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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A stilbene–strontium iodide based radioxenon detection system for monitoring nuclear explosions

Atmospheric measurement of noble gases has been extensively used for monitoring clandestine nuclear weapon explosions for many years. The ratios of four xenon isotopes of interest ( 131 mXe, 133 mXe, 133 Xe, and 135 Xe) help in discriminating regular reactor operations from nuclear tests. A new coincidence-based detection system using stilbene and strontium iodide [SrI 2 (Eu)] for electron and photon detection respectively was developed at Oregon State University to address some of the challenges of the radioxenon systems deployed in the field such as memory effect, and poor energy resolution. Silicon photomultipliers (SiPMs) were used for sensing optical photons from all scintillation media. Real-time coincidence identification was achieved using the eight-channel digital pulse processor. The detection system was evaluated using lab check sources and Oregon State TRIGA reactor irradiated radioxenon samples. A 48-hour background coincidence spectrum was collected yielding a coincidence count rate and background rejection rate of 0.0174 ± 0.0003 counts per second (cps) and 98.9% respectively. The minimum detectable concentration (MDC) of the system was evaluated to be 0.11 ± 0.01, 0.13 ± 0.02, 0.20 ± 0.02, and 0.73 ± 0.08 for 131 mXe, 133 mXe, 133 Xe, and 135 Xe respectively. The memory effect of the detection system was found to be 0.069 ± 0.015%, which is almost a 70-fold reduction compared to traditional plastic scintillators. Here, the detection elements, custom-designed electronics, and the detector response to radioxenon are detailed in this work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

DOE new players Carbon cycle (2016-2021)

The overarching scientific goals of our multidisciplinary grant was to further expand understanding about the key microorganisms (players), metabolic strategies (processes), and interspecies relationships (interactions) involved in the formation and oxidation of methane in the environment. This research applied novel environmental metagenomics, transcriptomics, and proteomic techniques, state-of-the-art analytical imaging, stable isotope geochemistry, and reaction-transport modeling to address these goals and develop an ‘ecosystems level’ understanding of the factors which regulate microbial methane cycling in anoxic sedimentary ecosystems. For decades, it was believed that the obligate step in methanogenesis catalyzed by methyl coenzyme M reductase (Mcr) was limited to a specific branch of the archaeal Domain, formerly known as the Euryarchaeota. Less than a decade ago co-I Tyson’s team published a surprising metagenomic-based discovery of divergent Mcr genes in a novel uncultured phylum (Bathyarchaeota), catalyzing a major shift in thinking about the diversity of microorganisms that encode the potential for methane (or higher alkane) metabolism in anoxic environments (Evans et al., 2015). In our work here, we further expand on the groups of archaea harboring the genomic potential for methane or hydrocarbon metabolism using environmental metagenomics and new gene targeted bioinformatics techniques. We additionally advanced understanding about the terminal electron acceptors and metabolic potential supporting the anaerobic oxidation of methane (AOM) in terrestrial ecosystems, specifically focused on new lineages of ANME archaea capable of respiring manganese oxides with methane presumably using large extracellular multi-heme cytochrome complexes. New details about specific syntrophic mechanisms underlying the exchange of electrons during sulfate-coupled methane oxidation between ANME-2 archaea and their sulfate-reducing bacterial partners were also elucidated as part of this funded project. Through a series of experimental ‘omics and single cell stable isotope probing studies with incubated environmental sediment samples and a cultured model electrogenic microorganism combined with model-based predictions. Combined, this work provides strong support for the hypothesis of direct interspecies electron transfer (DIET) is the dominant syntrophic mechanism controlling the anaerobic oxidation of methane with sulfate over other proposed mechanisms and additionally illustrates important spatial constraints and the underlying physico-chemical factors influencing AOM syntrophic consortia structure for DIET and extracellular metal respiration. This collaborative multi-institutional project successfully advanced several of our milestone goals including the identification of new microbial players containing methyl coenzyme M reductases hypothesized to be central to methane or hydrocarbon cycling in anoxic environments and enhancing fundamental knowledge about the role extracellular electron transfer plays in the ecophysiology of methanotrophic archaea respiring metal oxides and in the physical and metabolic structuring of syntrophic interactions in methane-rich sedimentary ecosystems.

03 NATURAL GAS↗
DOE OSTI2024

Threat Sources for Creating Synthetic Urban Search Data

Equivalent point source energy emission distributions were computed for various threat sources for use in simulating the detector responses for urban search scenarios. The sources include standard isotopic sources used in detector testing, medical and industrial sources occasionally encountered in urban searches, and several types of special nuclear materials. Most of the equivalent point source distributions represent small sources inside some amount of shielding, but the special nuclear material sources represent volumetrically distributed sources in spheres of metal. Text-based inputs for emission distributions are available for the Monte Carlo transport codes Monte Carlo N-Particle, SCALE/MAVRIC, and Omnibus/Shift, any of which can easily be converted to other formats. These sources were developed for use in the Radiological Anomaly Detection and Identification (RADAI) project and the follow-on project, the RADAI-Extended project, sponsored by the National Nuclear Security Administration Office of Defense Nuclear Nonproliferation Research and Development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A case study in contrastive learning information combination: Application to technical forensics of additive manufacturing filament source identification

Combination of information from disparate data sources into a single decision is a core challenge in many fields, including the field of technical forensics. Technical forensics (TF) utilizes technical characterization of questioned samples to determine properties of that sample; these properties are then used to infer information of forensic interest, such as provenance, age, or attribution. TF is utilized in traditional forensic applications, such as the attribution of material fragments from an explosive, and in nuclear forensic applications, such as the attribution of actinides which have been interdicted out of regulatory control. The challenge of combining information from disparate sources, described alternately by many terms including “Data Fusion” and “Data Integration”, is exacerbated in the technical forensics domain due to at least two factors: the challenge of interpreting each information source singularly, and the relatively small data set sizes available. Extensive literature exists attempting to combine technical forensics information sources, both in manual and automated processes. These attempts are often bespoke to the specific information sources (such as the bi-, tri-, or quad-isotope chart (Moody, Grant, and Hutcheon 2005)), with some emerging examples of simple early- and late- fusion (, respectively). Simultaneous to the information combination efforts described in the previous paragraph, the field of natural language processing attempted (and largely succeeded) in combining information from multiple non-technical information sources. The ecosystem of “multi-modal” language models, which can take text and images as input, and generate text and images as output, became large and diverse by 2025 (Khan et al. 2025). In a generalized sense, many of these methods are trained by learning neural networks which can convert raw text or images into a vector of numbers describing the text or image, hereafter called “embeddings” and the neural networks performing the conversion are called “embedders”. By using a separate embedder for text and images, finding coincident text and images (such as images with their captions), and optimizing the parameters of the embedders such that the embeddings for the text and the image are similar, the field has found a bridge between text and images (Girdhar et al. 2023). It is the contention of the authors of this report that this insight is not limited to text and images but instead can be extended to any modality which can be found coincidently. The subject of the rest of this report is the application of this method to example multi-modal technical forensic data. Some details about the data used in this report are not appropriate for this report, and are included in a companion report (PNNL-38669).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Unsupervised domain adaptation for radioisotope identification in gamma spectroscopy

Training machine learning models for radioisotope identification using gamma spectroscopy remains an elusive challenge for many practical applications, largely stemming from the difficulty of acquiring and labeling large, diverse experimental datasets. Simulations can mitigate this challenge, but the accuracy of models trained on simulated data can deteriorate substantially when deployed to an out-of-distribution operational environment. In this study, we demonstrate that unsupervised domain adaptation (UDA) can improve the ability of a model trained on synthetic data to generalize to a new testing domain, provided unlabeled data from the target domain are available. Conventional supervised techniques are unable to utilize this data because the absence of isotope labels precludes defining a supervised classification loss. Instead, we first pretrain a spectral classifier using labeled synthetic data and subsequently leverage unlabeled target data to align the learned feature representations between the source and target domains. We compare a range of different UDA techniques, finding that minimizing the maximum mean discrepancy (MMD) between source and target feature vectors yields the most consistent improvement to testing scores. For instance, using a custom transformer-based neural network, we achieved a testing accuracy of $0.904 \pm 0.022$ on an experimental LaBr test set after performing unsupervised feature alignment via MMD minimization, compared to $0.754 \pm 0.014$ before alignment. Overall, our results highlight the potential of using UDA to adapt a radioisotope classifier trained on synthetic data for real-world deployment.

Lalor, Peter W.↗
DOE OSTI2021

High-Current Light-Ion Cyclotron for Applications in Nuclear Security and Radioisotope Production

In this article, we propose the conceptual design, with supporting beam dynamics results, of a normal conducting, separated-sector cyclotron with a strong-focusing field gradient designed to accelerate light ions with a charge-to-mass ratio of 1/2 up to 15–20 MeV/u. The design can support a host of applications for therapy, radiobiology, material science, and instrumentation development. The light-ion species, which can include a mixed ion beam, can be dynamically chosen to provide a range of characteristic signals appropriate for specific material identification such as special nuclear materials. A conservative baseline concept is presented which has been optimized for radioisotope production of alpha emitters and theranostic radiopharmaceuticals. The modular design is also demonstrated to be scalable in gross physical parameters by a factor of 2–3, thereby reducing the size, weight, and power requirements (SWaP) and enabling near-term security applications.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

CUPID, the Cuore upgrade with particle identification

CUPID, the CUORE Upgrade with Particle Identification, is a next-generation experiment to search for neutrinoless double beta decay (0 νββ ) and other rare events using enriched Li 2 100 MoO 4 scintillating bolometers. It will be hosted by the CUORE cryostat located at the Laboratori Nazionali del Gran Sasso in Italy. The main physics goal of CUPID is to search for 0 νββ of 100 Mo with a discovery sensitivity covering the full neutrino mass regime in the inverted ordering scenario, as well as the portion of the normal ordering regime with lightest neutrino mass larger than 10 meV. With a conservative background index of 10 −4 cts/(keV·kg·yr), 240 kg isotope mass, 5 keV FWHM energy resolution at 3 MeV and 10 live-years of data taking, CUPID will have a 90% C.L. half-life exclusion sensitivity of 1.8 · 10 27 yr, corresponding to an effective Majorana neutrino mass ( m ββ ) sensitivity of 9–15 meV, and a 3σ discovery sensitivity of 1 · 10 27 yr, corresponding to an m ββ range of 12–21 meV.

Alfonso, K. [Virginia Polytechnic Institute and St↗
DOE OSTI2020

In Situ Identification of Reaction Intermediates and Mechanistic Understandings of Methane Oxidation over Hematite: A Combined Experimental and Theoretical Study

Effective methane utilization for either clean power generation or value-added chemical production has been a subject of growing attention worldwide for decades, yet challenges persist mostly in relation to methane activation under mild conditions. Here, we report hematite, an earth-abundant material, to be highly effective and thermally stable to catalyze methane combustion at low temperatures (<500 °C) with a low light-off temperature of 230 °C and 100% selectivity to CO 2 . The reported performance is impressive and comparable to those of precious-metal-based catalysts, with a low apparent activation energy of 17.60 kcal·mol –1 . Our theoretical analysis shows that the excellent performance stems from a tetra-iron center with an antiferromagnetically coupled iron dimer on the hematite (110) surface, analogous to that of the methanotroph enzyme methane monooxygenase that activates methane at ambient conditions in nature. Isotopic oxygen tracer experiments support a Mars van Krevelen redox mechanism where CH 4 is activated by reaction with a hematite surface oxygen first, followed by a catalytic cycle through a molecular-dioxygen-assisted pathway. Surface studies with in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and density functional theory (DFT) calculations reveal the evolution of reaction intermediates from a methoxy CH 3 –O–Fe, to a bridging bidentate formate b-HCOO–Fe, to a monodentate formate m-HCOO–Fe, before CO 2 is eventually formed via a combination of thermal hydrogen-atom transfer (HAT) and proton-coupled electron transfer (PCET) processes. Finally, the elucidation of the reaction mechanism and the intermediate evolutionary profile may allow future development of catalytic syntheses of oxygenated products from CH 4 in gas-phase heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Identification of the Tyrosine- and Phenylalanine-Derived Soluble Metabolomes of Sorghum

The synthesis of small organic molecules, known as specialized or secondary metabolites, is one mechanism by which plants resist and tolerate biotic and abiotic stress. Many specialized metabolites are derived from the aromatic amino acids phenylalanine (Phe) and tyrosine (Tyr). In addition, the improved characterization of compounds derived from these amino acids could inform strategies for developing crops with greater resilience and improved traits for the biorefinery. Sorghum and other grasses possess phenylalanine ammonia-lyase (PAL) enzymes that generate cinnamic acid from Phe and bifunctional phenylalanine/tyrosine ammonia-lyase (PTAL) enzymes that generate cinnamic acid and p -coumaric acid from Phe and Tyr, respectively. Cinnamic acid can, in turn, be converted into p -coumaric acid by cinnamate 4-hydroxylase. Thus, Phe and Tyr are both precursors of common downstream products. Not all derivatives of Phe and Tyr are shared, however, and each can act as a precursor for unique metabolites. In this study, 13 C isotopic-labeled precursors and the recently developed Precursor of Origin Determination in Untargeted Metabolomics (PODIUM) mass spectrometry (MS) analytical pipeline were used to identify over 600 MS features derived from Phe and Tyr in sorghum. These features comprised 20% of the MS signal collected by reverse-phase chromatography and detected through negative-ionization. Ninety percent of the labeled mass features were derived from both Phe and Tyr, although the proportional contribution of each precursor varied. In addition, the relative incorporation of Phe and Tyr varied between metabolites and tissues, suggesting the existence of multiple pools of p -coumaric acid that are fed by the two amino acids. Furthermore, Phe incorporation was greater for many known hydroxycinnamate esters and flavonoid glycosides. In contrast, mass features derived exclusively from Tyr were the most abundant in every tissue. The Phe- and Tyr-derived metabolite library was also utilized to retrospectively annotate soluble MS features in two brown midrib mutants ( bmr6 and bmr12 ) identifying several MS features that change significantly in each mutant.

09 BIOMASS FUELS↗
DOE OSTI2023

Nuclear fuel irradiation testbed for nuclear security applications

The nuclear security community has long been interested in the identification and quantification of nuclear material signatures to understand a material’s provenance, use, and ultimate application. New forensics signatures and methods intended for non-traditional or advanced nuclear fuel applications require fuel irradiation experiments to demonstrate viability and validity. Integral fuel irradiations have historically required significant costs and long timelines to design, irradiate, and characterize. This paper describes how a recently developed nuclear fuel irradiation testbed can be used to provide a low cost, rapid turnaround, modular test environment for irradiation and evaluation of nuclear fuel specimens for nuclear security applications. The irradiation testbed houses six small ‘MiniFuel’ samples within hermetically sealed capsules inside targets that can be removed in between each ∼25-day operating cycle of the High Flux Isotope Reactor (HFIR). As many as nine targets can be irradiated using a single irradiation position (reflector region) in HFIR, allowing for varying irradiation temperatures and burnups. A suite of hot cell capabilities have been established to perform post-irradiation examination for measuring performance (e.g., fuel swelling, fission gas release) and facilitating experiment disassembly for subsequent property measurements, microstructural analysis, or chemical assay. This new testbed allows fuel irradiations to be conducted on an accelerated timeframe to enable rapid proof of concept testing and to provide reference material for nuclear fuel security applications. Recent applications using this testbed include the testing of isotopic taggants in UO 2 fuel (intentional forensics), testing of U-10Mo fuel for down-conversion of highly enriched uranium–fueled reactors, and the production of irradiated UO 2 fuel material for signature analysis of its isotopic composition (plutonium, fission gases, etc.).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Phonon Olympics: Phonon property and lattice thermal conductivity benchmarking from open-source packages

Three widely used open-source packages for determining phonon properties and lattice thermal conductivities (ALAMODE, phono3py, and ShengBTE) are benchmarked by teams of expert users and the package developers. The phonons for Ge, RbBr, monolayer MoSe 2 , and AlN are modeled at zero temperature, and they scatter through three-phonon and phonon-isotope processes, with thermal conductivities obtained from the linearized Peierls–Boltzmann transport equation with input from density functional theory calculations. Over a wide range of temperatures, the thermal conductivities calculated by the teams fall within at most ±15% of their mean values for each of the four materials. The phonon frequencies, obtained from the harmonic force constants, do not show large differences between the calculations, indicating that the modal heat capacities and group velocities are not responsible for the thermal conductivity variations. It is the lifetimes associated with three-phonon scattering, obtained from the cubic force constants, that drive the variations. The many decisions required to calculate the cubic force constants (e.g., supercell size, atomic displacement, neighbor cutoff, and application of symmetries) make identification of the precise origin of the thermal conductivity variations challenging. The calculated thermal conductivities do not generally show agreement with experimental measurements, which is attributed to the limitations of the density functional theory calculations. Guidance for the development of best practices is provided, which will help to standardize protocols needed for building thermal conductivity databases. The results provide a baseline for future benchmarking of other packages and more advanced calculations.

McGaughey, Alan J. H. [Carnegie Mellon Univ., Pitt↗
DOE OSTI2022

Quantifying fish otolith mineralogy for trace-element chemistry studies

Otoliths are frequently used to infer environmental conditions or fish life history events based on trace-element concentrations. However, otoliths can be comprised of any one or combination of the three most common polymorphs of calcium carbonate - aragonite, calcite, and vaterite - which can affect the ecological interpretation of otolith trace-element results. Previous studies have reported heterogeneous calcium carbonate compositions between left and right otoliths but did not provide quantitative assessments of polymorph abundances. In this study, neutron diffraction and Raman spectroscopy were used to identify and quantify mineralogical compositions of Chinook salmon Oncorhynchus tshawytscha otolith pairs. We found mineralogical compositions frequently differed between otoliths in a pair and accurate calcium carbonate polymorph identification was rarely possible by visual inspection alone. The prevalence of multiple polymorphs in otoliths is not well-understood, and future research should focus on identifying otolith compositions and investigate how variations in mineralogy affect trace-element incorporation and potentially bias environmental interpretations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Mitigation of Cosmic Rays-Induced Errors in Superconducting Quantum Processors

Environmental radioactivity and cosmic-rays have recently been identified as a source of decoherence in super-conducting quantum bits (qubits). In particular, the absorption of cosmic-ray muons and gamma rays emitted by naturally occurring radioactive isotopes in the qubit substrate leads to correlated errors in superconducting quantum processors, posing significant challenges to quantum error correction. To enable quantum computing to scale, it is therefore necessary the devel-opment of mitigation strategies to prevent, or keep under control, error bursts due to particle impacts in the chip. While most environmental radioactive sources can be effectively suppressed using dedicated shielding, cosmic-ray muons, with their high penetration capability, can only be mitigated by moving the entire facility in a deep underground laboratory. This work explores the potential for developing a novel class of quantum processors equipped with an active veto system to protect superconducting-based quantum computers from the detrimental effects of atmospheric muons. Such a device would enable the identification of an atmospheric muon interaction within the processor and veto all operations performed during the occurrence of such an interaction. By demonstrating high detection efficiency and negligible dead time, we aim to establish that the future of quantum processors can be envisioned in above-around facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Gas diffusion through variably-water-saturated zeolitic tuff: Implications for transport following a subsurface nuclear event

Noble gas transport through geologic media has important applications in the characterization of underground nuclear explosions (UNEs). Without accurate transport models, it is nearly impossible to distinguish between xenon signatures originating from civilian nuclear facilities and UNEs. Understanding xenon transport time through the earth is a key parameter for interpreting measured xenon isotopic ratios. One of the most challenging aspects of modeling gas transport time is accounting for the effect of variable water saturation of geological media. In this study, we utilize bench-scale laboratory experiments to characterize the diffusion of krypton, xenon, and sulfur hexafluoride (SF6) through intact zeolitic tuff under different saturations. Here, we demonstrate that the water in rock cores with low partial saturation dramatically affects xenon transport time compared to that of krypton and SF6 by blocking sites in zeolitic tuff that preferentially adsorb xenon. This leads to breakthrough trends that are strongly influenced by the degree of the rock saturation. Xenon is especially susceptible to this phenomenon, a finding that is crucial to incorporate in subsurface gas transport models used for nuclear event identification. We also find that the breakthrough of SF6 diverges significantly from that of noble gases within our system. When developing field scale models, it is important to understand how the behavior of xenon deviates from chemical tracers used in the field, such as SF6 (Carrigan et al., 1996). These new insights demonstrate the critical need to consider the interplay between rock saturation and fission product sorption during transport modeling, and the importance of evaluating specific interactions between geomedia and gases of interest, which may differ from geomedia interactions with chemical tracers.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

A refined assessment of nuclear data target accuracy requirements for ALFRED

The interest in target accuracy assessment has been recently renewed within the OECD/NEA Working Party on International Nuclear Data Evaluation Cooperation with an update exercise, thanks to the invaluable initiative of Massimo Salvatores. This work, moving from evaluations on the main core integral parameters of the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED), and the identification of the associated target accuracies needed for improving its design, approaches the retrieval of target accuracy requirements for nuclear data, as the inverse problem of uncertainty quantification. The preliminary results obtained in a previous work are here refined by explicitly taking into account the total contribution due to correlations among variables in the optimization constraint, while its various components are evaluated individually. Moreover, three different sets of cost parameters are considered to introduce a bias in the solution in order to take in due account the relative difficulties in the execution of new differential experiments as needed for achieving the proposed target accuracies. By this, the obtained results are deemed usefully informative, and proposed for the update of a High Priority List which identifies the isotopes-reaction couples of most interest for future refinement experiments, especially when integrated with further analogous information collected on other advanced nuclear systems. Among the cross-sections whose refinement contributes the most to the reduction of the multiplication factor, the fission of Pu{sup 239} was found, which needs to be fixed below 1% in the range of interest for ALFRED (2 keV-4 MeV). Another contribution for the amelioration of the multiplication factor calculation accuracy, is due to the capture channel of Pu{sup 239}, for which the initial high uncertainty (around 15%) can be significantly reduced resorting to easily practicable experiments. The same occurs for the inelastic of Pb{sup 207}, for which the initial uncertainty value of around 50% can be drastically reduced up to target values between 4% and 7%.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

A 15-Mev/nucleon Iso-Cyclotron for Security and Radioisotope Production

Cargo inspection systems exploit the broad bremsstrahlung spectrum from a 6-10 MeV, low-duty cycle electron accelerator which in the presence of significant backgrounds presents challenges in image and material identification. An alternative approach is to use ions which can excite nuclear states either directly, or through generation of secondary high-energy signature gammas produced from nuclear interactions in a target. RadiaBeam is designing a compact sector isocyclotron 1.25 m in radius, with high-gradient cavities to accelerate multi-ion species up to 15-20 MeV/u with large turn-to turn, centimeter-level separation for low-loss extraction without lossy foil stripping. A strong-focusing radial field profile will be optimized in a separated-sector format for control over machine tune simultaneous with isochronous orbist requirements for high-current (~0.5 milliamp) operation. Innovation in injection will be introduced to replace the high-loss central region. Non-security applications of the cyclotron include medical isotope production, ion radiobiology, as well as material science research and ion instrumentation development.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Exploring New Diamond Surfaces with Precision Chemistry and Quantum Spectroscopy

Point defects in diamond known as color centers are a promising platform for quantum sensing. As atom-like systems, they can exhibit excellent spin coherence and can be manipulated with light. As solid-state defects, they can be produced at high densities and be incorporated into scalable devices. Diamond is a uniquely excellent host; it has a large band gap, can be synthesized with sub-ppb impurity concentrations, and can be isotopically purified to eliminate magnetic noise from nuclear spins. Specifically, the nitrogen vacancy (NV) center has been demonstrated to be a highly sensitive, non-invasive magnetic probe capable of resolving the magnetic field of a single electron spin with nanometer spatial resolution. However, the development of NV centers and other color centers in diamond as a quantum platform crucially relies on developing methods to functionalize and process diamond surfaces. Diamond is the hardest material, making polishing and processing challenging, and diamond surfaces are inert and sterically hindered, making them notoriously difficult to chemically terminate and functionalize. Our approach is to discover new surface chemistries for diamond by combining multimodal surface spectroscopy with NV-based quantum spectroscopy to carefully characterize the diamond surface. We have developed a suite of techniques for characterizing the diamond surface using rapid tools for reaction screening and detailed surface spectroscopy tools for definitive identification of the surface bonding.

36 MATERIALS SCIENCE↗