Search NASA⌕ Search

SEARCH · Search NASA

Results for “design theory and methodology”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Activity Theory Literature Review

Complex challenges across Sandia National Laboratories' (SNL) mission areas underscore the need for systems level thinking, resulting in a better understanding of the organizational work systems and environments in which our hardware and software will be used. SNL researchers have successfully used Activity Theory (AT) as a framework to clarify work systems, informing product design, delivery, acceptance, and use. To increase familiarity with AT, a working group assembled to select key resources on the topic and generate an annotated bibliography. The resources in this bibliography are arranged in six categories: 1) An introduction to AT; 2) Advanced readings in AT; 3) AT and human computer interaction (HCI); 4) Methodological resources for practitioners; 5) Case studies; and 6) Related frameworks that have been used to study work systems. This annotated bibliography is expected to improve the reader's understanding of AT and enable more efficient and effective application of it.

42 ENGINEERING↗
DOE OSTI2022

Density reconstruction in convergent high-energy-density systems using x-ray radiography and Bayesian inference

X-ray radiography is a technique frequently used to diagnose convergent high-energy-density (HED) systems, such as inertial confinement fusion implosion, and provides unique information that is not available through self-emission measurements. In this work, we investigate the scope and limits of that information using a radiography simulation combined with the Bayesian inference workflow. The accuracy of density reconstruction from simulated radiographs of spherical implosions driven with 27 kJ laser energy is assessed, including the increase or decrease in accuracy due to the addition of Lagrangian marker layers, Poisson noise, and improved prior information. This work is the first to present the full uncertainty distributions inferred from radiography analysis in HED systems and demonstrates the importance of constructing the full posterior probability density, as opposed to a point estimate, due to the modal structure of the likelihood surface introduced by typical experimental noise sources. This general methodology can be used both for robust analysis of radiographic data and for an improved design of radiography experiments by modeling the full experimental system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Semi-empirical quantum optics for mid-infrared molecular nanophotonics

Nanoscale infrared (IR) resonators with sub-diffraction limited mode volumes and open geometries have emerged as new platforms for implementing cavity quantum electrodynamics at room temperature. The use of IR nanoantennas and tip nanoprobes to study strong light–matter coupling of molecular vibrations with the vacuum field can be exploited for IR quantum control with nanometer spatial and femtosecond temporal resolution. In order to advance the development of molecule-based quantum nanophotonics in the mid-IR, we propose a generally applicable semi-empirical methodology based on quantum optics to describe light–matter interaction in systems driven by mid-IR femtosecond laser pulses. The theory is shown to reproduce recent experiments on the acceleration of the vibrational relaxation rate in infrared nanostructures. It also provides physical insights on the implementation of coherent phase rotations of the near-field using broadband nanotips. We then apply the quantum framework to develop general tip-design rules for the experimental manipulation of vibrational strong coupling and Fano interference effects in open infrared resonators. We finally propose the possibility of transferring the natural anharmonicity of molecular vibrational levels to the resonator near-field in the weak coupling regime to implement intensity-dependent phase shifts of the coupled system response with strong pulses and develop a vibrational chirping model to understand the effect. The semi-empirical quantum theory is equivalent to first-principles techniques based on Maxwell’s equations, but its lower computational cost suggests its use as a rapid design tool for the development of strongly coupled infrared nanophotonic hardware for applications ranging from quantum control of materials to quantum information processing.

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

Using interfaces to: create strongly-coupled magnetic-ferroelectrics

Starting at the level of electrons and atoms our long-term goal is to rationally design complex oxide heterostructures and interface-materials with targeted emergent behaviors. This is not a matter of simply optimizing material parameters, but rather begins with understanding a mechanism to control the interplay between the diverse microscopic degrees of freedom prevalent in complex oxides in order to create targeted macroscopic phenomena and ends with the design of new material realizations. These realizations are in turn created with atomic-layer precision, structurally assessed to see that they are the intended realization, and finally their relevant properties are measured. During this program we have developed the scientific ideas necessary to apply this materials-by-design paradigm to the creation of materials offering electrical control of magnetism. At the heart of our approach lies a partnership between theory, synthesis, and characterization. These are the areas of expertise of the three co-PIs, who have worked closely together since their arrival at Cornell. During this project bold ideas on where to put the atoms to provide electrical control of magnetism were met with the latest methods of synthesis science and electron microscopy in an attempt create targeted new multiferroics. Our work applying this materials-by-design methodology to multiferroics has enjoyed multiple successes. The Co-PIs have invented new mechanisms for multiferroics, which provide strong coupling between polarization and magnetism, and reduced them to practice. Specifically, we pioneered multiferroics based on spin-phonon coupling, rotation-driven multiferroicity, and novel geometric multiferroics. Importantly, the latter two of these mechanisms enable the deterministic switching of magnetism by an applied electric field, which is key to the application of multiferroics to future device technologies. Most recently, we performed detailed theoretical analysis on a system involving the combination of magnetoelectric and colossal magnetoresistance behaviors and predict that electrical control of a metal-insulator transition is possible in appropriately strained SmBaMn2O6. The research enabled by this grant led to 63 publications in leading refereed journals including Nature, Nature Materials, Physical Review Letters, and Advanced Materials demonstrating a materials-by-design paradigm to the creation of materials offering electrical control of magnetism.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Demonstrate Capability of NEAMS Tools to Generate Reactor Kinetics Parameters for Pebble-Bed HTGRs Transient Modeling

The system analysis of anticipated operating occurrences and design basis accident for pebblebed reactor systems requires knowledge of the neutron kinetic parameters. These parameters take into account various types of feedback from the pebble-bed core and are typically integrated into system analysis tools such as the System Analysis Module (SAM) in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) tool package. These parameters are typically generated by a higher fidelity full-core coupled neutronics/thermal fluids analysis, such as using Griffin and Pronghorn, in 2D or 3D. The delayed neutron fractions (beta) and the neutron lifetimes (lambda) are typically generated by applying the adjoint solution of the neutron flux. Temperature reactivity coefficients are the most important feedback for all anticipated operating occurrences and design basis accident, then depending on the transient other effects might be important as rector control system worth, s-curves, and Xenon generation. This work package will establish a methodology and process for calculating the reactor kinetics parameters for high-temperature gas-cooled reactor and provide them in a suitable form for system level analyses of typical anticipated operating occurrences and design basis accident.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Uncertainty Quantification in Atomistic Modeling of Metals and Its Effect on Mesoscale and Continuum Modeling: A Review

The design of next-generation alloys through the integrated computational materials engineering (ICME) approach relies on multiscale computer simulations to provide thermodynamic properties when experiments are difficult to conduct. Atomistic methods such as density functional theory (DFT) and molecular dynamics (MD) have been successful in predicting properties of never before studied compounds or phases. However, uncertainty quantification (UQ) of DFT and MD results is rarely reported due to computational and UQ methodology challenges. Over the past decade, studies that mitigate this gap have emerged. These advances are reviewed in the context of thermodynamic modeling and information exchange with mesoscale methods such as the phase-field method (PFM) and calculation of phase diagrams (CALPHAD). The importance of UQ is illustrated using properties of metals, with aluminum as an example, and highlighting deterministic, frequentist, and Bayesian methodologies. Finally, challenges facing routine uncertainty quantification and an outlook on addressing them are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2024

2D Metal/Graphene and 2D Metal/Graphene/Metal Systems for Electrocatalytic Conversion of CO 2 to Formic Acid

Efficiently transforming CO 2 into renewable energy sources is crucial for decarbonization efforts. Formic acid (HCOOH) holds great promise as a hydrogen storage compound due to its high hydrogen density, non-toxicity, and stability under ambient conditions. However, the electrochemical reduction of CO 2 (CO 2 RR) on conventional carbon black-supported metal catalysts faces challenges such as low stability through dissolution and agglomeration, as well as suffering from high overpotentials and the necessity to overcome the competitive hydrogen evolution reaction (HER). In this study, we modify the physical/chemical properties of metal surfaces by depositing metal monolayers on graphene (M/G) to create highly active and stable electrocatalysts. Strong covalent bonding between graphene and metal is induced by the hybridization of sp and d orbitals, especially the sharp $d_{z^2}$, $d_{yz}$, $d_{xz}$ orbitals of metals near the Fermi level, playing a decisive role. Moreover, charge polarization on graphene in M/G enables the deposition of another thin metallic film, forming metal/graphene/metal (M/G/M) structures. Finally, evaluating overpotentials required for CO 2 reduction to HCOOH, CO, and HER, we find that Pd/G, Pt/G/Ag, and Pt/G/Au exhibit excellent activity and selectivity toward HCOOH production. Our novel 2D hybrid catalyst design methodology may offer insights into enhanced electrochemical reactions through the electronic mixing of metal and other p-block elements.

2D Electrocatalysts↗
DOE OSTI2023

Active Learning Guided Computational Discovery of Plant-Based Redoxmers for Organic Nonaqueous Redox Flow Batteries

Organic nonaqueous redox flow batteries (ONRFBs) are promising energy storage devices due to their scalability and reliance on sourceable materials. However, finding suitable redox-active organic molecules (redoxmers) for these batteries remains a challenge. Using plant-based compounds as precursors for these redoxmers can decrease their costs and environmental toxicity. In this computational study, flavonoid molecules have been examined as potential redoxmers for ONRFBs. Flavone and isoflavone derivatives were selected as catholyte (positive charge carrier) and anolyte (negative charge carrier) molecules, respectively. To drive their redox potentials to the opposite extremes, in silico derivatization was performed using a novel algorithm to generate a library of > 40000 candidate molecules that penalizes overly complex structures. A multiobjective Bayesian optimization based active learning algorithm was then used to identify best redoxmer candidates in these search spaces. Furthermore, our study provides methodologies for molecular design and optimization of natural scaffolds and highlights the need of incorporating expert chemistry awareness of the natural products and the basic rules of synthetic chemistry in machine learning.

25 ENERGY STORAGE↗
DOE OSTI2023

Developing and applying quantifiable metrics for diagnostic and experiment design on Z

This project applies methods in Bayesian inference and modern statistical methods to quantify the value of new experimental data, in the form of new or modified diagnostic configurations and/or experiment designs. We demonstrate experiment design methods that can be used to identify the highest priority diagnostic improvements or experimental data to obtain in order to reduce uncertainties on critical inferred experimental quantities and select the best course of action to distinguish between competing physical models. Bayesian statistics and information theory provide the foundation for developing the necessary metrics, using two high impact experimental platforms on Z as exemplars to develop and illustrate the technique. We emphasize that the general methodology is extensible to new diagnostics (provided synthetic models are available), as well as additional platforms. We also discuss initial scoping of additional applications that began development in the last year of this LDRD.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A general strategy for preparing pyrrolic-N 4 type single-atom catalysts via pre-located isolated atoms

Single-atom catalysts (SACs) have been applied in many fields due to their superior catalytic performance. Because of the unique properties of the single-atom-site, using the single atoms as catalysts to synthesize SACs is promising. In this work, we have successfully achieved Co 1 SAC using Pt 1 atoms as catalysts. More importantly, this synthesis strategy can be extended to achieve Fe and Ni SACs as well. X-ray absorption spectroscopy (XAS) results demonstrate that the achieved Fe, Co, and Ni SACs are in a M1-pyrrolic N 4 (M= Fe, Co, and Ni) structure. Density functional theory (DFT) studies show that the Co(Cp) 2 dissociation is enhanced by Pt 1 atoms, thus leading to the formation of Co 1 atoms instead of nanoparticles. These SACs are also evaluated under hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), and the nature of active sites under HER are unveiled by the operando XAS studies. These new findings extend the application fields of SACs to catalytic fabrication methodology, which is promising for the rational design of advanced SACs.

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

Controlling Structural, Electronic, and Energy Flow Dynamics of Catalytic Processes through Tailored Nanostructures

MoS 2 (molybdenum disulfide) is a highly-versatile catalyst material for support of numerous reactions from hydrodesulfurization and denitrogenation to the focus of this renewal proposal: hydrogenation of CO/CO 2 towards (higher) alcohols. At the same time, MoS 2 is a non-toxic, environmentally-benign and rather inert material- which under ambient conditions for some time has served as a lubricant and, more recently, as next-generation electronic material. The apparent contrast between inertness and stability in ambient, and catalytic activity under reactive conditions is puzzling and calls for a synergistic theoretical and experimental investigation with the long-term objective of enabling the rational design of MoS 2 -based catalysts for alcohol-formation reactions by providing a microscopic understanding of the environmental factors that determines site activity and selectivity. Our research project seeks answers to the questions (a) what conformation does MoS 2 adopt under reaction conditions (as opposed to that under ultrahigh vacuum and low temperatures)?; (b) what reaction pathways exist on such a material?; (c) how can the local environment of the active sites be manipulated so as to make MoS 2 an efficient catalyst for production of higher alcohol from syngas? In particular, research strategies will explore how the basal plane composed of sulfur atoms can be activated so as to exhibit a reactivity of its own, by addressing three research targets and building on extensive preliminary and enabling work: (1) vacancies and vacancy aggregates on the basal plane; (2) non-local catalyst transformation through alkali doping, hydrogenation and phase transition; (3) fabrication of a metal-nanoparticle-activated MoS 2 system, in which particle anchoring, reactive sites and pathways as well as selectivity are controlled by design, as an example of predictive development of a catalyst material,. All strategies are directed to improve the efficacy of the key reactive sites and selectivity of chemical pathways by design, to replace the inefficient methodology of trial and error in catalyst development. This research project represents a synergistic combination of computational guidance, foundational surface-science-based experiments and validation under reactive conditions that aims at transformative new insights into the working of MoS 2 -based hydrogenation-catalysts, a topic squarely at the center of the interest of DOE BES. Guided and led by Talat Rahman, a computational physicist, this project will apply density functional theory to understand structure, reaction pathways and chemical potentials associated with MoS 2 -based CO/CO 2 hydrogenation, augmented by kinetic Monte Carlo methods for reaction rates and prefactors as well as ab-initio molecular dynamics for evaluation of thermal stability. Complementary experimental input and validation will originate from co-PI Ludwig Bartels, a physical chemist and materials scientist, whose group focuses on local imaging and preparation of MoS 2 materials, from co-PI Peter Dowben, an experimental physicist, whose group is expert in the spectroscopy of occupied and unoccupied electronic states, and from senior collaborator Michael White of Brookhaven National Laboratory, whose group generates high-resolution electronic and activity information on size-selected well-defined metal chalcogenide clusters. This collaborative effort will enable a comprehensive understanding of the correlation of structural integrity and catalytic activity of MoS 2 in forms ranging from extended films to individual particles with known geometries and binding sites. Alcohol formation from syngas is a rapidly emerging application that has great potential through facile, economic, and decentralized biomass gasification. CO 2 activation is one of the most pressing concerns of our time: increasing CO 2 levels in the atmosphere change the climate and expose the globe to environmental transformations with the potential for enormous economic and societal impact. We will investigate CO/CO 2 hydrogenation via an interdisciplinary research collaboration with established synergy – one that, in accordance with the mission of the DOE, involves accredited Hispanic-Serving Institutions and that, through student exchange with international collaborators and National Labs, will directly benefit a broad spectrum of communities and generate human resources in sciences essential to their future.

2D materials↗
DOE OSTI2020

Graph Theory and IC Component Design Analysis

Graph analysis in large integrated circuit (IC) designs is an essential tool for verifying design logic and timing via dynamic timing analysis (DTA). IC designs resemble graphs with each logic gate as a vertex and the conductive connections between gates as edges. Using DTA digital statistical correlations, graph condensation, and graph partitioning, it is possible to identify high-entropy component centers and paths within an IC design. Identification of high-entropy component centers (HECC) enables focused DTA, effectively lowering the computational complexity of DTA on large integrated circuit graphs. In this paper, a devised methodology termed IC layout subgraph component center identification (CCI) is used to identify described. CCI lowers DTA computationally complexity by condensing IC graphs into reduced subgraphs in which dominant logic functions are verified.

42 ENGINEERING↗
DOE OSTI2024

From minimum-viable-products to full models: a step-wise development of diagnostic forward models in support of design, analysis and modelling on the ST40 tokamak

Like most magnetic confined fusion experiments, the ST40 tokamak started off with a small subset of diagnostics and gradually increased the diagnostic set to include more complex and comprehensive systems. To make the most of each operational phase, forward models of various diagnostics are used and developed to aid design, provide consistency-checks during commissioning, test analysis methods, and build workflows to constrain high-level parameters to inform interpretation, theory and modelling. For new models and new analysis workflows, minimum-viable-products are released early, and their complexity is increased in a step-wise manner, facilitating the support of all programme phases on multiple parallel applications, while enabling learning opportunities and feedback loops. In this contribution we review the philosophy, scope and architecture of the framework under development. We discuss the details of some forward models, with examples on how they are used to aid diagnostic design, to investigate analysis methodologies through synthetic data, and how they are embedded in experimental analysis workflows. We compare previously published experimental results with new, more advanced analysis workflows employing more recent, detailed models and new diagnostic data, providing confirmation of the published material from the 2021–22 experimental campaign.

integrated data analysis↗
DOE OSTI2020

Progress in Understanding the Origins of Excellent Corrosion Resistance in Metallic Alloys: From Binary Polycrystalline Alloys to Metallic Glasses and High Entropy Alloys

Some of the factors responsible for good corrosion resistance of select polycrystalline and emerging alloys in chloride solutions are discussed with a goal of providing some perspectives on the current status and future directions. Traditional metallic glass alloys, single phase high entropy alloys (HEAs), early metallic glasses, and high entropy metallic glasses are all emerging corrosion-resistant alloys (CRAs) that utilize traditional strategies for improved corrosion resistance as well as take advantage of some other novel beneficial attributes. These materials enjoy many degrees of freedom as far as choice of both composition and structure, providing great flexibility in the pursuit of superior corrosion resistance. The new materials depart from classical solvent-solute type polycrystalline binary or ternary alloys. Thus, such emerging materials provide significant opportunities to achieve even greater improvements in corrosion resistance in harsh environments. Several examples of the unique corrosion properties of selected materials in the context of modern theories of corrosion are discussed herein. Discussion is restricted to solid-solution binary or ternary polycrystalline alloys, several metallic glass alloys, and single phase HEAs. A common feature of many CRAs is that composition and microstructure often affect both passivity and resistance to localized corrosion that can be divided into initiation, stabilization, and propagation stages. Enormous complexities in protective oxide structures and chemistries and the large number of combinatorial possibilities in newer materials such as HEAs preclude trial-and-error approaches and perhaps even combinatorial experimental design. Computational materials methodologies will be required in the search for new corrosion-resistant alloys in these material classes. The search must consider the best scientific insights available regarding how major and minor alloy additions, as well as various microstructural attributes, contribute to corrosion mitigation. Additional scientific insights, as they emerge, will enable choices beyond the reliance on high concentrations of alloying elements that are known to affect passivity breakdown and pit stabilization. A challenge is to connect the “basic attributes” of an alloy with its properties. The strength of this connection will likely require new scientific principles enabling deep multiphysics insights in order to link feature(s) such as composition and metallurgical phases to the desired corrosion properties. Application of data informatics will likely also play a role given the plethora of variables that are important in corrosion and the difficulty in assessing all relationships. Here, the opportunity exists to accelerate the design of emerging materials for high corrosion resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analysis of an Elasto-Hydrodynamic Seal by Using the Reynolds Equation

This paper reports numerical studies of an Elasto-Hydrodynamic (EHD) seal, which is being developed for supercritical CO2 (sCO2) turbomachinery applications. Current sCO2 turbomachinery suffers from high leakage rates, which is creating a major roadblock to the full realization of sCO2 power technology. The high leakage rates not only penalize the efficiencies but also create environmental concerns due to greenhouse effects caused by the increased CO2 discharge to the atmosphere. The proposed EHD seal needs to work at elevated pressures (10–35 MPa) and temperatures (350–700 °C) with low leakage and minimal wear. The unique mechanism of the EHD seal provides a self-regulated constriction effect to restrict the flow without substantial material contact, thereby minimizing leakage and wear. This work utilizes a physics-based modeling approach. The flow through the gradually narrowing seal clearance is modeled by the well-known Reynolds equation in EHD lubrication theory, while the deformation of the seal is modeled by using the governing equations of three-dimensional solid mechanics. As for the solution methodology, COMSOL’s Thin-Film Flow and Solid Mechanics modules were employed with their powerful capabilities. The numerical results were presented and discussed. It was observed that the Reynolds equation fully coupled with the surface deformation was able to successfully capture the constriction effect. The maximum and minimum leakages were calculated to be 2.25 g/s and 0.1 g/s at P = 5.5 MPa and P = 11 MPa for the design seal, respectively. It was interesting to observe that the seal leakage followed a quadratic trend with increasing pressure differential, which can become advantageous for high-pressure applications such as sCO2 power generation technology.

42 ENGINEERING↗
DOE OSTI2021

A Deterministic Multivariate Clustering Method for Drive Cycle Generation from In-Use Vehicle Data

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data. This paper explores the development and initial validation of a method of generating representative drive cycles from large collections of real-world vehicle data using a deterministic multivariate clustering approach. Starting with theory and diving into the methodology behind representative cycle generation, the paper aims to also present graphical and tabular results of initial validation via vehicle simulation and chassis dynamometer testing. Additional topics for further research and areas for ongoing development will also be presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Data-driven modeling of dynamic occupant thermostat override behavior for demand response applications

Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.

Sharma, Kunind [Northeastern University] (ORCID:00↗
DOE OSTI2026

Uniting Theory and Experiment to Deliver Flexible MOFS for Superior Methane (NG) Storage

The objective of the project was to use previous insights developed through synthesis and quantitative modeling of rigid metal–organic frameworks (MOFs) in an established synergistic theoretical/experimental team to create, modify, and evaluate flexible MOFs (FlexMOFs) for natural gas (NG) storage and release at practically useful pressures and transform the NG storage economy. The goal was reduced pressure absorbed natural gas (ANG) FlexMOF storage at operating pressures less than 100 bar with physisorption exploiting the favorable thermodynamics and kinetics of flexible porous material opening in response to adsorption. Hydrogen behavior in this context was also considered. The specific aim of the project was to design and develop a standard computational modeling methodology for, first, detailed atomistic retrodiction of FlexMOF gating behavior and ultimately prediction of the effects of functionalization and/or substitution on structural transitioning. The project was also geared towards the establishment of the interaction of methane with the framework and binding sites using modeling and the FlexMOF will be both internally and external validated as a SMART metric. This has value to the scientific community both from the obvious standpoint of providing a better understanding of the promising test case systems (CdIF-13 and the MIL-53(Al) series of MOFs), but also in providing an avenue of obtaining insight into these FlexMOF systems in general, which is of particular interest given the tendency of structure-function correlation to lag behind synthesis methodology (making the latter a hit or miss proposition for applications). This gap remains significant for FlexMOF systems whose gate opening behaviors complicate computational examination. The computational methodologies are relatively inexpensive in terms of both money and computational resources enhancing the general viability of these methodologies. The ultimate gain to the public will be in the application of these techniques to design systems for natural gas storage and use to cut down on green-house emissions.

03 NATURAL GAS↗