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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗
DOE OSTI2023

Experimenting in the cloud: The digital divide's impact on innovation

This paper builds on a recent National Science Foundation working paper that identified a strong association between cloud use and various types of innovation but did not consider whether 1) cloud adoption is a reliable indicator of the innovation orientation of a firm, or 2) cloud adoption enables various types of innovation. We estimate propensity score matching and endogenous treatment effect models to control for innovation orientation, producing evidence to test the second explanation. Here, findings support an enabling effect of the cloud on innovation providing concrete evidence of the adverse impact of the digital divide.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Validation and Verification of TEDS Facility HYBRID Modeling

The HYBRID modeling repository is an in-house developed library of models for selected integrated energy systems (IES) modelling. HYBRID models have been developed since 2015 to describe the physical operation of tightly coupled thermal systems including power generators, thermal transport systems, thermal storage, thermal-to-electric conversion systems, and other thermal applications. Here, validation and verification (V&V) capabilities are demonstrated using the Thermal Energy Distribution System (TEDS) at INL. Building upon prior work, the TEDS model has been updated and verified so that it better represents the installed system configuration and the operating control system. The model control system was changed to allow replication of actual experimental procedures. Experimental operations focusing primarily on thermocline tank performance were devised and performed. Several anomalies were found in the operation data of the experiment facility. V&V activities calibrating a selected input parameter are demonstrated on a single component as well as with a single parameter within the thermocline. Calibrating is then demonstrated on multiple components and a multi-parameter metric for the entire system. The validation methodology is successfully applied to validate the model with experimental data. It is also used to confirm a hypothesis behind one of the anomalies in experimental performance.

25 ENERGY STORAGE↗
DOE OSTI2021

Exploring the physics of cesium lead halide perovskite quantum dots via Bayesian inference of the photoluminescence spectra in automated experiment

The unique optoelectronic properties of metal halide perovskite quantum dots (QDs) make them promising candidates for applications in light-emitting diodes (LEDs), scintillators, and other photonic devices. The automated micropipetting synthesis platform equipped with an optical reader enables the opportunity for high throughput synthesis and photoluminescent (PL) characterization of metal halide perovskite QDs for the first time. Here, we explore the compositional dependence of the PL behavior and stability of the combinatorial library of cesium lead halide (CsPbX 3 ) perovskites QDs via the automated platform. To study the stability of synthesized QDs in the binary and ternary configurations, we study the time-dependent PL properties using previously developed machine learning analysis. Additionally, to systematically explore the PL behavior in the ternary CsPbX 3 QDs system, we introduce the Bayesian inference framework that allows the probabilistic fit of multiple models to the PL data and establishes both optimal model and model parameter robustly. Furthermore, these behaviors can be used as a control parameter for the navigation of the multidimensional compositional spaces in automated synthesis. Furthermore, this analysis shows the nonuniformity of the PL peak behavior in the ternary CsPbX 3 QDs system. Further, the analysis confirms narrow size distribution and good quality of CsPbBr 3 QDs alloyed with low concentrations of iodide and chloride. We note that Bayesian Inference fit parameters can be further used as a control signal for navigation of the chemical spaces in automated synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermo-Fluid Modeling Framework for Supercomputing Digital Twins: Part 2, Automated Cooling Models

The development of digital twins for the purpose of improving the energy efficiency of supercomputing facilities is a non-trivial endeavor that is complicated by the difficulty of creating physics-based thermo-fluid cooling system models (CSMs). Within ExaDigit---an open-source framework for liquid-cooled supercomputing digital twins---a thermo-fluid modeling framework is being developed. This effort has been segmented into two with two companion papers describing each portion of the overall effort. Part 1 focuses on the development of a cooling system library in Dymola for the Frontier supercomputer at Oak Ridge National Laboratory {\cite{Kumar2024}. Part 2, this paper, describes an effort to create a template-based auto-generation methodology for CSMs, called \textit{AutoCSM}. In this paper, an overview of the initial AutoCSM architecture and workflow is provided, along with a practical example using the Oak Ridge Leadership Computing Facility's (OLCF) Frontier supercomputer CSM. AutoCSM will (1) improve ExaDigiT's user accessibility by providing a flexible workflow for modularizing the creation of the CSM system and control logic, (2) decrease the development time of CSMs, and (3) standardize the method for incorporating CSMs into the ExaDigiT framework.

Greenwood, Scott↗
DOE OSTI2021

Distribution Grid Modeling Using Smart Meter Data

The knowledge of distribution grid models, including topologies and line impedances, is essential for grid monitoring, control and protection. However, such information is often unavailable, incomplete or outdated. The increasing deployment of smart meters (SMs) provides a unique opportunity to tackle this issue. This paper proposes a two-stage framework for distribution grid modeling using SM data. In the first stage, the network topology is identified by reconstructing a weighted Laplacian matrix of distribution networks. In the second stage, a least absolute deviations (LAD) regression model is developed for estimating line impedance of a single branch based on the nonlinear (inverse) power flow model, wherein a conductor library is leveraged to narrow down the solution space. The LAD regression model is originally a mixed-integer nonlinear program whose continuous relaxation is still non-convex. Furthermore, we specially address its convex relaxation and discuss the exactness. The modified regression model is then embedded within a bottom-up sweep algorithm to achieve the identification across the network in a branch-wise manner. Numerical results on the IEEE 13-bus, 37-bus and 69-bus test feeders validate the effectiveness of the proposed methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

ResStock™ v3.2.0 [SWR-19-15 and SWR-20-07]

The ResStock™ analysis tool was built on NREL's OpenStudio® platform, and is a project geared at modeling existing residential building stocks at national, regional, or local scales with a high-degree of granularity (e.g., one physics-based simulation model for every 200 dwelling units), using the EnergyPlus® simulation engine. Information about ComStock™, a sister tool for modeling the commercial building stock, can be found here: https://www.nrel.gov/buildings/comstock.html This repository contains: Housing characteristics of the U.S. residential building stock, in the form of conditional probability distributions stored as tab-separated value (.tsv) files. Comments at the bottom of each file document data sources and assumptions for each. A library of housing characteristic "options" that translate high-level characteristic parameters into arguments for OpenStudio measures, and which are referenced by the housing characteristic .tsv files and building energy upgrades defined in project definition files Project definition files: v2.3.0 and later: buildstockbatch YML files openable in any text editor v2.2.5 and prior: Project folder openable in PAT Unit-level OpenStudio Measures for automatically constructing OpenStudio Models of each representative dwelling unit model: v3.0.0 and later: OpenStudio-HPXML Measures v2.5.0 and prior: OpenStudio Measures Higher-level OpenStudio Measures for controlling simulation inputs and outputs This repository does not contain software for running ResStock simulations, which can be found as follows: Versions 2.3.0 and later only support the use of buildstockbatch for deploying simulations on high-performance or cloud computing. Version 2.3.0 also removed separate projects for single-family detached and multifamily buildings, in lieu of a combined project_national representing the U.S. residential building stock. See the changelog for more details. Versions 2.2.5 and prior support the use of the publicly available OpenStudio-PAT software as an interface for deploying simulations on cloud computing. Read the documentation for v2.2.5.

Horowitz, Scott↗
DOE OSTI2024

Cystine-knot peptide inhibitors of HTRA1 bind to a cryptic pocket within the active site region

Cystine-knot peptides (CKPs) are naturally occurring peptides that exhibit exceptional chemical and proteolytic stability. We leveraged the CKP carboxypeptidase A1 inhibitor as a scaffold to construct phage-displayed CKP libraries and subsequently screened these collections against HTRA1, a trimeric serine protease implicated in age-related macular degeneration and osteoarthritis. The initial hits were optimized by using affinity maturation strategies to yield highly selective and potent picomolar inhibitors of HTRA1. Crystal structures, coupled with biochemical studies, reveal that the CKPs do not interact in a substrate-like manner but bind to a cryptic pocket at the S1’ site region of HTRA1 and abolish catalysis by stabilizing a non-competent active site conformation. The opening and closing of this cryptic pocket is controlled by the gatekeeper residue V221, and its movement is facilitated by the absence of a constraining disulfide bond that is typically present in trypsin fold serine proteases, thereby explaining the remarkable selectivity of the CKPs. Our findings reveal an intriguing mechanism for modulating the activity of HTRA1, and highlight the utility of CKP-based phage display platforms in uncovering potent and selective inhibitors against challenging therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

MALDI-MS screening of microbial colonies with isomer resolution to select fatty acid desaturase variants

Creating controlled lipid unsaturation locations in oleochemicals can be a key to many bioengineered products. However, evaluating the effects of modifications to the acyl-ACP desaturase on lipid unsaturation is not currently amenable to high-throughput assays, limiting the scale of redesign efforts to <200 variants. Here, we report a rapid MS assay for profiling the positions of double bonds on membrane lipids produced by Escherichia coli colonies after treatment with ozone gas. By MS measurement of the ozonolysis products of Δ6 and Δ8 isomers of membrane lipids from colonies expressing recombinant Thunbergia alata desaturase, we screened a randomly mutagenized library of the desaturase gene at 5 s per sample. Two variants with altered regiospecificity were isolated, indicated by an increase in 16:1 Δ8 proportion. We also demonstrated the ability of these desaturase variants to influence the membrane composition and fatty acid distribution of E. coli strains deficient in the native acyl-ACP desaturase gene, fabA. Lastly, we used the fabA deficient chassis to concomitantly express a non-native acyl- ACP desaturase and a medium-chain thioesterase from Umbellularia californica, demonstrating production of only saturated free fatty acids.

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

Data for MALDI-MS Screening of Microbial Colonies With Isomer Resolution to Select Fatty Acid Desaturase Variants

Creating controlled lipid unsaturation locations in oleochemicals can be a key to many bioengineered products. However, evaluating the effects of modifications to the acyl-ACP desaturase on lipid unsaturation is not currently amenable to high-throughput assays, limiting the scale of redesign efforts to <200 variants. Here, we report a rapid mass spectrometry (MS) assay for profiling the positions of double bonds on membrane lipids produced by Escherichia coli colonies after treatment with ozone gas. By MS measurement of the ozonolysis products of Δ6 and Δ8 isomers of membrane lipids from colonies expressing recombinant Thunbergia alata desaturase, we screened a randomly mutagenized library of the desaturase gene at 5 s per sample. Two variants with altered regiospecificity were isolated, indicated by an increase in 16:1 Δ8 proportion. We also demonstrated the ability of these desaturase variants to influence the membrane composition and fatty acid distribution of E. coli strains deficient in the native acyl-ACP desaturase gene, fabA. Finally, we used the fabA deficient chassis to concomitantly express a non-native acyl-ACP desaturase and a medium-chain thioesterase from Umbellularia californica, demonstrating production of only saturated free fatty acids.

Conversion↗
DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Exploring the Nature of f-Element Soft Donor Interactions Using Electronically Tunable Azolate Ionic Liquids

This project was undertaken to advance the understanding of how f-elements interact with moderately soft donors, a heavily investigated yet open question which is of prime importance in spent nuclear fuel processing and fundamental inorganic chemistry. During the course of the project, based on exciting results, a stretch goal was developed to study the hydrolysis products of transuranic actinide metals, a somewhat understudied field even with its significance in nuclear fuel cycle and impacts in environmental chemistry. The stretch goal was to take our serendipitous discovery of an easy route to isolation of crystalline multinuclear ƒ-element hydrolysis products, and apply it to gaining a mechanistic understanding of Pu(III/IV) colloid formation. The simplicity of our techniques should lend themselves to the remote handling required for study of many transuranic elements. We developed several methodologies using azolium azolate chemistry to overcome ƒ-element hydrolysis problems that prohibit the isolation of ƒ-element soft donor complexes and to build a crystallographic library of ƒ-element N-donor complexes as a means to understand the fundamental differences between actinide and lanthanide interactions with moderately soft donor ligands. Our next major endeavor will be to transfer this chemistry from 4ƒ elements to transuranic elements, particularly in the study of hydrolysis of Pu(III/IV). While our work is fundamental in nature, applications of the knowledge we are generating should be felt in such diverse fields as catalysis, separations in general, nuclear waste remediation specifically, and many other applications in f-element magnetic and luminescent properties. The potential ramifications of the consistent and robust formation of hydrolysis controlled hexanuclear lanthanide structures are enormous, with future uses being catalyst formation, higher-nuclearity structure synthesis using our hexanuclear motif as a fundamental building block, Pu waste remediation, separations, and many other potential applications resulting from characteristic magnetic and luminescent properties of lanthanide polynuclear structures. Three synthetic methodologies (direct mixing with variable stoichiometries, use of volatile solvent, metathesis) were developed starting with 7 acidic and 6 basic azoles to obtain ionic liquids suitable for f-element coordination. Proton transfer by acidic/basic azole combination led to suitable low melting salts and two cocrystals. Acid/base reaction of azoles with soft-donor permanent cations of ([X 4444 ][OH] (where [X 4444 ] + = tetrabutylammonium [N 4444 ] + or tetrabutylphosphonium [P 4444 ] + ) with weakly acidic azoles including imidazole, 1,2,3-triazole, 1,2,4-triazole, 5-aminotetrazole, 4,5-dicyanoimidazole, and 2-amino-4,5-dicyanoimidazole) revealed several suitable low-melting salts. Metathesis reactions of Na(azolate) were conducted by first using weakly acidic azoles including 4,5-dicyanoimidazole, 2-amino-4,5-dicyanoimidazole, 5-aminotetrazole, and 1,2,4-triazole to form sodium or lithium salts using group(I) hydroxides in methanolic solutions. The best results were obtained by reacting the basic and acidic azoles directly in 1:1 or 3:1 ratios at elevated temperatures. Twenty-two azole mixtures were identified which are either low melting solids or room temperature liquids. Each of the low melting solids was confirmed to be a new solid phase, each of which is being further characterized. The liquids and solids are anticipated to be ILs, eutectics, or partially ionized systems, all of which will be suitable for the dissolution of f-element salts. Five new synthetic methodologies were developed to finding suitable crystallization conditions for f-element complexation with the goal of finding simple one pot reaction syntheses and crystallization strategies that could be used under the demanding conditions of transuranic chemistries. These synthetic methods yield many new crystalline phases which were studied by single crystal X-ray diffraction.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

From CAN to ROS: A Monitoring and Data Recording Bridge

The Controller Area Network (CAN) bus protocol is used in modern vehicles for sharing messages between several control units within a vehicle. CAN bus messages are encoded with unknown scheme and decoding these messages provide unlimited access to valuable information that is used in many autonomous vehicles applications. This paper proposes a ROS based package (CAN-to-ROS) for monitoring, recording, and real-time and offline decoding of CAN bus messages. The package is developed in the ROS framework to add modularity and ease of integration with other software, and it is written in C++ to guarantee speed of the execution during run-time. For realtime decoding of CAN bus data, CAN-to-ROS package used in conjunction with other library called Libpanda that provide access to CAN bus message from a vehicle. The package was evaluated and tested on a Raspberry Pi with real CAN bus data from a Toyota RAV4. The results confirm the capabilities of CAN-to-ROS package and resulted in using the package in other research projects.

Elmadani, Safwan↗
DOE OSTI2021

Mid Infra-Red Laser Sensor for Continuous Sulfur Trioxide Monitoring to Improve Coal-Fired Power Plant Performance during Flexible Operations

During the course of this project, we performed exhaustive research and development of SO3/H2SO4 sensing technology for coal-fired power plant applications (Figure 1). The development culminated in a successful field campaign of a prototype continuous real-time H2SO4 monitor at a coal-fired power plant (TRL 6) accomplishing the primary goal of the project. The developed sensors utilize tunable laser absorption spectroscopy (TLAS) operating in the mid-infrared (Mid-IR) wavelength region, which is the so-called “molecular fingerprint” region. Systems operating in the Mid-IR have orders of magnitude more sensitivity than systems operating at shorter wavelengths, such as near-infrared (NIR). However, NIR systems are more widespread due to more mature supporting technology (e.g., fiber optics, optical components, etc.). In this project, we not only produced a specific Mid-IR sensor, we also advanced Mid-IR sensor technology in general through the development and demonstration of such supporting technology. In this project, we also developed proprietary broad tuning lasers enabling the ability to effectively measure SO3, H2SO4, H2O, and SO2. Different molecular species have unique spectral signatures that can be probed with lasers operating at different wavelengths. Standard TLAS uses relatively narrow wavelength tuning distributed feedback (DFB) lasers, which can typically only target a single species with narrow features, and are not appropriate for species with broad features, such as SO3 or H2SO4. In contrast, by developing unique, broad-tuning laser technology, we were able to measure these species, as well as SO2 and H2O simultaneously. Furthermore, to enable real-time analysis at a power plant, we modified a commercially available heated gas cell to operate in the Mid-IR wavelength range and fiber coupled the lasers to enable remote delivery of the beams. To generate reference data (library spectra), our collaborators at the University of California Irvine (UCI) developed a catalytic SO3 generation facility. It is worth mentioning that representative H2SO4 and SO3 Mid-IR spectra are not a part of any publicly available database and the data generated under this project is a valuable resource in and of itself. In addition, based on the UCI study we determined that detection of SO3 is complicated by the very strong SO2 absorption. For that reason, we concentrated on H2SO4 detection. Since SO3 and H2SO4 exist in a flue gas in a state of equilibrium, which depends on temperature and humidity, by measuring water concentration and controlling the temperature of the gas cell, we developed an approach to determine SO3 concentration from the H2SO4 measurement. During the development phase of the project, we performed three testing campaigns at our collaborator’s FERCo flue gas facility with conditions representative of the coal-fired power plant (~ 40ppm SO3, 1700ppm to 2800 ppm SO2, 10% water) with the exception of particulate matter. After three test campaigns at FERCo we performed field testing at Harrison Power Station. The final system was mounted on a duct and measured H2SO4, SO2 and water. The tests were highly successful with a demonstrated real-time H2SO4 precision of 1 ppm with a 1 second update. Our collaborators at EPRI conducted an industry survey and determined that there is a very high interest for the SO3/H2SO4 monitoring in the power generation industry as well as in heavy industries in general. Furthermore, work performed by OptoKnowledge beyond the scope of this project under a synergistic DOE SBIR determined another approach to SO3 detection. We applied for Phase II on this SBIR for development a of versatile SO3/H2SO4 sensor but were not selected. We are currently looking for another opportunity to leverage all the technological advancements produced by this project including but not limited to the flue gas facility at UCI, the hardware and software developed, and relationships with FERCo, EPRI CEMTEK, and Harrison Station.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.

Pratiush, Utkarsh [Univ. of Tennessee, Knoxville, ↗
DOE OSTI2020

Effects of composition and pressure on electronic states of iron in bridgmanite

Electronic states of iron in the lower mantle's dominant mineral, (Mg,Fe,Al)(Fe,Al,Si)O 3 bridgmanite, control physical properties of the mantle including density, elasticity, and electrical and thermal conductivity. However, the determination of electronic states of iron has been controversial, in part due to different interpretations of Mössbauer spectroscopy results used to identify spin state, valence state, and site occupancy of iron. We applied energy-domain Mössbauer spectroscopy to a set of four bridgmanite samples spanning a wide range of compositions: 10–50% Fe/total cations, 0–25% Al/total cations, 12–100% Fe 3+ /total Fe. Measurements performed in the diamond-anvil cell at pressures up to 76 GPa below and above the high to low spin transition in Fe 3+ provide a Mössbauer reference library for bridgmanite and demonstrate the effects of pressure and composition on electronic states of iron. Results indicate that although the spin transition in Fe 3+ in the bridgmanite B-site occurs as predicted, it does not strongly affect the observed quadrupole splitting of 1.4 mm/s, and only decreases center shift for this site to 0 mm/s at ~70 GPa. Thus center shift can easily distinguish Fe 3+ from Fe 2+ at high pressure, which exhibits two distinct Mössbauer sites with center shift ~1 mm/s and quadrupole splitting 2.4–3.1 and 3.9 mm/s at ~70 GPa. Correct quantification of Fe 3+ /total Fe in bridgmanite is required to constrain the effects of composition and redox states in experimental measurements of seismic properties of bridgmanite. Furthermore, in Fe-rich, mixed-valence bridgmanite at deep-mantle-relevant pressures, up to ~20% of the Fe may be a Fe 2.5+ charge transfer component, which should enhance electrical and thermal conductivity in Fe-rich heterogeneities at the base of Earth's mantle.

58 GEOSCIENCES↗
DOE OSTI2021

Zinc binding alters the conformational dynamics and drives the transport cycle of the cation diffusion facilitator YiiP

YiiP is a secondary transporter that couples Zn 2+ transport to the proton motive force. Structural studies of YiiP from prokaryotes and Znt8 from humans have revealed three different Zn 2+ sites and a conserved homodimeric architecture. These structures define the inward-facing and outward-facing states that characterize the archetypal alternating access mechanism of transport. To study the effects of Zn 2+ binding on the conformational transition, we use cryo-EM together with molecular dynamics simulation to compare structures of YiiP from Shewanella oneidensis in the presence and absence of Zn 2+ . To enable single-particle cryo-EM, we used a phage-display library to develop a Fab antibody fragment with high affinity for YiiP, thus producing a YiiP/Fab complex. To perform MD simulations, we developed a nonbonded dummy model for Zn 2+ and validated its performance with known Zn 2+ -binding proteins. Using these tools, we find that, in the presence of Zn 2+ , YiiP adopts an inward-facing conformation consistent with that previously seen in tubular crystals. After removal of Zn 2+ with high-affinity chelators, YiiP exhibits enhanced flexibility and adopts a novel conformation that appears to be intermediate between inward-facing and outward-facing states. This conformation involves closure of a hydrophobic gate that has been postulated to control access to the primary transport site. Comparison of several independent cryo-EM maps suggests that the transition from the inward-facing state is controlled by occupancy of a secondary Zn 2+ site at the cytoplasmic membrane interface. This work enhances our understanding of individual Zn 2+ binding sites and their role in the conformational dynamics that govern the transport cycle.

59 BASIC BIOLOGICAL SCIENCES↗