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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An Exceptionally Stable Metal–Organic Framework Constructed from Chelate-Based Metal–Organic Polyhedra

In this paper, we report the rational design and synthesis of a new, water-stable metal-organic framework (MOF), Fe-HAF-1, constructed from supramolecular, Fe3+-hydroxamate-based polyhedra with mononuclear metal nodes. Owing to its chelate-based con-struction, Fe-HAF-1 displays exceptional chemical stability in organic and aqueous solvents over a wide pH range (pH 1-14), including in the presence of 5 M NaOH. Despite the charge-neutrality of the Fe 3+ -tris(hydroxamate) centers, Fe-HAF-1 crystals are negatively charged above pH 4. This unex-pected property is attributed to the formation of defects during crystallization that results in uncoordinated hydroxamate ligands or hydroxide-coordinated Fe centers. The anionic na-ture of Fe-HAF-1 crystals enables selective adsorption of pos-itively charged ions in aqueous solution, resulting in efficient separation of organic dyes and other charged species in a size-selective fashion. Fe-HAF-1 presents a new addition to a small group of chelate-based MOFs and provides a rare framework whose 3D connectivity is exclusively formed by metal-hydroxamate coordination.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tailoring Lewis/Brønsted acid properties of MOF nodes via hydrothermal and solvothermal synthesis: simple approach with exceptional catalytic implications

The Lewis/Brønsted catalytic properties of the Metal–Organic Framework (MOF) nodes can be tuned by simply controlling the solvent employed in the synthetic procedure. In this work, we demonstrate that Hf-MOF-808 can be prepared from a material with a higher amount of Brønsted acid sites, via modulated hydrothermal synthesis, to a material with a higher proportion of unsaturated Hf Lewis acid sites, via modulated solvothermal synthesis. The Lewis/Brønsted acid properties of the resultant metallic clusters have been studied by different characterization techniques, including XAS, FTIR and NMR spectroscopies, combined with a DFT study. The different nature of the Hf-MOF-808 materials allows their application as selective catalysts in different target reactions requiring Lewis, Brønsted or Lewis– Brønsted acid pairs.

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

Sensing Electrical Networks Securely & Economically (SENSE)

The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2006

Mission Architecture Comparison for Human Lunar Exploration

The Vision for Space Exploration outlines a bold new national space exploration policy that holds as one of its primary objectives the extension of human presence outward into the Solar System, starting with a return to the Moon in preparation for the future exploration of Mars and beyond. The National Aeronautics and Space Administration is currently engaged in several preliminary analysis efforts in order to develop the requirements necessary for implementing this objective in a manner that is both sustainable and affordable. Such analyses investigate various operational concepts, or mission architectures , by which humans can best travel to the lunar surface, live and work there for increasing lengths of time, and then return to Earth. This paper reports on a trade study conducted in support of NASA s Exploration Systems Mission Directorate investigating the relative merits of three alternative lunar mission architecture strategies. The three architectures use for reference a lunar exploration campaign consisting of multiple 90-day expeditions to the Moon s polar regions, a strategy which was selected for its high perceived scientific and operational value. The first architecture discussed incorporates the lunar orbit rendezvous approach employed by the Apollo lunar exploration program. This concept has been adapted from Apollo to meet the particular demands of a long-stay polar exploration campaign while assuring the safe return of crew to Earth. Lunar orbit rendezvous is also used as the baseline against which the other alternate concepts are measured. The first such alternative, libration point rendezvous, utilizes the unique characteristics of the cislunar libration point instead of a low altitude lunar parking orbit as a rendezvous and staging node. Finally, a mission strategy which does not incorporate rendezvous after the crew ascends from the Moon is also studied. In this mission strategy, the crew returns directly to Earth from the lunar surface, and is thus referred to as direct return. Figures of merit in the areas of safety and mission success, mission effectiveness, extensibility, and affordability are used to evaluate and compare the lunar orbit rendezvous, libration point rendezvous, and direct return architectures, and this paper summarizes the results of those assessments.

Geffre, Jim↗
DOE OSTI2017

Quantum Accelerators for High-performance Computing Systems

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, the prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.

Humble, Travis↗
DOE OSTI2021

Stochastic pre-event preparation for enhancing resilience of distribution systems

Extreme weather events are the common causes for power supply interruptions and power outages in electrical distribution systems. Improving the distribution system and enhancing its resilience is becoming crucial due to the increased frequency of extreme weather events. Preparation and allocation of multiple flexible resources, such as mobile resources, fuel resources, and labor resources before extreme weather events can mitigate the effects of extreme weather events and enhance the resilience of power distribution systems. Here, in this paper, a two-stage stochastic mixed-integer linear programming (SMILP) is proposed to optimize the preparation and resource allocation process for upcoming extreme weather events, which leads to faster and more efficient post-event restoration. The objective of the proposed two-stage SMILP is to maximize the served load and minimize the operating cost of flexible resources. The first stage in the optimization problem selects the amounts and locations of different resources. The second stage considers the operational constraints of the distribution system and repair crew scheduling constraints. The proposed stochastic pre-event preparation model is solved by a scenario decomposition method, Progressive Hedging (PH), to ease the computational complexity introduced by a large number of scenarios. Furthermore, to show the impact of solar photovoltaic (PV) generation on system resilience, three types of PV systems are considered during a power outage and the resilience improvements with different PV penetration levels are compared. Numerical results from simulations on a large-scale (more than 10,000 nodes) distribution feeder have been used to validate the effectiveness and scalability of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Orb5: A global electromagnetic gyrokinetic code using the PIC approach in toroidal geometry

This paper presents the current state of the global gyrokinetic code Orb5 as an update of the previous reference [Jolliet et al., Comp. Phys. Commun. 177 409 (2007)]. The Orb5 code solves the electromagnetic VlasovMaxwell system of equations using a PIC scheme and also includes collisions and strong flows. The code assumes multiple gyrokinetic ion species at all wavelengths for the polarization density and drift-kinetic electrons. Variants of the physical model can be selected for electrons such as assuming an adiabatic response or a “hybrid” model in which passing electrons are assumed adiabatic and trapped electrons are drift-kinetic. A Fourier filter as well as various control variates and noise reduction techniques enable simulations with good signal-to-noise ratios at a limited numerical cost. They are completed with different momentum and zonal flow-conserving heat sources allowing for temperature-gradient and flux-driven simulations. The code, which runs on both CPUs and GPUs, is well benchmarked against other similar codes and analytical predictions, and shows good scalability up to thousands of nodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Catalysis by Metal Organic Frameworks: Perspective and Suggestions for Future Research

Metal organic frameworks (MOFs) have drawn wide attention as potential catalysts, offering high densities of catalytic sites in high-area porous solids, some with stabilities at high temperatures. The field is at an early stage, characterized by numerous discoveries and novel demonstrations of catalytic properties associated with the crystalline structures of MOFs, but applications of MOFs as catalysts are still lacking. In this perspective we summarize advantages and limitations of MOFs as catalysts and fundamental issues to be addressed about their potential applications. MOF framework compositions and pore structures can strongly influence catalytic performance, allowing, for example, shape-selective and bifunctional catalysis, but research is needed to quantify reaction/transport processes in MOFs, identify catalytic sites, and determine intrinsic catalytic reaction rates. Progress is hindered by the lack of understanding of the heterogeneity of MOFs, with catalytic sites sometimes being in structures such as defects not determined by X-ray diffraction crystallography. Determination of the dynamics of MOFs and their catalytic sites, as well as the intrinsic kinetics of catalytic reactions, will help to advance guidelines for synthesizing optimum catalysts. Further, MOFs present challenges related to stability and regeneration as catalysts, some associated with the unique nature of MOFs, such as the node–linker bonds, which can break during catalysis. There are opportunities to understand these matters in depth and to find conditions of catalytic operation that minimize the processes leading to deactivation.

catalysis (heterogeneous), materials and chemistry↗
DOE OSTI2022

Hydrogen separation with a graphenylene monolayer: Diffusion Monte Carlo study

Here, we performed fixed-node diffusion Monte Carlo (DMC) calculations to investigate structural and energetic properties of graphenylene (GPNL), a two-dimensional network of sp 2 -bonded carbon atoms with large near-circular pores, and its H 2 separation performance for gas mixtures. We have found that the energetic stability of a GPNL monolayer is comparable to that of γ-graphyne, as evidenced by its large cohesive energy of 6.755(3) eV/atom. Diffusion barriers of several gas molecules, including hydrogen, through a GPNL membrane were determined from the analysis of their adsorption energies depending on the adsorption distance, which led to our estimation for hydrogen selectivity with respect to other target molecules. DMC hydrogen selectivity of a GPNL monolayer was found to be exceptionally high at 300 K, as high as 10 10 –10 11 against CO and N 2 gases. This, along with high hydrogen permeance due to its generic pore structure, leads us to conclude that GPNL is a promising membrane to be used as a high-performance hydrogen separator from gas mixtures. We find that when compared to our DMC results, DFT calculations tend to overestimate H 2 selectivity, which is mostly due to their inaccurate description of short-range repulsive interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Auxetic metamaterials from disordered networks

Recent theoretical work suggests that systematic pruning of disordered networks consisting of nodes connected by springs can lead to materials that exhibit a host of unusual mechanical properties. In particular, global properties such as Poisson's ratio or local responses related to deformation can be precisely altered. Tunable mechanical responses would be useful in areas ranging from impact mitigation to robotics and, more generally, for creation of metamaterials with engineered properties. However, experimental attempts to create auxetic materials based on pruningbased theoretical ideas have not been successful. In this study, we introduce a more realistic model of the networks, which incorporates angle-bending forces and the appropriate experimental boundary conditions. A sequential pruning strategy of select bonds in this model is then devised and implemented that enables engineering of specific mechanical behaviors upon deformation, both in the linear and in the nonlinear regimes. In particular, it is shown that Poisson's ratio can be tuned to arbitrary values. The model and concepts discussed here are validated by preparing physical realizations of the networks designed in this manner, which are produced by laser cutting 2D sheets and are found to behave as predicted. Furthermore, by relying on optimization algorithms, we exploit the networks' susceptibility to tuning to design networks that possess a distribution of stiffer and more compliant bonds and whose auxetic behavior is even greater than that of homogeneous networks. Finally, taken together, the findings reported here serve to establish that pruned networks represent a promising platform for the creation of unique mechanical metamaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine Learning-Based Identification of the Interface Regions for Coupling Local and Nonlocal Models

Local-nonlocal coupling approaches provide a means to combine the computational efficiency of local models and the accuracy of nonlocal models. However, the coupling process can be challenging, requiring expertise to identify the interface between local and nonlocal regions. Here, this study introduces a machine learning-based approach to automatically detect the regions in which the local and nonlocal models should be used. The method uses loading functions evaluated at grid points to decide the model selection at those points. Training of the networks is based on datasets provided by classes of loading functions for which reference coupling configurations are computed using accurate coupled solutions, where accuracy is measured in terms of the relative error between the solution to the coupling approach and the solution to the nonlocal model. We study two approaches that vary in data structure. The first, the full-domain input data approach, uses the entire load vector and outputs a complete label vector, performing a global classification. The second, a window-based approach, processes loads into windows and addresses the problem as a node-wise classification where each window's central point is classified individually. The classification problems are solved via deep learning algorithms based on convolutional neural networks. The performance of these approaches is studied on one-dimensional numerical examples using F1-scores and accuracy metrics. Notably, the windowing approach achieves an accuracy of 0.96 and an F1-score of 0.97, highlighting its potential to automate coupling processes effectively and enhance computational efficiency in material science applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimal Power Dispatch of DGs in Radial and Mesh AC Grids: A Hybrid Solution Methodology between the Salps Swarm Algorithm and Successive Approximation Power Flow Method

In this paper, we address the problem of the optimal power dispatch of Distributed Generators (DGs) in Alternating Current (AC) networks, better known as the Optimal Power Flow (OPF) problem. We used, as the objective function, the minimization of power losses (P loss ) associated with energy transport, which are subject to the set of constraints that compose AC networks in an environment of distributed generation. To validate the effectiveness of the proposed methodology in solving the OPF problem in any network topology, we employed one 10-node mesh test system and three radial text systems: 10, 33, and 69 nodes. In each test system, DGs were allowed to inject 20%, 40%, and 60% of the power supplied by the slack generator in the base case. To solve the OPF problem, we used a master–slave methodology that integrates the optimization method Salps Swarm Algorithm (SSA) and the load flow technique based on the Successive Approximation (SA) method. Moreover, for comparison purposes, we employed some of the algorithms reported in the specialized literature to solve the OPF problem (the continuous genetic algorithm, the particle swarm optimization algorithm, the black hole algorithm, the antlion optimization algorithm, and the Multi-Verse Optimizer algorithm), which were selected because of their excellent results in solving such problems. The results obtained by the proposed solution methodology demonstrate its superiority and convergence capacity in terms of minimization of P loss in both radial and mesh systems. It provided the best reduction in minimum P loss in short processing times and showed excellent repeatability in each test system and scenario under analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1996

Cloud Classification in Polar and Desert Regions and Smoke Classification from Biomass Burning Using a Hierarchical Neural Network

This research focuses on a new neural network scene classification technique. The task is to identify scene elements in Advanced Very High Resolution Radiometry (AVHRR) data from three scene types: polar, desert and smoke from biomass burning in South America (smoke). The ultimate goal of this research is to design and implement a computer system which will identify the clouds present on a whole-Earth satellite view as a means of tracking global climate changes. Previous research has reported results for rule-based systems (Tovinkere et at 1992, 1993) for standard back propagation (Watters et at. 1993) and for a hierarchical approach (Corwin et al 1994) for polar data. This research uses a hierarchical neural network with don't care conditions and applies this technique to complex scenes. A hierarchical neural network consists of a switching network and a collection of leaf networks. The idea of the hierarchical neural network is that it is a simpler task to classify a certain pattern from a subset of patterns than it is to classify a pattern from the entire set. Therefore, the first task is to cluster the classes into groups. The switching, or decision network, performs an initial classification by selecting a leaf network. The leaf networks contain a reduced set of similar classes, and it is in the various leaf networks that the actual classification takes place. The grouping of classes in the various leaf networks is determined by applying an iterative clustering algorithm. Several clustering algorithms were investigated, but due to the size of the data sets, the exhaustive search algorithms were eliminated. A heuristic approach using a confusion matrix from a lightly trained neural network provided the basis for the clustering algorithm. Once the clusters have been identified, the hierarchical network can be trained. The approach of using don't care nodes results from the difficulty in generating extremely complex surfaces in order to separate one class from all of the others. This approach finds pairwise separating surfaces and forms the more complex separating surface from combinations of simpler surfaces. This technique both reduces training time and improves accuracy over the previously reported results. Accuracies of 97.47%, 95.70%, and 99.05% were achieved for the polar, desert and smoke data sets.

Alexander, June↗
NASA NTRS1995

DITDOS: A set of design specifications for distributed data inventories

The analysis of space science data often requires researchers to work with many different types of data. For instance, correlative analysis can require data from multiple instruments on a single spacecraft, multiple spacecraft, and ground-based data. Typically, data from each source are available in a different format and have been written on a different type of computer, and so much effort must be spent to read the data and convert it to the computer and format that the researchers use in their analysis. The large and ever-growing amount of data and the large investment by the scientific community in software that require a specific data format make using standard data formats impractical. A format-independent approach to accessing and analyzing disparate data is key to being able to deliver data to a diverse community in a timely fashion. The system in use at the Planetary Plasma Interactions (PPI) node of the NASA Planetary Data System (PDS) is based on the object-oriented Distributed Inventory Tracking and Data Ordering Specification (DITDOS), which describes data inventories in a storage independent way. The specifications have been designed to make it possible to build DITDOS compliant inventories that can exist on portable media such as CD-ROM's. The portable media can be moved within a system, or from system to system, and still be used without modification. Several applications have been developed to work with DITDOS compliant data holdings. One is a windows-based client/server application, which helps guide the user in the selection of data. A user can select a data base, then a data set, then a specific data file, and then either order the data and receive it immediately if it is online or request that it be brought online if it is not. A user can also view data by any of the supported methods. DITDOS makes it possible to use already existing applications for data-specific actions, and this is done whenever possible. Another application is a stand-alone tool to assist in the extraction of data from portable media, such as CD-ROM's. In addition to the applications, there is a set of libraries that can facilitate building new DITDOS compliant applications.

King, T. A.↗
DOE OSTI2019

Development of the Local (Site) Symmetry Method in the Supercell Model for a Crystal with an Impurity

Symmetry aspects of the periodic model of a crystal with a point defect (a supercell model or a extended unit cell (EUC) model) are considered; splitting of the Wyckoff positions in a primitive crystal cell with the introduction of supercell and the change of the one-electron states classification over k-vector (Brillouin zone folding) are discussed. When considering a point defect in a crystal in the supercell model, it is necessary to take into account the symmetry of the one-electron states of the original crystal at the top of the valence band and at the bottom of the conduction band. The selected supercell should reproduce these states. Each specific selection of a supercell corresponds to a specific splitting of the Wyckoff positions of the original crystal and, as a result, the possibility to place a defect in positions with different point symmetry and to perform a calculation without taking into account the point symmetry of the crystal with a defect at all (site symmetry method). By the results of the calculation of a crystal with a defect in the supercell model, taking into account site symmetry, it is possible to determine the real symmetry of the crystal with a defect, which is essential for the interpretation of experimental data. A copper impurity in a lithium node in a LiCl crystal retains the cubic symmetry of the atom being replaced; the impurity of an iron atom in a titanium site with cubic local symmetry in a SrTiO{sub 3} crystal lowers the symmetry to tetragonal; and the H site in the CsPbI{sub 3} crystal is characterized by the complete removal of point symmetry with the formation of an I{sub 2}{sup −} ion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2007

NASA Tech Briefs, June 2007

Topics covered include: High-Accuracy, High-Dynamic-Range Phase-Measurement System; Simple, Compact, Safe Impact Tester; Multi-Antenna Radar Systems for Doppler Rain Measurements; 600-GHz Electronically Tunable Vector Measurement System; Modular Architecture for the Measurement of Space Radiation; VLSI Design of a Turbo Decoder; Architecture of an Autonomous Radio Receiver; Improved On-Chip Measurement of Delay in an FPGA or ASIC; Resource Selection and Ranking; Accident/Mishap Investigation System; Simplified Identification of mRNA or DNA in Whole Cells; Printed Multi-Turn Loop Antennas for RF Biotelemetry; Making Ternary Quantum Dots From Single-Source Precursors; Improved Single-Source Precursors for Solar-Cell Absorbers; Spray CVD for Making Solar-Cell Absorber Layers; Glass/BNNT Composite for Sealing Solid Oxide Fuel Cells; A Method of Assembling Compact Coherent Fiber-Optic Bundles; Manufacturing Diamond Under Very High Pressure; Ring-Resonator/Sol-Gel Interferometric Immunosensor; Compact Fuel-Cell System Would Consume Neat Methanol; Algorithm Would Enable Robots to Solve Problems Creatively; Hypothetical Scenario Generator for Fault-Tolerant Diagnosis; Smart Data Node in the Sky; Pseudo-Waypoint Guidance for Proximity Spacecraft Maneuvers; Update on Controlling Herds of Cooperative Robots; and Simulation and Testing of Maneuvering of a Planetary Rover.

Source record↗
DOE OSTI2017

Community detection in sequence similarity networks based on attribute clustering

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs, for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MOF-enabled confinement and related effects for chemical catalyst presentation and utilization

A defining characteristic of nearly all catalytically functional MOFs is uniform, molecular-scale porosity. MOF pores, linkers and nodes that define them, help regulate reactant and product transport, catalyst siting, catalyst accessibility, catalyst stability, catalyst activity, co-catalyst proximity, composition of the chemical environment at and beyond the catalytic active site, chemical intermediate and transition-state conformations, thermodynamic affinity of molecular guests for MOF interior sites, framework charge and density of charge-compensating ions, pore hydrophobicity/hydrophilicity, pore and channel rigidity vs. flexibility, and other features and properties. Collectively and individually, these properties help define overall catalyst functional behaviour. Here, this review focuses on how porous, catalyst-containing MOFs capitalize on molecular-scale confinement, containment, isolation, environment modulation, energy delivery, and mobility to accomplish desired chemical transformations with potentially superior selectivity or other efficacy, especially in comparison to catalysts in homogeneous solution environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗