; therefore, the rational design of stable MOFs plays an important role towards the development of functional porous MOFs. In this Focus article, we summarize progress in the rational design and synthesis of stable MOFs with controllable pores and functionalities. The implementation of reticular chemistry allows for the rational top-down design of stable porous MOFs with targeted topological networks and pore structures from the pre-selected building blocks. We highlight the reticular synthesis and applications of stable MOFs: (1) MOFs based on high valent metal ions (e.g., Al 3+ , Cr 3+ , Fe 3+ , Ti 4+ and Zr 4+ ) and carboxylate ligands; (2) MOFs based on low valent metal ions (e.g., Ni 2+ , Cu 2+ , and Zn 2+ ) and azolate linkers. We envision that the synthetic strategies, including modulated synthesis and post-synthetic modification, can potentially be extended to other more complex systems like metal-phosphonate framework materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Generative AI for design of nanoporous materials: review and future prospects

Generative artificial intelligence (AI) is emerging as a powerful tool for advancing the design of nanoporous materials such as metal–organic frameworks, covalent–organic frameworks, and zeolites. These materials have potential application in important areas such as carbon capture, catalysis, gas storage, chemical separation, and drug delivery due to their modular, tunable structures, and their performance in these areas depends on precise control over their structure, chemical functionalities, and properties. Herein, we provide a review of generative AI algorithms that are emerging as powerful tools for the design of nanoporous materials, namely generative adversarial networks, variational autoencoders, diffusion models, genetic algorithms, reinforcement learning, and large language models. Some models are particularly good at generating diverse and high-quality designs, while others excel at exploring large design spaces or optimizing materials with desired properties. Certain algorithms also allow for efficient transitions between different designs, and some offer versatility in generating materials based on textual input. We discuss the advantages, limitations, and applications of these algorithms in porous material design and emphasize the future potential of integrating AI with experimental workflows to accelerate the development and validation of AI-generated materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cataloging Legacy Data from the Tritium Systems Test Assembly Program

The Tritium Systems Test Assembly (TSTA) at Los Alamos National Laboratory, operational from 1984 to 2001, was critical in advancing fusion fuel cycle technologies, including tritium storage, gas separation, and pumping. TSTA’s contributions, particularly in safe tritium operations, have influenced subsequent fusion projects. This paper discusses the ongoing effort to digitize and catalog TSTA’s historical data to create a searchable resource for the fusion research community. While the long-term objective is to develop a relational database for structured data management, the project remains in the early phase, with current efforts focused on scanning and indexing physical documents. Initial plans for database implementations are also presented, outlining key considerations for structure, query indexing, and standardization. As digitization progresses, future discussions will refine these implantation details to ensure an efficient and comprehensive system. This initiative aims to preserve critical legacy data, enhance the design of tritium system facilities, and support the next generation of fusion energy research.

42 ENGINEERING↗
DOE OSTI2025

Towards Mitigating Electron Beam-Induced Damage in MOFs Using Low Dose Electron Microscopy for In-Situ Room-Temperature Measurements

Metal-Organic Frameworks (MOFs) have emerged as a versatile class of materials with applications in gas storage and separation, catalysis, and drug delivery [1]. Understanding their damage mechanisms in under various environmental conditions is crucial for optimizing performance and stability [2]. This study employs a combination of Length Structural Coherence (LSC) analysis in electron scattering and Electron Energy Loss Spectroscopy (EELS) to elucidate the damage mechanisms in two representative MOFs. MIL101(Fe), and MIL101(Cr). Here, the primary objective is to reveal structural and chemical changes that occur under electron beam irradiation in Scanning Transmission Electron Microscopy (STEM), both in the pristine state and during in-situ CO and CO 2 adsorption. By combining LSC in Radial Distribution Function (RDF) analysis with EELS, comprehensive insights into the nanoscale alterations are obtained and correlated to the electron dose rate.

dos Santos, Gabriel T. [Northwestern University, E↗
DOE OSTI2025

Investigation of structural and thermal properties of Nb 2 CT X MXenes at elevated temperature

Nb-based MXenes, particularly Nb 2 CT X is noted for its metallic characteristics, and nearly zero band gap because of it 2D structure. Different synthesis processes have been utilized such as HF etching, HCl/LiF and molten salt method to prepare delaminated Nb 2 CT X MXene sheets[1]. Moreover, various approaches have been tried for modifying MXenes properties including partial oxidation for application such as energy storage, gas sensing, photocatalyst etc. One step synthesis technique used for creating efficient hydrogen evolution photocatalyst comprised of Nb 2 O 5 /C/Nb 2 C composites. Furthermore, we have prepared Nb 2 CT X MXenes with a strong etching method and investigated its fundamental properties at elevated temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗