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DOE OSTI2026

Improving ProtoDUNE pion cross-section measurements with NuGraph Michel-electron tagging

Understanding hadron-argon interactions is essential for precise neutrino energy reconstruction and final-state interaction modeling in liquid-argon time projection chamber (LArTPC) experiments such as DUNE. In particular, pion absorption and charge-exchange processes constitute significant sources of systematic uncertainty in neutrino oscillation measurements. ProtoDUNE-SP, a large-scale LArTPC prototype operated at the CERN Neutrino Platform and exposed to charged-particle test beams in the few-GeV range, enables direct measurements of these processes. This work focuses on the measurement of differential cross sections for pion absorption and charge exchange using the 2 GeV/c pion beam data from the ProtoDUNE-SP run. A key component of this analysis is the identification of Michel electrons from $\pi \rightarrow \mu \rightarrow e$ decay chains, which helps separate different interaction topologies and improves background rejection. Michel electron identification will also assist in reliably calibrating the electromagnetic response in ProtoDUNE-SP data and for the future DUNE detectors. In this analysis, we apply NuGraph to identify Michel electrons. NuGraph is a graph neural network that models detector hits as nodes connected by spatial and temporal edges for particle and topology classification in LArTPC detectors. We first benchmark NuGraph’s Michel electron classification performance using ICEBERG data, a small-scale LArTPC prototype used for DUNE electronics and reconstruction development, and then transfer the approach to ProtoDUNE-SP. This poster presents the analysis strategy, NuGraph-based classification studies, and discusses how these developments are expected to improve the pion cross-section measurement.

Razafinime, Soamasina Herilala [Cincinnati U.] (OR↗

DOE OSTI2025

Technical, Economic, Energetic, and Environmental Evaluation of Pretreatment Strategies for Scaling Control in Brackish Water Desalination Brine Treatment

Effective pretreatment is essential for achieving long-term stable operation and high water recovery during the desalination of alternative waters. This study developed a process modeling approach for technical, economic, energetic, and environmental assessments of pretreatment technologies to identify the impacts of each technology treating brackish water desalination brine with high scaling propensity. The model simulations evaluated individual pretreatment technologies, including chemical softening (CS), chemical coagulation (CC), electrocoagulation (EC), and ion exchange (IX). In addition, combinations of these pretreatment technologies aiming at the effective reduction of key scaling constituents such as hardness and silica were investigated. The three evaluation parameters in this assessment consist of levelized cost of water (LCOW, $/m 3 ), specific energy consumption and cumulative energy demand (SEC|CED, kWh/m 3 ), and carbon dioxide emissions (CO 2 , kg CO 2-eq /m 3 ). The case study evaluated in this work was the desalination brine from the Kay Bailey Hutchison Desalination Plant (KBHDP) with a total dissolved solids (TDS) concentration of 11,000 mg/L and rich in hardness and silica. The evaluation of individual pretreatment units from the highest to lowest LCOW, SEC|CED, and CO 2 emissions in the KBHDP brine was IX > CS > EC > CC, CS > IX > EC > CC, and CC > CS > EC > IX, respectively. In the case of pretreatment combinations for the KBHDP, the EC + IX treatment combination was shown to be the best in terms of the LCOW and CO 2 emissions. The modeling and evaluation of these pretreatment units provide valuable guidance on the selection of cost-effective, energy-efficient, and environmentally sustainable pretreatment technologies tailored to desalination brine applications for minimal- or zero-liquid discharge.

14 SOLAR ENERGY↗

DOE OSTI2024

Developing a Transferable Framework for CO2-Stimulated Geothermal Energy Enhancement: A Case Study

This is the conference paper accompanying a poster presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. In this paper, we present innovative technologies to image key features, including CO₂-stimulated fracture imaging, CO₂ fluid sweep imaging and heat transfer and exchange imaging by leveraging multiple datasets and applying advanced AI/ML, multi-level data analytics, and data/information fusion to better understand the geothermal reservoir for enhanced recovery.

Liu, Guoxiang↗

DOE OSTI2024

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure–property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg 2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg 2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg 2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. In conclusion, this observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

25 ENERGY STORAGE↗

DOE OSTI2021

Oxygen Electrocatalysis on Mixed-Metal Oxides/Oxyhydroxides: From Fundamentals to Membrane Electrolyzer Technology

Catalyzing the oxygen evolution reaction (OER) is important for key energy-storage technologies, particularly water electrolysis and photoelectrolysis for hydrogen fuel production. Under neutral-to-alkaline conditions, first-row transition-metal oxides/(oxy)hydroxides are the fastest-known OER catalysts and have been the subject of intense study for the past decade. Critical to their high performance is the intentional or accidental addition of Fe to Ni/Co oxides that convert to layered (oxy)hydroxide structures during the OER. Unraveling the role that Fe plays in the catalysis and the molecular identity of the true “active site” has proved challenging, however, due to the dynamics of the host structure and absorbed Fe sites as well as the diversity of local structures in these disordered active phases. In this Account, we highlight our work to understand the role of Fe in Ni/Co (oxy)hydroxide OER catalysts. We first discuss how we characterize the intrinsic activity of the first-row transition-metal (oxy)hydroxide catalysts as thin films by accounting for the contributions of the catalyst-layer thickness (mass loading) and electrical conductivity as well as the underlying substrate’s chemical interactions with the catalyst and the presence of Fe species in the electrolyte. We show how Fe-doped Ni/Co (oxy)hydroxides restructure during catalysis, absorb/desorb Fe, and in some cases degrade or regenerate their activity during electrochemical testing. We highlight the relevant techniques and procedures that allowed us to better understand the role of Fe in activating other first-row transition metals for OER. We find several modes of Fe incorporation in Ni/Co (oxy)hydroxides and show how those modes correlate with activity and durability. We also discuss how this understanding informs the incorporation of earth-abundant transition-metal OER catalysts in anion-exchange-membrane water electrolyzers (AEMWE) that provide a locally basic anode environment but run on pure water and have advantages over the more-developed proton-exchange-membrane water electrolyzers (PEMWE) that use platinum-group-metal (PGM) catalysts. We outline the key issues of introducing Fe-doped Ni/Co (oxy)hydroxide catalysts at the anode of the AEMWE, such as the oxidative processes triggered by Fe species traveling through the polymer membrane, pH-gradient effects on the catalyst stability, and possibly limited catalyst utilization in the compressed stack configuration. We also suggest possible mitigation strategies for these issues. Lastly, we summarize remaining challenges including the long-term stability of Fe-doped Ni/Co (oxy)hydroxides under OER conditions and the lack of accurate models of the dynamic active surface that hinder our understanding of, and thus ability to design, these catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Adaptations for gas exchange enabled the elongation of lepidopteran proboscises

The extensive biodiversification of butterflies and moths (Lepidoptera) is partly attributed to their unique mouthparts (proboscis [Pr]) that can span in length from less than 1 mm to over 280mm in Darwin's sphinx moths. Lepi-doptera, similar to other insects, are believed to inhale and exhale respiratory gases only through valve-like spi-racles on their thorax and abdomen, making gas exchange through the narrow tracheae (Tr) challenging for the elongated Pr. How Lepidoptera overcome distance effects for gas transport to the Pr is an open question that is important to understanding how the Pr elongated over evolutionary time. Here, we show with scanning electron microscopy and X-ray imaging that distance effects on gas exchange are overcome by previously unreported micropores on the Pr surface and by superhydrophobic Tr that prevent water loss and entry. We find that the density of micropores decreases monotonically along the Pr length with the maxima proportional to the Pr length and that micropore diameters produce a Knudsen number at the boundary between the slip and transition flow regimes. By numerical estimation, we further show that the respiratory gas exchange for the Pr predominantly occurs via diffusion through the micropores. In conclusion, these adaptations are key innovations vital to Pr elongation, which likely facilitated lepidopteran biodiversification and the radiation of angiosperms by coevolutionary processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Solution and Interface Structure and Dynamics in Geochemistry: Gateway to Link Elementary Processes to Mineral Nucleation and Growth

Our understanding of the process of mineral nucleation is starting to evolve from the solely thermodynamical aspects in classical nucleation theory toward a mechanistic study of reactions influenced by solvation structures of ions and their dynamics. A knowledge of how these atomic and molecular interactions respond to changing solution composition and/or the nature of an interface will form a fundamental foundation to understand rate-limiting reactions and processes for nucleation and growth. Here, we review recent advances from multidisciplinary experimental and computational approaches of the structure and dynamics of aqueous solutions and mineral–liquid interfaces that will influence rates of nucleation (and growth behavior) both homogeneously in aqueous solutions and heterogeneously at mineral–liquid interfaces. Furthermore, these processes include structure (and extent) of solute clustering, solvent degrees of freedom, and the presence of noninnocent charge-balancing ions, all of which can drive the selectivity and exert control over nucleation mechanisms. Similar controlling reactions can also occur at interfaces with the added complexities of how solute ions interact with and assemble on surface sites and use different mechanisms from bulk solutes, such as lateral solvent exchanges between distinct surface sites. To gain a predictive understanding of nucleation chemistry, we emphasize several key knowledge gaps that will need to be addressed in this field and highlight the importance of combining computations and experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Continuum Model to Define the Chemistry and Mass Transfer in a Bicarbonate Electrolyzer

Bicarbonate electrolyzers are devices designed to convert CO 2 captured from point sources or the atmosphere into chemicals and fuels without needing to first isolate pure CO 2 gas. In this work, we report here an experimentally validated model that quantifies the reaction chemistry and mass transfer processes within the catalyst layer and cation exchange membrane layer of a bicarbonate electrolyzer. Our results demonstrate that two distinct chemical microenvironments are key to forming CO at high rates: an acidic membrane layer that promotes in situ CO 2 formation and a basic catalyst layer that suppresses the hydrogen evolution reaction. We show that the rate of CO product formation can be increased by modulating the catalyst and membrane layer properties to increase the rate of in situ CO 2 generation and transport to the cathode. These insights serve to inform the design of bicarbonate and BPM-based CO 2 electrolyzers while demonstrating the value of modeling for resolving rate-determining processes in electrochemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Machine learning-assisted crystal engineering of a zeolite

Abstract It is shown that Machine Learning (ML) algorithms can usefully capture the effect of crystallization composition and conditions (inputs) on key microstructural characteristics (outputs) of faujasite type zeolites (structure types FAU, EMT, and their intergrowths), which are widely used zeolite catalysts and adsorbents. The utility of ML (in particular, Geometric Harmonics) toward learning input-output relationships of interest is demonstrated, and a comparison with Neural Networks and Gaussian Process Regression, as alternative approaches, is provided. Through ML, synthesis conditions were identified to enhance the Si/Al ratio of high purity FAU zeolite to the hitherto highest level (i.e., Si/Al = 3.5) achieved via direct (not seeded), and organic structure-directing-agent-free synthesis from sodium aluminosilicate sols. The analysis of the ML algorithms’ results offers the insight that reduced Na 2 O content is key to formulating FAU materials with high Si/Al ratio. An acid catalyst prepared by partial ion exchange of the high-Si/Al-ratio FAU (Si/Al = 3.5) exhibits improved proton reactivity (as well as specific activity, per unit mass of catalyst) in propane cracking and dehydrogenation compared to the catalyst prepared from the previously reported highest Si/Al ratio (Si/Al = 2.8).

36 MATERIALS SCIENCE↗

DOE OSTI2023

Evaluating E. coli genome‐scale metabolic model accuracy with high‐throughput mutant fitness data

Abstract The Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

DSO+T: Valuation Methodology and Economic Metrics (DSO+T Study: Volume 4)

This report summarizes a rigorous valuation analysis methodology used by the Distribution System Operator with Transactive (DSO+T) study to estimate the financial benefits and costs of adopting Transactive Energy coordination of distributed energy resources for key stakeholders (for example distribution system operators and customers). This was achieved by modeling the value exchanges between stakeholders and determining the annualized costs and revenues experienced by stakeholders, enabling the evaluation of overall impact on stakeholder’s annualized cash flow. Extensive work was conducted developing methods to estimate the operating costs of distribution system operators at a level of granularity that would allow the financial impact of implementing a transactive energy approach to be estimated. This work included developing parametric models for labor and software costs, distribution system capital and maintenance costs, growth rates, and factors to determine annualized costs of capital investments. Simulation results were used to calculate wholesale energy costs and revenues from retail sales. Valuation analysis methods were also developed for other stakeholders including customers, the transmission system operator, independent system operator, and generators. The resulting capability allows a complete mapping of the flow of financial value between stakeholders that can be directly integrated with the results of demand flexibility simulations. Example results are provided for a business-as-usual case and compared to a transactive energy case as well as to actual cost data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Ionomer Optimization for Water Uptake and Swelling in Anion Exchange Membrane Electrolyzer: Hydrogen Evolution Electrode

Green hydrogen produced through anion exchange membrane water electrolysis is a promising, low-cost chemical storage solution for intermittent renewable energy sources. Low-temperature electrolysis using anion exchange membranes (AEM) combines the benefits of established water electrolysis technologies based on alkaline electrolysis and proton exchange membrane electrolysis. The anion conductive ionomers (ACI) used in the AEM electrolyzer (AEMEL) electrodes has been investigated. The ACI serves two primary purposes: (i) facilitate hydroxide conduction between the catalyst and bulk electrolyte and (ii) bind the catalyst to the porous transport layer and membrane. High ion exchange capacity (IEC) ACIs are desired, however, high IEC can cause excessive water uptake (WU) and detrimental ACI swelling. Proper water management is a key factor in obtaining maximum performance in AEM-based devices. In this study, a series of poly(norbornene)-based ACIs were synthesized and deployed in hydrogen evolving AEMEL cathode electrodes. A balance between ionic conductivity, WU and ionomer swelling was achieved in the ACI by varying the IEC and degree of polymer cross-linking. It was found that higher IEC ACIs with light crosslinking are preferred in the HER electrode. Furthermore, such a configuration fine-tuned the WU and ionomer swelling to achieve optimum cell performance and reduce cell operating voltages.

08 HYDROGEN↗

DOE OSTI2021

Characterizing mechanical and microstructural properties of novel montmorillonite-rich polyethylene composites

Montmorillonite (MMT) clays are important industrial materials used as catalysts, chemical sorbents and fillers in polymer–clay nanocomposites. The layered structure of these clays has motivated research into further applications of these low-cost materials, including use as ion exchange media and solid-state ionic conductors. In these applications, the mechanical properties of MMT are key when considering long-term, reliable performance. Previous studies have focused on the mechanical properties of nanocomposites with MMT as the minority component or pure MMT thin films. In this work, the microstructure and mechanical properties of pure MMT and majority MMT/polyethylene composites pressed into dense pellets are examined. Characterization methods such as X-ray diffraction, atomic force microscopy and scanning electron microscopy together with nanoindentation reveal important structure–property relationships in the clay-based materials. Here, utilizing these techniques, we have discovered that MMT processing impacts the layered microstructure, chemical stability and, critically, the elastic modulus and hardness of bulk MMT samples. Particularly, the density of the pellets and the ordering of the clay platelets within them strongly influence the elastic modulus and hardness of the pellets. By increasing pressing force or by incorporating secondary components, the density, and therefore mechanical properties, can be increased. If the layered structure of the clay is destroyed by exfoliation, the mechanical properties will be compromised. Understanding these relationships will help guide new studies to engineer mechanically stable MMT-based materials for industrial applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Century-long timelines of herbarium genomes predict plant stomatal response to climate change

Abstract Dissecting plant responses to the environment is key to understanding whether and how plants adapt to anthropogenic climate change. Stomata, plants’ pores for gas exchange, are expected to decrease in density following increased CO 2 concentrations, a trend already observed in multiple plant species. However, it is unclear whether such responses are based on genetic changes and evolutionary adaptation. Here we make use of extensive knowledge of 43 genes in the stomatal development pathway and newly generated genome information of 191 Arabidopsis thaliana historical herbarium specimens collected over 193 years to directly link genetic variation with climate change. While we find that the essential transcription factors SPCH, MUTE and FAMA, central to stomatal development, are under strong evolutionary constraints, several regulators of stomatal development show signs of local adaptation in contemporary samples from different geographic regions. We then develop a functional score based on known effects of gene knock-out on stomatal development that recovers a classic pattern of stomatal density decrease over the past centuries, suggesting a genetic component contributing to this change. This approach combining historical genomics with functional experimental knowledge could allow further investigations of how different, even in historical samples unmeasurable, cellular plant phenotypes may have already responded to climate change through adaptive evolution.

Environmental Sciences & Ecology↗

DOE OSTI2023

Mutual-information based optimal experimental design for hyperpolarized $$^{13}$$C-pyruvate MRI

Abstract A key parameter of interest recovered from hyperpolarized (HP) MRI measurements is the apparent pyruvate-to-lactate exchange rate, $$k_{{\textrm PL}}$$ k P L , for measuring tumor metabolism. This manuscript presents an information-theory-based optimal experimental design approach that minimizes the uncertainty in the rate parameter, $$k_{{\textrm PL}}$$ k P L , recovered from HP-MRI measurements. Mutual information is employed to measure the information content of the HP measurements with respect to the first-order exchange kinetics of the pyruvate conversion to lactate. Flip angles of the pulse sequence acquisition are optimized with respect to the mutual information. A time-varying flip angle scheme leads to a higher parameter optimization that can further improve the quantitative value of mutual information over a constant flip angle scheme. However, the constant flip angle scheme, 35 and 28 degrees for pyruvate and lactate measurements, leads to an accuracy and precision comparable to the variable flip angle schemes obtained from our method. Combining the comparable performance and practical implementation, optimized pyruvate and lactate flip angles of 35 and 28 degrees, respectively, are recommended.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

CO2-Locate: A Dynamic Database and Tool for Accessing National Oil and Gas Well Data to Inform Carbon Storage Projects

The CO2-Locate Database is a growing compilation of publicly available wellbore resources that have been merged based on common attributes across data sources with an attribute schema developed to be consistent across disparate resources, reduce data gaps, and eliminate record redundancy. The first version of CO2-Locate has been published to Energy Data eXchange (EDX) and includes the integrated public wells dataset as well as additional geospatial summary layers of key wellbore characteristics to protect proprietary resources. Additionally, the CO2-Locate database has been deployed into a web application, enabling easy access, data filtering capabilities, and visualization of U.S. wellbore infrastructure by stakeholders to inform injection site selection and risk assessments.

Dyer, Alec S. [NETL Site Support Contractor, Natio↗

DOE OSTI2020

A Community Energy Operations and Planning System: Concept, Use cases, Metrics, and Benefits

Community and city leaders are interested in achieving sustainability goals, providing resilient energy infrastructure, and improving economic competitiveness. Community-level data acquisition and analysis can provide energy and associated benefits that are not possible at the single building level. However, there is a lack of organizational structure, common semantic data models, interoperable systems, and methods to support data-driven decision-making for community-scale energy supply and demand systems. We explored the need and opportunity for a Community Energy Operations and Planning System (Community EOPS), a potential data exchange platform. We conducted “customer discovery” interviews, and reviewed literature, public tools, and technology platforms to identify key energy data “users” and use cases in communities. The key users of the Community EOPS could be developers of mixed-use districts, corporate, defense and university campus energy managers, and city managers of cities that own their energy utility. The value could be for community planning and reporting (for energy data-integrated land use planning and community infrastructure investments in microgrids, storage, district heating and cooling), energy efficiency (leveraging optimizations for community scale energy supply and demand), flexible load management (grid-edge load management to offset, shift, and flatten loads for multiple buildings and EV fleets), cost savings and revenue generation (participating in grid services), and social benefits such as energy resilience, equity, and awareness. We developed a conceptual Community EOPS architecture with recommendations for streamlined and prioritized data acquisition, sharing, and integration driven by prioritized use cases, common metrics, and actionable visualizations that can provide value to a community’s users.

Singh, Reshma↗

DOE OSTI2021

Implementation of quantum key distribution and quantum clock synchronization via time bin encoding

Quantum key distribution allows for a provably secure transmission of cryptographic keys over an optical channel. Encoded polarization states or time-bin degree of freedom have been used for successful demonstrations. However, photon losses in long fibers, slow single photon detectors, and detector dark counts significantly limit the overall bit rate. Improving key throughput and reducing the overhead of key reconciliation remain as major challenges. Methods which utilize multiple time bins allow for multiple key bits to be encoded in a single photon, thus increasing the fidelity of transmitted keys and decreasing the overhead of key reconciliation in real-world conditions. Previous implementations of these methods required that Alice and Bob share a time reference by sharing a dedicated classical channel used for synchronization. This work presents a technique that allows two parties to exchange time-bin encoded photons without the need for synchronized time references. Our technique uses a framing protocol which allows Alice to encode a time reference along with a key which is determined by Alice before transmission. Security can be achieved by monitoring the visibility of a pair of Franson interferometers, using decoy pulses and measuring the round trip time between Alice and Bob. The bit rate of this technique is limited only by the recovery time of the detector and the speed of the modulation electronics. We experimentally demonstrate a raw bit rate of 5Mb/s over an optical channel with 55dB of loss, which is competitive with current research. We also demonstrate absolute timing synchronization with an accuracy of 20ps.

encryption↗