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DOE OSTI2026

BMINN: Learning chemical potentials and parameters from voltage data for multi-phase battery modeling

Free-energy landscapes and chemical potentials govern the dynamics of phase transitions, transport, and stability in functional materials, yet they remain experimentally inaccessible under realistic operating conditions. Here we introduce a Bayesian model-integrated neural network (BMINN) that embeds physics-based formulations of non-autonomous partial differential-algebraic equations into probabilistic learning. This approach reconstructs hidden thermodynamics directly from macroscopic current-voltage data, providing quantitative access to metastable states, staging transitions, and energy barriers without synchrotron probes. Demonstrated on lithium-graphite electrodes, BMINN recovers full Gibbs free-energy landscapes with fidelity validated against operando X-ray diffraction. The framework generalizes across dynamical regimes, enabling accurate voltage prediction, internal state estimation, and inference of governing parameters. Beyond batteries, BMINN exemplifies a broadly applicable strategy for learning missing physics in multiphase, non-equilibrium systems, offering a new pathway to uncover hidden thermodynamic functions across condensed matter and materials physics.

25 ENERGY STORAGE↗

DOE OSTI2021

Robust analysis of space-, time-, and energy-resolved soft x-ray measurements of magnetically confined fusion plasmas (invited)

A novel compact multi-energy soft x-ray (ME-SXR) diagnostic based on the PILATUS3 100K x-ray detector has been developed in collaboration between the Princeton Plasma Physics Laboratory and the University of Wisconsin-Madison and tested on the Madison Symmetric Torus (MST) reversed-field pinch. This solid-state photon-counting detector consists of a two-dimensional array of ~100 000 pixels for which the lower photon absorption cutoff energy can be independently set, allowing it to be configured for a unique combination of simultaneous spatial, spectral, and temporal resolution of ~1 cm, 100 eV, and 500 Hz, respectively. The diagnostic is highly versatile and can be readily adapted to diverse plasma operating conditions and scientific needs without any required downtime. New results from improved-confinement and quasi-single helicity plasmas in the MST demonstrate how the detector can be applied to study multiple aspects of the evolution of magnetically confined fusion-grade plasmas. These include observing the evolution of thermal emissivity, characterizing the energy of mid-Z excitation lines, extracting the T e profile, and observing the evolution of non-thermal populations. A technique for integrating the ME-SXR diagnostic into an integrated data analysis framework based on Bayesian inference is also presented. As a result, this allows ME-SXR measurements to be combined with data for complementary diagnostics in order to simultaneously infer Te and nZ from all available information.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Transactive Energy System Deployment Over Insecure Communication Links

Here, in this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that 1) individual agents’ bidding information is kept private throughout hierarchical market-based interactions; and 2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Note to Practitioners—This paper is motivated by addressing the issues of cyber resiliency for practically deploying transactive energy system (TES) but it is also applicable to the problem of enhancing the privacy and security for any general hierarchical control systems. TES is an emerging control approach that engages energy suppliers and customers through market operations and uses the price to optimally allocate energy resources. While it has been shown to be promising for power system applications, the underlying market-based interactions raise significant concerns of privacy (data leakage) and security (data tampering). However, existing TES works only focus on the coordination mechanism instead of privacy and security issues. This paper proposes a new cryptography-based TES design for practical deployment. Specifically, to protect privacy, individual supply and demand amounts to be exchanged are all encrypted in a particular way such that the original amounts cannot be inferred from the encrypted amounts, while the desired computation for setting the market clearing price can be carried out over the encrypted amounts, thus generating an encrypted result which, when decrypted, matches that of the same computation over the original amounts. To achieve security, for each exchanged data, its sender generates a particular digital signature which is exchanged together with the data. This enables the receiver to automatically detect the integrity by checking whether a mathematical relationship holds for the pair of data and signature. In our future research, we will investigate more challenging scenarios where some suppliers and customers themselves could be corrupted and purposely submit distorted amounts.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2011

Oxygen and Magnesium Isotopic Compositions of Asteroidal Materials Returned from Itokawa by the Hayabusa Mission

The Hayabusa spacecraft made two touchdowns on the surface of Asteroid 25143 Itokawa on November 20th and 26th, 2005. The Asteroid 25143 Itokawa is classified as an S-type asteroid and inferred to consist of materials similar to ordinary chondrites or primitive achondrites [1]. Near-infrared spectroscopy by the Hayabusa spacecraft proposed that the surface of this body has an olivine-rich mineral assemblage potentially similar to that of LL5 or LL6 chondrites with different degrees of space weathering [2]. The spacecraft made the reentry into the Earth s atmosphere on June 12th, 2010 and the sample capsule was successfully recovered in Australia on June 13th, 2010. Although the sample collection processes on the Itokawa surface had not been made by the designed operations, more than 1,500 grains were identified as rocky particles in the sample curation facility of JAXA, and most of them were judged to be of extraterrestrial origin, and definitely from Asteroid Itokawa on November 17th, 2010 [3]. Although their sizes are mostly less than 10 microns, some larger grains of about 100 microns or larger were also included. The mineral assembly is olivine, pyroxene, plagioclase, iron sulfide and iron metal. The mean mineral compositions are consistent with the results of near-infrared spectroscopy from Hayabusa spacecraft [2], but the variations suggest that the petrologic type may be smaller than the spectroscopic results. Several tens of grains of relatively large sizes among the 1,500 grains will be selected by the Hayabusa sample curation team for preliminary examination [4]. Each grain will be subjected to one set of preliminary examinations, i.e., micro-tomography, XRD, XRF, TEM, SEM, EPMA and SIMS in this sequence. The preliminary examination will start from the last week of January 2011. Therefore, samples for isotope analyses in this study will start from the last week of February 2011. By the time of the LPSC meeting we will have measured the oxygen and magnesium isotopic composition of several grains. We will present the first results from the isotope analyses that will have been performed.

Yurimoto, H↗

DOE OSTI2022

First Sagittarius A* Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole in the Center of the Milky Way

We present the first Event Horizon Telescope (EHT) observations of Sagittarius A* (Sgr A*), the Galactic center source associated with a supermassive black hole. These observations were conducted in 2017 using a global interferometric array of eight telescopes operating at a wavelength of λ = 1.3 mm. The EHT data resolve a compact emission region with intrahour variability. A variety of imaging and modeling analyses all support an image that is dominated by a bright, thick ring with a diameter of 51.8 ± 2.3 μas (68% credible interval). The ring has modest azimuthal brightness asymmetry and a comparatively dim interior. Using a large suite of numerical simulations, we demonstrate that the EHT images of Sgr A* are consistent with the expected appearance of a Kerr black hole with mass ∼4 × 10$^{6}$ M $_{⊙}$, which is inferred to exist at this location based on previous infrared observations of individual stellar orbits, as well as maser proper-motion studies. Our model comparisons disfavor scenarios where the black hole is viewed at high inclination (i > 50°), as well as nonspinning black holes and those with retrograde accretion disks. Our results provide direct evidence for the presence of a supermassive black hole at the center of the Milky Way, and for the first time we connect the predictions from dynamical measurements of stellar orbits on scales of 10$^{3}$–10$^{5}$ gravitational radii to event-horizon-scale images and variability. Furthermore, a comparison with the EHT results for the supermassive black hole M87* shows consistency with the predictions of general relativity spanning over three orders of magnitude in central mass.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗

NASA NTRS2005

Overview of Results from the Cassini Magnetospheric Imaging Instrument (MIMI) During the First Year of Operations

The MIMI investigation comprises three sensors covering the indicated energy ranges: the Ion and Neutral Camera (INCA) -- 7 keV/nuc 3 Mev) and protons (1.6 < E < 160 Mev) from the back end of the dual field-of-view telescope. The Saturn observation sequences began in January, 2004 and culminated in Saturn Orbit Insertion on July 1, 2004. The MIMI sensors observed substantial activity in interplanetary space for several months prior to SOI, including several interplanetary shocks associated with corotating interaction regions, numerous increases most likely originating from particle streams in the vicinity of the Saturnian bow shock and energetic neutral atoms (ENA) emanating from Saturn s magnetosphere. Results following SOI revealed: a dynamical magnetosphere with a day-night asymmetry and an 11-hour periodicity; several water-product ions (O+, OH+, H2O+), but little N+; inferred quantities of neutral gas sufficient to cause major losses in the trapped ions and electrons in the middle and inner magnetosphere; a Titan exosphere that is a copious source of ENA; INCA imaging through ENA has also revealed a previously unknown radiation belt residing inward of the D-ring that is most likely the result of double charge-exchange between the main radiation belt and the upper layers of Saturn s exosphere. Finally, there is ample evidence for the presence of substorm-like injections of plasma that subsequently corotates for a number of days before dissipating on the night-side magnetotail. The observations will be presented and discussed in the context of current theoretical models.

Krimigis, S. M.↗

DOE OSTI2023

Insights into the Oxidative Degradation Mechanism of Solid Amine Sorbents for CO 2 Capture from Air: Roles of Atmospheric Water

Abstract Direct air capture (DAC) processes for extraction of CO 2 from ambient air are unique among chemical processes in that they operate outdoors with minimal feed pretreatments. Here, the impact of humidity on the oxidative degradation of a prototypical solid supported amine sorbent, poly(ethylenimine) (PEI) supported on Al 2 O 3 , is explored in detail. By combining CO 2 adsorption measurements, oxidative degradation rates, elemental analyses, solid‐state NMR and in situ IR spectroscopic analysis in conjunction with 18 O labeling of water, a comprehensive picture of sorbent oxidation is achieved under accelerated conditions. We demonstrated that the presence of water vapor can play an important role in accelerating the degradation reactions. From the study we inferred the identity and kinetics of formation of the major oxidative products, and the role(s) of humidity. Our data are consistent with a radical mediated autooxidative degradation mechanism.

Carneiro, Juliana S. A.↗

DOE OSTI2020

Measurement uncertainty of rossi-alpha neutron experiments

Rossi-alpha neutron experiments are used to estimate the prompt neutron decay constant of a fissile assembly, a quantity of widespread interest in applications including in nuclear nonproliferation and criticality safety. This work develops a mathematical model to efficiently estimate measurement uncertainty of Rossi-alpha neutron experiments inferred from a two-exponential fit model with histogram binning. The derived uncertainty estimates were validated using repeated Rossi-alpha measurements of a subcritical, 4.5-kg sphere of weapons-grade, alpha-phase plutonium with nickel, copper, tungsten, and polyethylene reflectors. The estimates of uncertainty for the histogram data produced by the model were conservative and agree with the reference uncertainties within noise. The estimates of the prompt neutron decay constant uncertainty agreed with the reference uncertainties within one standard deviation. In conclusion, the proposed model will reduce total measurement times, ultimately reducing operational and procedural costs in application.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Conformal Hierarchical Simulation-Based Inference with Local Validity

Trustworthy and interpretable uncertainty quantification is a long-standing challenge in artificial intelligence. Simulation-based inference (SBI) comprises a broad swath of approaches for estimating latent parameters with uncertainties. Although flexible neural density estimators in SBI can be remark- ably expressive capturing highly structured, high-dimensional posteriors their credible regions can be badly mis-calibrated and are often only accompanied by heuristic coverage checks. We present the first SBI framework that delivers finite-sample local valid coverage guarantees that hold in the neighborhood of each observation. Our framework can couple any off-the-shelf hierarchical SBI engine with a confor- mal Bayesian post-processing step that operates on the posterior predictive density. A kernel-weighted conformity score adapts the conformal quantile to the local geometry of the data, yielding prediction sets that are simultaneously (i) marginally calibrated, (ii) locally valid, and (iii) hierarchical, handling global and observation-specific parameters in a single pass. Through experiments on synthetic data and benchmarks from neuroscience and physics, we show that our approach attains 1 − α coverage, where prior SBI methods under- or over-cover. Our approach also maintains a competitive, credible set size with minimal computational overhead. Finally, our approach can be used to make predictions on real data and give valid credible regions modulo weight-initialization-based model mis-specification.

Trivedi, Shubhendu [Fermilab]↗

DOE OSTI2020

Characterization of Mechanical Ventilation Systems in New US Homes: What types of systems are out there and are they functioning as intended?

As the airtightness of homes improves to meet energy efficiency goals, it becomes more important for mechanical ventilation systems to help maintain a comfortable and healthy indoor air environment. ASHRAE Standard 62.2 provides national guidance for mechanical ventilation system design and installation, however adoption of those guidelines into local building codes has occurred at different rates. Once provisions for mechanical ventilation are adopted in a local code, are mechanical ventilation systems properly designed, installed, commissioned and operated according to code or above code program requirements? Is there a need for further industry and homeowner education to ensure systems function as intended? This paper presents results from field studies that include characterization of mechanical ventilation systems in over 150 new homes in CA, CO, FL, GA, IL, OR, and SC built between 2011 and 2018. In each of the study homes, airflow of local (kitchen, bathrooms) and whole-house ventilation were measured. Occupant usage of the mechanical ventilation systems were monitored for one week in each home. Installed performance is compared to inferred design intent. The paper also includes homeowner perceptions about, and interactions with, the installed mechanical ventilation systems.

Martin, Eric↗

DOE OSTI2022

Exploring the Consistency of Water Scarcity Inferences between Large-Scale Hydrologic and Node-Based Water System Model Representations of the Upper Colorado River Basin

Water resources model development and simulation efforts have seen rapid growth in recent decades to aid evaluations and planning around water scarcity and allocation. Models are typically developed by two distinct communities: (1) large-scale hydrologic modelers emphasizing hydroclimatological processes, and (2) water systems modelers emphasizing environmental, infrastructural, and institutional features that shape water scarcity at the local basin level. This study assesses whether two representative models from these communities produce consistent insights when evaluating the water scarcity vulnerabilities in the Upper Colorado River Basin within the state of Colorado. Results showed that although the regional-scale model [model for scale adaptive river transport (MOSART)—water management (WM)] can capture the aggregate effect of all water operations in the basin, it underestimates the subbasin-scale variability in specific user’s vulnerabilities. The basin-scale water systems model [State of Colorado’s Stream Simulation Model (StateMod)] suggests a larger variance of scarcity across the basin’s water users due to its more detailed accounting of local water allocation infrastructure and institutional processes. This model intercomparison highlights potentially significant limitations of large-scale studies in seeking to evaluate water scarcity and actionable adaptation strategies, as well as ways in which basin-scale water systems model’s information can be used to better inform water allocation and shortage when used in tandem with larger-scale hydrological modeling studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

MIND-MAC: Multi-Level In-memory Quasi Non-Destructive MAC Operation in Compact 2T-nC FeRAM for Efficient DNN Accelerator

We present MIND-MAC, a compact 2T-nC FeRAM architecture that performs multi-level, quasi-non-destructive in-memory multiply–accumulate (MAC) for deep neural networks. By exploiting voltage-controlled partial domain switching in MFM capacitors and read-transistor amplification, the cell stores multi-bit weights and gates bit-serial inputs to produce an accumulated current on shared lines. We combine TCAD-extracted parasitics with experimentally calibrated ferroelectric models in SPICE to validate device-/circuit-level behavior, and validate multi-level sensing and QNRO with measurements on a fabricated 2T-3C test vehicle. An analytical system model maps MIND-MAC to a 6-GB main-memory in-memory compute (IMC) architecture and benchmarks VGG13 inference in 61.08 ms at 964.99 mJ. Results indicate high density, reduced rewrite overhead, and energy efficiency, positioning 2T-nC FeRAM as a promising IMC candidate for next-generation AI hardware.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Insights into the Oxidative Degradation Mechanism of Solid Amine Sorbents for CO 2 Capture from Air: Roles of Atmospheric Water

Direct air capture (DAC) processes for extraction of CO 2 from ambient air are unique among chemical processes in that they operate outdoors with minimal feed pretreatments. Here, the impact of humidity on the oxidative degradation of a prototypical solid supported amine sorbent, poly(ethylenimine) (PEI) supported on Al 2 O 3 , is explored in detail. By combining CO 2 adsorption measurements, oxidative degradation rates, elemental analyses, solid-state NMR and in situ IR spectroscopic analysis in conjunction with 18 O labeling of water, a comprehensive picture of sorbent oxidation is achieved under accelerated conditions. Here we demonstrated that the presence of water vapor can play an important role in accelerating the degradation reactions. From the study we inferred the identity and kinetics of formation of the major oxidative products, and the role(s) of humidity. Our data are consistent with a radical mediated autooxidative degradation mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes

A promising approach for scalable Gaussian processes (GPs) is the Karhunen-Loève (KL) decomposition, in which the GP kernel is represented by a set of basis functions which are the eigenfunctions of the kernel operator. Such decomposed kernels have the potential to be very fast, and do not depend on the selection of a reduced set of inducing points. However KL decompositions lead to high dimensionality, and variable selection thus becomes paramount. This paper reports a new method of forward variable selection, enabled by the ordered nature of the basis functions in the KL expansion of the Bayesian Smoothing Spline ANOVA kernel (BSS-ANOVA), coupled with fast Gibbs sampling in a fully Bayesian approach. It quickly and effectively limits the number of terms, yielding a method with competitive accuracies, training and inference times for tabular datasets of low feature set dimensionality. Theoretical computational complexities are O ( N P 2 ) in training and O ( P ) per point in inference, where N is the number of instances and P the number of expansion terms. The inference speed and accuracy makes the method especially useful for dynamic systems identification, by modeling the dynamics in the tangent space as a static problem, then integrating the learned dynamics using a high-order scheme. The methods are demonstrated on two dynamic datasets: a ‘Susceptible, Infected, Recovered’ (SIR) toy problem, along with the experimental ‘Cascaded Tanks’ benchmark dataset. Comparisons on the static prediction of time derivatives are made with a random forest (RF), a residual neural network (ResNet), and the Orthogonal Additive Kernel (OAK) inducing points scalable GP, while for the timeseries prediction comparisons are made with LSTM and GRU recurrent neural networks (RNNs) along with the SINDy package.

Hayes, Kyle↗

NASA NTRS1977

Flow characteristics in an expansion tunnel as inferred from velocity measurements

A photoionization technique was used to study flow characteristics in an expansion tunnel. Vertical surveys of the axial component of flow velocity just downstream from the nozzle exit were obtained, and estimates of freestream density were inferred from the velocity measurement technique. The pitot pressure was measured and compared to the average axial component of velocity as a function of time for the two cases when air and CO2 were used as test gases. Vertical velocity and static density profiles at the nozzle exit are presented for the case when CO2 was used as test gas. Experimental results were used to determine the diameter and uniformity of the test core at the nozzle exit and the duration of the quasi-steady flow period. These data are relevant to evaluation of the suitability of operating an expansion tube as an expansion tunnel. The expansion tunnel is an expansion tube with a conical nozzle positioned at the exit of the acceleration section, so that nozzle entrance flow conditions are hypersonic and characterized by hypervelocity.

Miller, C. G.↗

NASA NTRS2020

Apatites in Gale Crater

ChemCam is an active remote sensing instrument suite that has operated successfully on MSL since landing Aug. 6th, 2012. It uses laser pulses to remove dust and to analyze rocks up to 7 m away. Laser-induced breakdown spectroscopy (LIBS) obtains emission spectra of materials ablated from the samples in electronically excited states. The intensities of the emission lines scale with the abundances of the related element. ChemCam is sensitive to most major rock-forming elements as well as to a set of minor and trace elements such as F, Cl, Li, P, Sr, Ba, and Rb. The measured chemical composition can then be used to infer the mineralogical composition of the ablated material. Here, we report a summary of inferred apatite detections along the MSL traverse at Gale Crater. We present the geologic settings of these findings and derive some interpretations about the formation conditions of apatite in time and space.

Forni, O.↗

NASA NTRS1992

Chemical environments of submarine hydrothermal systems

Perhaps because black-smoker chimneys make tremendous subjects for magazine covers, the proposal that submarine hydrothermal systems were involved in the origin of life has caused many investigators to focus on the eye-catching hydrothermal vents. In much the same way that tourists rush to watch the spectacular eruptions of Old Faithful geyser with little regard for the hydrology of the Yellowstone basin, attention is focused on the spectacular, high-temperature hydrothermal vents to the near exclusion of the enormous underlying hydrothermal systems. Nevertheless, the magnitude and complexity of geologic structures, heat flow, and hydrologic parameters which characterize the geyser basins at Yellowstone also characterize submarine hydrothermal systems. However, in the submarine systems the scale can be considerably more vast. Like Old Faithful, submarine hydrothermal vents have a spectacular quality, but they are only one fascinating aspect of enormous geologic systems operating at seafloor spreading centers throughout all of the ocean basins. A critical study of the possible role of hydrothermal processes in the origin of life should include the full spectrum of probable environments. The goals of this chapter are to synthesize diverse information about the inorganic geochemistry of submarine hydrothermal systems, assemble a description of the fundamental physical and chemical attributes of these systems, and consider the implications of high-temperature, fluid-driven processes for organic synthesis. Information about submarine hydrothermal systems comes from many directions. Measurements made directly on venting fluids provide useful, but remarkably limited, clues about processes operating at depth. The oceanic crust has been drilled to approximately 2.0 km depth providing many other pieces of information, but drilling technology has not allowed the bore holes and core samples to reach the maximum depths to which aqueous fluids circulate in oceanic crust. Such determinations rely on studies of pieces of deep oceanic crust uplifted by tectonic forces such as along the Southwest Indian Ridge, or more complete sections of oceanic crust called ophiolite sequences which are presently exposed on continents owing to tectonic emplacement. Much of what is thought to happen in submarine hydrothermal systems is inferred from studies of ophiolite sequences, and especially from the better-exposed ophiolites in Oman, Cyprus and North America. The focus of much that follows is on a few general features: pressure, temperature, oxidation states, fluid composition and mineral alteration, because these features will control whether organic synthesis can occur in hydrothermal systems.

Shock, Everett L.↗