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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Tracking Restoration And Closure (TRAC): Status Update on Story Maps for Communicating Site Cleanup and Closure Status - 19033

The U.S. Department of Energy (DOE) Office of Environmental Management (EM) initiated the development of a customized, web-based mapping tool for communicating technical information on groundwater plumes at sites within the EM complex. Although the online tool was initially conceived to be a simple conversion of a paper report on contaminant plume sizes, remedial approaches, and regulatory status, it has advanced to providing specific information on cleanup status and site closure. The story maps provide robust geospatial visualization of plumes at DOE sites, as well as explanatory text, photographs, and video for an entire site, or for a management unit within the site. This collection of story maps is called TRAC (Tracking Restoration And Closure), and not only communicates information for each individual site, but also summarizes pertinent metrics on cleanup and remaining contaminants across all EM sites. TRAC is focused on communicating cleanup status, technical challenges, and needs for site closure, with a key challenge of transforming data into relevant, easily understood information. Although DOE managers are the target audience, the story maps can also be used to contribute to public understanding of groundwater cleanup progress at EM sites. Unlike the data access tools maintained at some EM sites (e.g., Hanford, Portsmouth, and Paducah), TRAC is neither a portal for data downloads, nor a tool for performing data analytics. Rather, the goal of TRAC is to provide relevant information on cleanup progress and closure that is consistent across all sites, allowing the user to view summary information across all sites, or examine information relevant to a particular site. This information sharing is needed to maintain open communications with interested parties and communicate efforts that ensure long-term protection of human health and the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Quantitative Method Development and Validation of Naloxone and 6α‐naloxol from Male African Green Monkey Plasma.

Theopioid epidemic is a rapidly growing crisis around the world. Current models forpharmacokinetic assessment of countermeasures use African green monkeys (AGM). Arapid, sensitive and selective method was developed and validated usingLC‐MS/MS for the determination of naloxone and 6α‐naloxol in AGM plasma. Samplepreparation involved a simple solid phase extraction (SPE) using ahydrophilic‐lipophilic‐balanced reversed‐phase cartridge. Separation of naloxoneand 6α‐naloxol was achieved on a Halo C18, 2.1 × 50 mm, 2.7μ analytical columnusing an Agilent 1290 Infinity HPLC. A solvent system of methanol‐water‐formicacid was used for the elution of analytes. The analytes were detected and monitoredby a SCIEX QTRAP 6500 + triple quadrupole tandem mass spectrometer operatedin electrospray ionization (ESI) positive mode and multiple reaction monitoring(MRM). Molecular ion transitions for naloxone, 6α‐naloxol and naloxone‐D5 were 328.0/212.0,330.0/185.0, and 333.1/212.0 m/z, respectively. The method was validated usingcalibration and recovery assays with spiked samples. Linear calibration curveswere generated over the range of 1.5–100 ng/ml with values for the coefficientof determination (R 2 ) of >0.9950. The values for both inter‐dayand intra‐day precision and accuracy were well within the generally acceptedcriteria for analytical methods (≤15%). This method was subsequentlyused to measure plasma concentrations of naloxone and 6α‐naloxol in male AGMs administerednaloxone subcutaneously and intravenously. The developed method demonstratedexcellent recovery, repeatability, accuracy and sensitivity. Support or Funding Information DISCLAIMERS. The views expressed in this abstractare those of the authors (s) and do not reflect the official policy of theDepartment of Army, Department of Defense, or U. S. Government. This researchwas supported by the Defense Threat Reduction Agency – Joint Science andTechnology office, Medical S&T Division. Thisproject was supported in part by an appointment to the Research ParticipationProgram for the U.S. Army Medical Research and Materiel Command administratedby the Oak Ridge Institute for Science and Education through an agreementbetween the U.S. Army Medical Research and Materiel Command. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Bandaru, Veera Venkata Ratnam↗
DOE OSTI2022

Boiling Transitions During Droplet Contact on Superheated Nano/Micro-Structured Surfaces

Manipulating surface topography is one of the most promising strategies for increasing the efficiency of numerous industrial processes involving droplet contact with superheated surfaces. In such scenarios, the droplets may immediately boil upon contact, splash and boil, or could levitate on their own vapor in the Leidenfrost state. In this work we report the outcomes of water droplets coming in gentle contact with designed nano/micro-textured surfaces at a wide range of temperatures as observed using high-speed optical and X-ray imaging. Further, we report a paradoxical increase in the Leidenfrost temperature ($T_{\text{LFP}}$) as the texture spacing is reduced below a critical value (~10 μm) that represents a minima in $T_{\text{LFP}}$. Although droplets on such textured solids appear to boil upon contact, our studies suggest that their behavior is dominated by hydrodynamic instabilities implying that the increase in $T_{\text{LFP}}$ may not necessarily lead to enhanced heat transfer. On such surfaces, the droplets display a new regime characterized by splashing accompanied by a vapor jet penetrating through the droplets before they transition to the Leidenfrost state. We provide a comprehensive map of boiling behavior of droplets over a wide range of texture spacings that may have significant implications towards applications such as electronics cooling, spray cooling, nuclear reactor safety and containment of fire calamities.

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

Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes

This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf). Both csv and json files can be read by common text editors but the data contained into them can be better handled using programming languages like python and database oriented libraries like pandas. Pdf files can be read by any pdf reader software.[02-23-2024] Update: The code and datasets necessary to reproduce the results of the study are available as a zipped repository (code_datasets_catchments_similarity.zip).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Scrambling versus relaxation in Fermi and non-Fermi liquids

In this work, we compute the Lyapunov exponent characterizing quantum scrambling in a family of generalized Sachdev- Ye-Kitaev models, which can be tuned between different low temperature states from Fermi liquids, through non-Fermi liquids, to fast scramblers. The analytic calculation, controlled by a small coupling constant and large $\textit{N}$, allows us to clarify the relations between the quasiparticle relaxation rate $\textit{1/τ}$ and the Lyapunov exponent $λ_L$ characterizing scrambling. In the Fermi liquid states we find that the quasiparticle relaxation rate dictates the Lyapunov exponent. In non-Fermi liquids, where $1/τ \gg T$, we find that $λ_L$ is always $\textit{T}$ linear with a prefactor that is independent of the coupling constant in the limit of weak coupling. Instead it is determined by a scaling exponent that characterizes the relaxation rate. $λ_L$ approaches the general upper bound 2$\textit{πT}$ at the transition to a fast scrambling state. Finally, in a marginal Fermi liquid state the exponent is linear in temperature with a prefactor that vanishes as a nonanalytic function ~$g\text{ln}(1/g)$ of the coupling constant $\textit{g}$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Maximum Concentration Values Review for Use in NUCON Vapor Abatement Unit Testing

Exponent has recommended that “high inlet spike” concentrations be verified for accuracy regarding their representation of the maximum measured headspace concentrations for tanks at Hanford. Exponent further recommended that “high inlet spike” concentrations of chemicals of potential concern (COPCs) be inclusive of surrogate COPCs. In the initial analysis (Rev. A Test Plan), only analytical results from the Site-Wide Industrial Hygiene Database (SWIHD) were used. The reason for this initial decision was a concern about Washington River Protection Solutions (WRPS) taking responsibility for results that were not produced during their contract tenure. As a result of Exponent’s comments, WRPS verified the “high inlet spike” values for accuracy against the data for single-shell tanks in all the historical databases, not only SWIHD. Measurements made prior to interim waste stabilization or waste retrieval were not considered in the verification of maximum measured concentrations as they are not representative of current tank farm conditions. Data for surrogate COPCs were also considered in determining the “high inlet spike” concentrations. Table S.1 shows the newly evaluated concentrations (COPC and surrogate). The original and revised test conditions are also shown with changes indicated by red text.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Photoelectron spectroscopy of cryogenically cooled NiO 2 – via slow photoelectron velocity-map imaging

In this work, high-resolution anion photoelectron spectra of cryogenically cooled NiO 2 – anions, obtained using slow photoelectron velocity-map imaging (cryo-SEVI), are presented in tandem with coupled cluster electronic structure calculations including relativistic effects. The experimental spectra encompass the $\tilde{\text{X}}^1Σ_{\text{g}}^+ ← \tilde{\text{X}}^2Π_{\text{g}}, ã^3Π{\text{g}} ← \tilde{\text{X}}^2Π_{\text{g}}$, and $\tilde{\text{A}}^1Π_{\text{g}} ← \tilde{\text{X}}^2Π_{\text{g}}$ photodetachment transitions of linear ONiO 0/– , revealing previously unobserved vibrational structure in all three electronic bands. The high-resolution afforded by cryo-SEVI allows for the extraction of vibrational frequencies for each state, consistent with those previously measured in the ground state and in good agreement with scalar-relativistic coupled-cluster calculations. Previously unobserved vibrational structure is observed in the $ã^3Π_{\text{g}}$ and $Ã^1Π_{\text{g}}$ states and is tentatively assigned. Further, a refined electron affinity of 3.0464(7) eV for NiO 2 is obtained as well as precise term energies for the ã and à states of NiO 2 of 0.3982(7) and 0.7422(10) eV, respectively. Numerous Franck–Condon forbidden transitions involving the doubly degenerate $ν_2$ bending mode are observed and ascribed to Herzberg-Teller coupling to an excited electronic state.

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

Frequent Fulcrum Functions: The Basics of SCALE’s Graphical User Interface [Slides]

This tutorial introduces the Fulcrum graphical user interface and the basic functions that enhance the common activities of creating, editing, navigating, executing, and visualizing SCALE input files. This tutorial will help you become familiar with the Fulcrum input file text editor and the integrated input development environment features of autocompletion, automatic checking, cursor context, and input navigation. In addition, the Fulcrum and SCALE runtime environment will be reviewed to improve the understanding of job execution workflow. This tutorial does not cover data and geometry plotting. Please see the Advanced User Interface Capabilities tutorial for details regarding plotting data and geometry. No prior experience with SCALE is required. You can follow along using SCALE 6.2 or 6.3-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Experimental and theoretical studies of the reactions of ground-state sulfur atoms with hydrogen and deuterium

The gas-phase kinetics of S( 3 P) atoms with H 2 and D 2 have been studied via the laser flash photolysis—resonance fluorescence technique. S atoms were generated by pulsed photolysis of CS 2 at 193 nm and monitored by time-resolved fluorescence at 181 nm. The rate coefficients for H 2 ( k 1 ) and D 2 ( k 2 ), respectively, are summarized as k 1 (600-1110 K) = 3.0 × 10 –9 exp(– 1.317×10 5 –2.703×10 7 K/ T / 8.314 T/K ) cm 3 molecule –1 s –1 and k 2 (770-1110 K) = 2.2 × 10 –14 ( T /298 K) 3.55 exp(–5420 K/T) cm 3 molecule –1 s –1 . Error limits are discussed in the text. The rate coefficients for formation of SH(SD) + H(D) on a newly developed triplet potential energy surface were characterized via ring polymer molecular dynamics and canonical variational transition-state theory. Furthermore there is excellent agreement above about 1000 K between theory and experiment. At lower temperatures, the experimental rate coefficient is substantially larger than the results computed for the adiabatic reaction, suggesting a significant role for intersystem crossing to the singlet potential energy surface at lower temperatures.

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

Theory of ignition and burn propagation in inertial fusion implosions

A detailed analytic model is presented here to investigate the physics of burn propagation in inertially confined plasmas. The onset of ignition and burn propagation occurs when alpha heating of the hot spot causes rapid ablation of shell mass into the hot spot. This allows large energy gains to be achieved since most of the fuel mass is located in the shell. Here, we first present a comprehensive review of previous analytic models that have been used to describe the physics of hot-spot evolution and ignition; we then show that a proper description of a propagating burn wave requires a comprehensive model of hot spot and shell evolution that includes proper mass conservation in the shell, fusion reactivity, and fuel depletion. The analytic theory is in good agreement with detailed radiation-hydrodynamic simulations that predict the onset of burn propagation as occurring when the yield enhancement caused by alpha heating is between 15- and 25-fold, $f_α$ ~ 1.4, where $f_α$ = alpha energy deposited/hot-spot energy at bang time, and the hot-spot burnup fraction is approximately 2%. We show that the definition of ignition is not sensitive to the alpha-particle stopping power nor asymmetries provided that the absorbed fraction of alpha particles $θ_α$ is correctly accounted for. Finally, we use the results of 2-D simulations to show that even when $θ_α$ is small and unknown (as is true in hot spots with mid modes that have significant leakage of alpha particles into the surrounding cold bubbles), one can still relate the experimentally measureable parameter $\chi^{53}_α$ to the yield amplification and the burning-plasma parameter $Q^{\text{hs}}_α$ = alpha energy deposited/total input work delivered to the hot spot

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective

We present a perspective for accelerating biomass manufacturing via digitalization. We summarize the challenges for manufacturing and identify areas where digitalization can help. A profound potential in using lignocellulosic biomass and renewable feedstocks, in general, is to produce new molecules and products with unmatched properties that have no analog in traditional refineries. Discovering such performance-advantaged molecules and the paths and processes to make them rapidly and systematically can transform manufacturing practices. Furthermore, we discuss retrosynthetic approaches, text mining, natural language processing, and modern machine learning methods to enable digitalization. Laboratory and multiscale computation automation via active learning are crucial to complement existing literature and expedite discovery and valuable data collection without a human in the loop. Such data can help process simulation and optimization select the most promising processes and molecules according to economic, environmental, and societal metrics. We propose the close integration between bench and process scale models and data to exploit the low dimensionality of the data and transform the manufacturing for renewable feedstocks.

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

Chaconne: A Statistical Approach to Nonlocal Compression for Supervised Learning, Semi-Supervised Learning, and Anomaly Detection

This project developed a novel statistical understanding of compression analytics (CA), which has challenged and clarified some core assumptions about CA, and enabled the development of novel techniques that address vital challenges of national security. Specifically, this project has yielded the development of novel capabilities including 1. Principled metrics for model selection in CA, 2. Techniques for deriving/applying optimal classification rules and decision theory to supervised CA, including how to properly handle class imbalance and differing costs of misclassification, 3. Two techniques for handling nonlocal information in CA, 4. A novel technique for unsupervised CA that is agnostic with regard to the underlying compression algorithm, 5. A framework for semisupervised CA when a small number of labels are known in an otherwise large unlabeled dataset. 6. The academic alliance component of this project has focused on the development of a novel exemplar-based Bayesian technique for estimating variable length Markov models (closely related to PPM [prediction by partial matching] compression techniques). We have developed examples illustrating the application of our work to text, video, genetic sequences, and unstructured cybersecurity log files.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Laser Ablation Plasmas and Spectroscopy for Nuclear Applications

The development of measurement methodologies to detect and monitor nuclear-relevant materials remains a consistent and significant interest across the nuclear energy, nonproliferation, safeguards, and forensics communities. Optical spectroscopy of laser-produced plasmas is becoming an increasingly popular diagnostic technique to measure radiological and nuclear materials in the field without sample preparation, where current capabilities encompass the standoff, isotopically resolved and phase-identifiable (e.g., UO and UO[Formula: see text]) detection of elements across the periodic table. These methods rely on the process of laser ablation (LA), where a high-powered pulsed laser is used to excite a sample (solid, liquid, or gas) into a luminous microplasma that rapidly undergoes de-excitation through the emission of electromagnetic radiation, which serves as a spectroscopic fingerprint for that sample. This review focuses on LA plasmas and spectroscopy for nuclear applications, covering topics from the wide-area environmental sampling and atmospheric sensing of radionuclides to recent implementations of multivariate machine learning methods that work to enable the real-time analysis of spectrochemical measurements with an emphasis on fundamental research and development activities over the past two decades. Background on the physical breakdown mechanisms and interactions of matter with nanosecond and ultrafast laser pulses that lead to the generation of laser-produced microplasmas is provided, followed by a description of the transient spatiotemporal plasma conditions that control the behavior of spectroscopic signatures recorded by analytical methods in atomic and molecular spectroscopy. High-temperature chemical and thermodynamic processes governing reactive LA plasmas are also examined alongside investigations into the condensation pathways of the plasma, which are believed to serve as chemical surrogates for fallout particles formed in nuclear fireballs. Laser-supported absorption waves and laser-induced shockwaves that accompany LA plasmas are also discussed, which could provide insights into atmospheric ionization phenomena from strong shocks following nuclear detonations. Furthermore, the standoff detection of trace radioactive aerosols and fission gases is reviewed in the context of monitoring atmospheric radiation plumes and off-gas streams of molten salt reactors. Finally, concluding remarks will present future outlooks on the role of LA plasma spectroscopy in the nuclear community.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Dynamic Network Analysis of Nuclear Science Literature for Research Influence Assessment

Analyzing nuclear science literature via data-driven methods is a critical step for assessing research influence and technology advancements. Indicators of scholarly activities may be buried in large volumes of nuclear research publications and collaboration networks over time. Mining for relevant scholarly influence trends in large volumes of text can be computationally challenging; however, open-source information on research collaborations over time can offer opportunities to extract meaningful insights. While network centrality analysis of scholarly research provides topology-based insights, additional emphasis on dynamics associated with the diffusion of information through these networks is important. Here this paper represents a step in that direction through the development of a novel dynamic network analysis framework and computational engine to identify key entities and capabilities over time within global scholarly nuclear science collaboration networks. Network theoretic, stochastic simulation, and optimization methods are leveraged to address variability in scholarly interactions, influence propagation, and collaboration patterns via network connections. A topic-aware influence maximization algorithm is developed to address the goal of identifying key influential authors in diverse research topics over time. Efficient parallelized implementation of the algorithm is applied to reduce computational costs. A proof-of-concept case study using open-source Scopus data with 33,517 published nuclear research papers from 2000-2019 is presented and representative analytic insights are generated. Broad implications of these insights are discussed and future research directions are also identified.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Relaxation drag history of shock accelerated microparticles

Experimental measurements of the displacements of shock accelerated microparticles from shortly after shock interaction to the particle relaxation time show time-dependent drag coefficients ( $C_{D}$ ) that are much higher than those predicted by quasi-steady and unsteady drag models. Nylon particles with mean diameter of $4~\unicode[STIX]{x03BC}\text{m}$ , accelerated by one-dimensional normal shocks (Mach number $M_{s}=1.2$ , 1.3 and 1.4), have measured $C_{D}$ values that follow a power-law behaviour. The drag is a function of the time-dependent Knudsen number, $Kn^{\ast }=M_{s}/Re_{p}$ , where the particle Reynolds number ( $Re_{p}$ ) is calculated using the time-dependent slip velocity. Also, some portion of the drag can be attributed to quasi-steady forces, but the total drag cannot be predicted by current unsteady force models that are based on the Basset–Boussinesq–Oseen equation and pressure drag. The largest contribution to the total drag is the unsteady component ( $C_{D,us}$ ) until the particle attains $Kn^{\ast }\approx 0.5{-}1.0$ , then the unsteady contribution decays. The quasi-steady component ( $C_{D,qs}$ ) increases almost linearly with $Kn^{\ast }$ , intersects the $C_{D,us}$ at $Kn^{\ast }\approx 2$ and becomes the primary contributor to the drag towards the end of the relaxation zone as $Re_{p}\rightarrow 0$ . Finally, there are currently no analytical models that are able to predict the nonlinear behaviour of the shock accelerated particles during the relaxation phase of the flow.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Erratum: “Beyond chemical accuracy in the heavy p-block: The first ionization potentials and electron affinities of Ga–Kr, In–Xe, and Tl–Rn” [J. Chem. Phys. 151, 024303 (2019)]

In Ref. 1 incorrect values for the spin-orbit effects on the electron affinities (EAs) of Ga and In were used in Table IV. The KRCI values shown in Table III of Ref. 1, -0.49 and -0.94 kcal/mol for Ga and In, respectively, should have been given. Correct use of these latter values results in final FPD EAs for Ga and In of 6.97 and 8.91 kcal/mol, respectively. The incorrect FPD values were also given in the Abstract and Conclusion sections of Ref. 1. In addition, the experimental EA for In shown in the last column of Table IV was incorrect and should be 8.85 kcal/mol (the actual value being 8.8534 but only two decimal places are displayed throughout this table). A complete replacement for Table IV is given below with the corrected values given in bold font. The corrected FPD and experimental EA values for In in particular changes some of the conclusions of Ref. 1, namely when it is stated both in the abstract and the main text (Sec. III.B and Conclusions) that the experimental EA values for all of the group 13 (Ga, In, and Tl) EAs are too large. This is obviously not true for the EA of In, where the actual FPD value and the experimental result of Walter et al. are in excellent agreement, to within 0.1 kcal/mol. The FPD EAs of the other two group 13 elements, Ga and Tl, differ from their experimental values by 2.5 and 1.3 kcal/mol, respectively, which is still outside of the estimated uncertainty limits of this FPD approach (conservatively ±0.5 kcal/mol), particularly for Ga, therefore the original conclusions for these two elements are largely unchanged.

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

Complexation of Tc(IV) with ${\text{SO}}_{4}^{2–}$ in NaCl Medium

We report on the experimental determination of the stability constant for the complexation of the Tc(IV) cation by ${\text{SO}}_{4}^{2–}$ at 1.0 mol kg -1 ionic strength (NaCl) and pcH 1.51 ± 0.05, using a solvent extraction method. This research represents a first step in determining unknown thermodynamic parameters for the complexation of Tc(IV) by simple polyatomic anions. Radiotracer studies were carried out with 99 Tc and 35 S, using both HDEHP and TOPO as extractants, to characterize the mechanism of the solvent extraction and to examine the extraction of the competing species, TcO(HSO 4 )+ and TcOSO 4 , into the organic phase. The apparent stability constant log 10 β app for the complexation of Tc(IV) by sulfate was found to be 1.13 ± 0.04.

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

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

Abstract We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗