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Parahydrogen Properties Version 05 Database Release for NTP Applications

Consistent modeling assumptions across any large project are crucial to minimize errors between different approaches. Use of consistent material and fluid properties across a large project supports consistent interpretation and application within modeling and simulation results as well as their relevancy to operational systems. NASA’s Space Nuclear Propulsion program dedicates extensive resources towards establishing consistent and, to the extent possible, accurate property databases for its internal staff and all external partners. This work highlights the extensive research performed to modernize the fluid property database of hydrogen which is the leading propellant option for in-space nuclear propelled spacecraft. Specifically, the parahydrogen spin state is of interest since the propellant is stored in a near normal boiling point liquid state which results in it consisting almost entirely of the parahydrogen spin isomer. This database tool has taken recent NASA work and modernized it into a python-based package for easy usage across all modeling entities. The package allows users to provide temperature and pressure pairs along with their desired output properties to yield results accounting for both real-gas and equilibrium dissociation effects while also sharing the default thermodynamic reference state provided by the National Institute of Standards and Technology (NIST) Standard Database 23. The suite also includes advanced capabilities to increase usability, such as on-the-fly interpolation and multidimensional plotting.

Nuclear Thermal Propulsion↗

Linking transportation agent-based model ($\mathrm{ABM}$) outputs with micro-urban social types ($\mathrm{MUSTs}$) via typology transfer for improved community relevance

The human relationship with transportation is shaped by social, economic, demographic, and urban form variables, or socio-spatial factors. The spatial dynamics of these are key to generating and interpreting outputs of transportation models that are most relevant for a community and the diverse mobility needs of its members. Here we present a typology transfer framework, grounded in socio-spatial dynamics shaping people's mobility, to take transportation-themed regional mobility model outcomes, in this case from two agent-based models (ABMs), and extrapolate them to other cities, with less time and resource intensity than new ABM development. The typology transfer process first identifies micro-urban social types (MUSTs) using socio-spatial factors, then defines city types based on spatial patterns of MUSTs to assess across which cities transfer results are likely to best hold. Lastly, a typology transfer multiplier matrix extrapolates a given variable, in our case the Mobility Energy Productivity (MEP) metric, to another city. The full process demonstration uses ABM results from Chicago (POLARIS model) and San Francisco (BEAM model), applying them to New York City. We discuss how MEP or other outputs can be appropriately estimated and used for integrated, human-centered mobility analysis. Key findings include that this MUST framework of user-defined dependent and independent variables allows tailoring ABM results and interpretations to specific community needs and data availability. Findings clarify that positive outcomes can be targeted towards user groups, based on sociospatial characteristics, using a typology approach, such as inclusive access to mobility choices, transportation affordability, and greater efficiency in resource use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Harnessing Neural Networks for Elucidating X-ray Absorption Structure–Spectrum Relationships in Amorphous Carbon

Improved understanding of structural and chemical properties through local experimental probes, such as X-ray absorption near-edge structure (XANES) spectroscopy, is crucial for the understanding and design of functional materials. In recent years, significant advancements have been made in the development of data science approaches for the automated interpretation of XANES structure–spectrum relationships. However, existing studies have primarily focused on crystalline solids and small molecules, while fewer efforts have been devoted to disordered systems. Thus, in this work, we demonstrate the development of neural network models for predicting and interpreting XANES spectra of amorphous carbon (a-C) from local structural descriptors. Comparison between different structural descriptors expectedly shows that the inclusion of both bond length and bond angle information is necessary for an accurate prediction of the spectra. Among the descriptors considered in this work, we find that the local many-body tensor representation yields the highest accuracy and greatest interpretability so that it can be leveraged to understand the importance of structural motifs in determining XANES spectra. Furthermore, we also discuss performance of neural network models for predicting both local structure features, such as bond lengths and bond angles, and global chemical composition, such as the sp:sp 2 :sp 3 ratio.

36 MATERIALS SCIENCE↗

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗

Search for pair production of squarks or gluinos decaying via sleptons or weak bosons in final states with two same-sign or three leptons with the ATLAS detector

A search for pair production of squarks or gluinos decaying via sleptons or weak bosons is reported. The search targets a final state with exactly two leptons with same-sign electric charge or at least three leptons without any charge requirement. The analysed data set corresponds to an integrated luminosity of 139 fb –1 of proton-proton collisions collected at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Multiple signal regions are defined, targeting several SUSY simplified models yielding the desired final states. A single control region is used to constrain the normalisation of the WZ + jets background. No significant excess of events over the Standard Model expectation is observed. The results are interpreted in the context of several supersymmetric models featuring R-parity conservation or R-parity violation, yielding exclusion limits surpassing those from previous searches. In models considering gluino (squark) pair production, gluino (squark) masses up to 2.2 (1.7) TeV are excluded at 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for dark matter produced in association with a single top quark or a top quark pair in proton-proton collisions at $ \sqrt{s}=13 $ TeV

A search for dark matter produced in association with top quarks in proton-proton collisions at a center-of-mass energy of 13 TeV is presented. The data set used corresponds to an integrated luminosity of 35.9 fb$^{-1}$ recorded with the CMS detector at the LHC. Whereas previous searches for neutral scalar or pseudoscalar mediators considered dark matter production in association with a top quark pair only, this analysis also includes production modes with a single top quark. The results are derived from the combination of multiple selection categories that are defined to target either the single top quark or the top quark pair signature. No significant deviations with respect to the standard model predictions are observed. The results are interpreted in the context of a simplified model in which a scalar or pseudoscalar mediator particle couples to a top quark and subsequently decays into dark matter particles. Scalar and pseudoscalar mediator particles with masses below 290 and 300 GeV, respectively, are excluded at 95% confidence level, assuming a dark matter particle mass of 1 GeV and mediator couplings to fermions and dark matter particles equal to unity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for dark photons in Higgs boson production via vector boson fusion in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search is presented for a Higgs boson that is produced via vector boson fusion and that decays to an undetected particle and an isolated photon. The search is performed by the CMS collaboration at the LHC, using a data set corresponding to an integrated luminosity of 130 fb$^{−1}$, recorded at a center-of-mass energy of 13 TeV in 2016–2018. No significant excess of events above the expectation from the standard model background is found. The results are interpreted in the context of a theoretical model in which the undetected particle is a massless dark photon. An upper limit is set on the product of the cross section for production via vector boson fusion and the branching fraction for such a Higgs boson decay, as a function of the Higgs boson mass. For a Higgs boson mass of 125 GeV, assuming the standard model production rates, the observed (expected) 95% confidence level upper limit on the branching fraction is 3.5 (2.8)%. This is the first search for such decays in the vector boson fusion channel. Combination with a previous search for Higgs bosons produced in association with a Z boson results in an observed (expected) upper limit on the branching fraction of 2.9 (2.1)% at 95% confidence level.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Keeping it simple: simplified frameworks for long-lived particles at neutrino facilities

Modern-day accelerator neutrino facilities are excellent venues for searches for new-physics particles. Many distinct new-physics models predict overlapping signatures and phenomenology in these experiments. In this work, we advocate for the adoption of simplified frameworks when studying these types of new-physics signatures, which are characterized by a small number of primary variables, including particle masses, lifetimes, and production and decay modes/rates that most directly control signal event rates and kinematics. In particular, taking the example of long-lived particles that decay inside a neutrino detector as a test case, we study formulate and study simplified frameworks in the context of light scalars/fermions produced in kaon decays which then decay into final states containing an electron-positron pair. We show that using these simplified frameworks can allow for individual experimental analyses to be applicable to a wide variety of specific model scenarios. As a side benefit, we demonstrate that using this approach can allow for the T2K collaboration, by reinterpreting its search for Heavy Neutral Leptons, to be capable of setting world-leading limits on the Higgs-Portal Scalar model. Furthermore, we argue the simplified framework interpretation can serve as a bridge to model identification in the hopeful detection of a new-physics signal. As an illustration, we perform a first determination of the likelihood that, in the presence of a new-physics signal in a detector like the DUNE ND-GAr, multiple different new-physics hypotheses (such as the Higgs-Portal Scalar and Heavy Neutral Lepton ones) can be disentangled. We demonstrate that this model discrimination is favorable for some portions of detectable new-physics parameter space but for others, it is more challenging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for dark photons in decays of Higgs bosons produced in association with Z bosons in proton-proton collisions at s $\sqrt{s}$ = 13 TeV

A search is presented for a Higgs boson that is produced in association with a Z boson and that decays to an undetected particle together with an isolated photon. The search is performed by the CMS Collaboration at the Large Hadron Collider using a data set corresponding to an integrated luminosity of 137 fb$^{-1}$ recorded at a center-of-mass energy of 13 TeV. No significant excess of events above the expectation from the standard model background is found. The results are interpreted in the context of a theoretical model in which the undetected particle is a massless dark photon. An upper limit is set on the product of the cross section for associated Higgs and Z boson production and the branching fraction for such a Higgs boson decay, as a function of the Higgs boson mass. For a mass of 125 GeV, assuming the standard model production cross section, this corresponds to an observed (expected) upper limit on this branching fraction of 4.6 (3.6)% at 95% confidence level. These are the first limits on Higgs boson decays to final states that include an undetected massless dark photon.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for dark matter in events with missing transverse momentum and a Higgs boson decaying into two photons in pp collisions at $$ \sqrt{s} $$ = 13 TeV with the ATLAS detector

A search for dark-matter particles in events with large missing transverse momentum and a Higgs boson candidate decaying into two photons is reported. The search uses 139 fb - 1 of proton-proton collision data collected at $$ \sqrt{s} $$ s = 13 TeV with the ATLAS detector at the CERN LHC between 2015 and 2018. No significant excess of events over the Standard Model predictions is observed. The results are interpreted by extracting limits on three simplified models that include either vector or pseudoscalar mediators and predict a final state with a pair of dark-matter candidates and a Higgs boson decaying into two photons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Skin factor and potential formation damage from chemical and mechanical processes in a naturally fractured carbonate aquifer with implications to CO 2 sequestration

Here, in this study, we investigate formation damage due to acidization and water injection tests into the naturally fractured carbonate Middle Duperow Formation at Kevin Dome, Montana, potentially diminishing the chance of a future successful Geological Carbon Sequestration (GCS) project. Multiple well-test analytical models, correlated with core description and lithology data, are used to determine flow behavior and communication between the water injection interval and surrounding formations. An improved three-dimensional (3D) geologic model with dual-continuum matrix and fracture properties is constructed based on most recent seismic, core, and water sample measurements. Brine injection is simulated to verify the interpretation from the analytical models, followed by CO 2 injection simulation. Geochemical calculations are performed to understand the in-situ processes that led to formation damage. Our findings suggest: (1) there are two possible scenarios that could lead to a positive total effective skin factor and permeability decline: partial penetration and formation damage; (2) analytical models indicate a positive total skin factor, contradicting results of a previous study suggesting that the well was mildly stimulated; (3) numerical simulation supports the formation damage hypothesis by matching the pressure buildup observed during the latter two brine injection tests; (4) several mechanical and chemical processes may have occurred during injection to clog the matrix/fracture system: anhydrite fines migration and/or calcite precipitation. We then make preventative suggestions for future GCS projects into carbonate reservoirs and remediation recommendations for GCS operation at the Kevin Dome.

54 ENVIRONMENTAL SCIENCES↗

Surface fitting with biharmonic and harmonic models

The physical and geometric interpretation of a surface fitting technique, multiquadric equations (MQ), is discussed. The relation of this method and its reciprocal form to biharmonic and harmonic techniques respectively, is pointed out. In both forms the solutions may be viewed as being numerical approximations of an integral equation in which an unknown density function is the physical source for disturbing potential (reciprocal-MQ) or elastic displacement (MQ).

Hardy, R. L.↗

Overview of nebula models: Potential chondrule-forming environments

Observations of T Tauri stars and their circumstellar disks, combined with broadly applied theoretical principles, permit the construction of solar nebular models that are potentially useful for the interpretation of meteoritic data. Quantitative comparisons of model results with meteoritic and planetary data is used to test several propositions regarding the bulk properties of chondrites and chondrule precursor material.

Cassen, P.↗

Eruption of a Multiple-Turn Helical Magnetic Flux Tube in a Large Flare: Evidence for External and Internal Reconnection that Fits the Breakout Model of Solar Magnetic Eruptions

We present observations and an interpretation of a unique multiple-turn spiral flux tube eruption from AR10030 on 2002 July 15. The TRACE CIV observations clearly show a flux tube that is helical and that is erupting from within a sheared magnetic field. These observations are interpreted in the context of the breakout model for magnetic field explosions. The initiation of the helix eruption starts 25 seconds after the peak of the flare s strongest impulsive spike of microwave gryosynchrotron radiation early in the flare s explosive phase, implying that the sheared core field is not the site of the initial reconnection. Within the quadrupolar configuration of the active region, the external and internal reconnection sites are identified in each of two consecutive eruptive flares that produce a double CME. The first external breakout reconnection apparently releases an underlying sheared core field and allows it to erupt, leading to internal reconnection in the wake of the erupting helix. This internal reconnection heats the two-ribbon flare and might or might not produce the helix. These events lead to the first CME and are followed by a second breakout that initiates a second and larger halo CME. The strong magnetic shear in the region is associated with rapid proper motion and evolution of the active region. The multiple-turn helix originates from above a sheared-field magnetic inversion line within a filament channel, and starts to erupt only after fast breakout reconnection has started. These observations are counter to the standard flare model and support the breakout model for eruptive flare initiation. However, the observations are compatible with internal reconnection in a sheared magnetic arcade in the formation and eruption of the helix.

Gary, G. Allen↗

Eruption of a Multiple-Turn Helical Magnetic Flux Tube in a Large Flare: Evidence for External and Internal Reconnection that Fits the Breakout Model of Solar Magnetic Eruptions

We present observations and an interpretation of a unique multiple-turn spiral flux tube eruption from active region 10030 on 2002 July 15. The TRACE C IV observations clearly show a flux tube that is helical and erupting from within a sheared magnetic field. These observations are interpreted in the context of the breakout model for magnetic field explosions. The initiation of the helix eruption. as determined by a linear backward extrapolation, starts 25 s after the peak of the flare's strongest impulsive spike of microwave gyrosynchrotron radiation early in the flare s explosive phase, implying that the sheared core field is not the site of the initial reconnection. Within the quadrupolar configuration of the active region, the external and internal reconnection sites are identified in each of two consecutive eruptive flares that produce a double coronal mass ejection (CME). The first external breakout reconnection apparently releases an underlying sheared core field and allows it to erupt, leading to internal reconnection in the wake of the erupting helix. This internal reconnection releases the helix and heats the two-ribbon flare. These events lead to the first CME and are followed by a second breakout that initiates a second and larger halo CME. The strong magnetic shear in the region is compatible with the observed rapid proper motion and evolution of the active region. The multiple-turn helix originates from above a sheared-field magnetic inversion line within a filament channel. and starts to erupt only after fast breakout reconnection has started. These observations are counter to the standard flare model and support the breakout model for eruptive flare initiation.

Gary, G. Allen↗

The EST Model for Predicting Progressive Damage and Failure of Open Hole Bending Specimens

Progressive damage and failure in open hole composite laminate coupons subjected to flexural loading is modeled using Enhanced Schapery Theory (EST). Previous studies have demonstrated that EST can accurately predict the strength of open hole coupons under remote tensile and compressive loading states. This homogenized modeling approach uses single composite shell elements to represent the entire laminate in the thickness direction and significantly reduces computational cost. Therefore, when delaminations are not of concern or are active in the post-peak regime, the version of EST presented here is a good engineering tool for predicting deformation response. Standard coupon level tests provides all the input data needed for the model and they are interpreted in conjunction with finite element (FE) based simulations. Open hole bending test results of three different IM7/8552 carbon fiber composite layups agree well with EST predictions. The model is able to accurately capture the curvature change and deformation localization in the specimen at and during the post catastrophic load drop event.

damage↗

Physics-informed, empirically constrained machine learning for designing Fe-9Cr alloys

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Materials data analytics can be used to significantly shorten development time of specialized alloys needed for next generation energy applications. Incorporation of the domain knowledge into deep-learning graph structure via fuzzy pre-training and causal process imitation presents a viable approach to developing accurate data-driven models and reliable alloy design tools, with limited datasets. It was demonstrated that the domain knowledge-based empirical constraints not only inhibit overfitting but also allow training more accurate and reliable ML models with improved transparency of the output interpretation. In this study, alloy tensile properties were interpreted with three competing virtual-microstructure models.</span>

Romanov, Vyacheslav↗

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks

Abstract Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.

59 BASIC BIOLOGICAL SCIENCES↗