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At least 775 records · Page 43

Hybrid Model Based Approaches for Systems Health Management and Prognostics

This is a previously approved and published presentation. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Present achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. In principle, data-driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data-driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety-critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Prognostics↗

Safety Assessment of El Cabril, the Spanish Surface Disposal facility for LILW and VLLW - 17233

El Cabril project was launched in 1986, for Low and Intermediate Level Waste (LILW) disposal, based on concrete barriers and concrete disposal units. The operation of a Very Low Leve Waste (VLLW) complementary facility based on clay and High Density Polyethylene (HDPE) barriers and different types of disposal units started in 2008. Two main objectives are considered in the design: Immediate and post-closure protection and no radiological restrictions, after institutional control period. To fulfil these objectives several design criteria like waste isolation through a multi-barrier system, surveillance period no longer than 300 years and limitation of activity are applied. The Safety Assessment process follows a methodology which, taking into account important facts like safety and design criteria, time frame, radiological protection criteria, waste characteristics, environment, FEPs (features, events and processes), etc., develops different scenarios, models and calculations to define the safety approach. This safety approach follows the current guides and recommendations of international organizations, it covers the potential impact of the facility for the operational and long-term periods and it includes normal evolution and less likely accidental and inadvertent human intrusion events. All the studies and considerations done for the Safety Assessment have to be included in a safety Report, required for getting the Operation License for Nuclear Installations in Spain. The content of this Report is defined by the Spanish regulation and it has to be revised if there is a change in the facility that may affect the safety. It is also mandatory making a Safety Periodic Review (every 10 years in the case of El Cabril) that has to be presented to the Regulatory Council. This paper outlines the principles, objectives and criteria of El Cabril's disposal installation and it explains the safety assessment performed, for both LILW and VLLW disposal, as part of the documentation produced to obtain the authorization to operate. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nanoscale imaging of He-ion irradiation effects on amorphous TaO x toward electroforming-free neuromorphic functions

Resistive switching in thin films has been widely studied in a broad range of materials. Yet, the mechanisms behind electroresistive switching have been persistently difficult to decipher and control, in part due to their non-equilibrium nature. Here, we demonstrate new experimental approaches that can probe resistive switching phenomena, utilizing amorphous TaO x as a model material system. Specifically, we applied scanning microwave impedance microscopy and cathodoluminescence (CL) microscopy as direct probes of conductance and electronic structure, respectively. These methods provide direct evidence of the electronic state of TaO x despite its amorphous nature. For example, CL identifies characteristic impurity levels in TaO x , in agreement with first principles calculations. We applied these methods to investigate He-ion-beam irradiation as a path to activate conductivity of materials and enable electroforming-free control over resistive switching. However, we find that even though He-ions begin to modify the nature of bonds even at the lowest doses, the films' conductive properties exhibit remarkable stability with large displacement damage and they are driven to metallic states only at the limit of structural decomposition. Finally, we show that electroforming in a nanoscale junction can be carried out with a dissipated power of <20 nW, a much smaller value compared to earlier studies and one that minimizes irreversible structural modifications of the films. Importantly, the multimodal approach described here provides a new framework toward the theory/experiment guided design and optimization of electroresistive materials.

36 MATERIALS SCIENCE↗

Multipole groups and fracton phenomena on arbitrary crystalline lattices

Multipole symmetries are of interest in multiple contexts, from the study of fracton phases, to nonergodic quantum dynamics, to the exploration of new hydrodynamic universality classes. However, prior explorations have focused on continuum systems or hypercubic lattices. In this work, we systematically explore multipole symmetries on arbitrary crystal lattices. We explain how, given a crystal structure (specified by a space group and the occupied Wyckoff positions), one may systematically construct all consistent multipole groups. We focus on two-dimensional crystal structures for simplicity, although our methods are general and extend straightforwardly to three dimensions. We classify the possible multipole groups on all two-dimensional Bravais lattices, and on the Kagome and breathing Kagome crystal structures to illustrate the procedure on general crystal lattices. Using Wyckoff positions, we provide an in-principle classification of all possible multipole groups in any space group. We explain how, given a valid multipole group, one may construct a consistent lattice Hamiltonian and a low-energy field theory. We then explore the physical consequences, beginning by generalizing certain results originally obtained on hypercubic lattices to arbitrary crystal structures. Next, we identify two apparently novel phenomena: an emergent, robust subsystem symmetry on the triangular lattice, and an exact multipolar symmetry on the breathing Kagome lattice that does not include conservation of charge (monopole), but instead conserves a vector charge. This makes clear that there is new physics to be found by exploring the consequences of multipolar symmetries on arbitrary lattices, and this work provides the map for the exploration thereof, as well as guiding the search for emergent multipolar symmetries and the attendant exotic phenomena in real materials based on nonhypercubic lattices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Load Capacity Estimation of Foil Air Journal Bearings for Oil-Free Turbomachinery Applications

This paper introduces a simple "Rule of Thumb" (ROT) method to estimate the load capacity of foil air journal bearings, which are self-acting compliant-surface hydrodynamic bearings being considered for Oil-Free turbo-machinery applications such as gas turbine engines. The ROT is based on first principles and data available in the literature and it relates bearing load capacity to the bearing size and speed through an empirically based load capacity coefficient, D. It is shown that load capacity is a linear function of bearing surface velocity and bearing projected area. Furthermore, it was found that the load capacity coefficient, D, is related to the design features of the bearing compliant members and operating conditions (speed and ambient temperature). Early bearing designs with basic or "first generation" compliant support elements have relatively low load capacity. More advanced bearings, in which the compliance of the support structure is tailored, have load capacities up to five times those of simpler designs. The ROT enables simplified load capacity estimation for foil air journal bearings and can guide development of new Oil-Free turbomachinery systems.

DellaCorte, Christopher↗

Substrate effects on spin relaxation in two-dimensional Dirac materials with strong spin-orbit coupling

Understanding substrate effects on spin dynamics and relaxation is of key importance for spin-based information technologies. However, the key factors that determine such effects, in particular for materials with strong spin-orbit coupling (SOC), have not been well understood. Here we performed first-principles real-time density-matrix dynamics simulations with SOC and the electron phonon and electron-impurity scattering for spin lifetimes (τ s ) of supported/free-standing germanene, a prototypical strong SOC 2D Dirac material. We show that the effects of different substrates on τ s can surprisingly differ by two orders of magnitude. We find that substrate effects on τ s are closely related to substrate-induced modifications of the SOC-field anisotropy, which changes the spin flip scattering matrix elements. We propose a new electronic quantity, named spin-flip angle θ ↑↓ , to characterize spin relaxation through intervalley spin-flip scattering. We find that $τ^{-1}_s$ is approximately proportional to the averaged value of sin 2 (θ ↑↓ /2), which serves as a guiding parameter of controlling spin relaxation.

36 MATERIALS SCIENCE↗

Enhancing Cloud Cybersecurity: Prescriptive Controls for Operational Technology

This whitepaper provides strategic insights and recommendations into security cloud-based solutions for electric utilities, encompassing operational technology (OT), virtual power plants (VPP), distributed energy resources (DERs), applications, networks, and data storage as they transition to and leverage cloud infrastructure through managed service providers (MSPs) and cloud service providers (CSPs). Principles derived from established frameworks serve as a foundation for best practices across cybersecurity projects and remove the constraints of settling on a single framework. For organizations that prefer not to integrate a specific framework altogether, elements of the proposed approach could be adopted or tailored to best fit defined requirements and expected functionalities. The Cirrus assessment, a utility cloud feasibility tool, and the roadmap it provides serve as a precursor to this paper, which seeks to be a valuable resource for defining next steps following cloud technology integration feasibility appraisal. With its comprehensive approach to adoption, the Cirrus framework offers strategic guidance on responsibly preparing for or deploying a utility cloud solution. The previously published whitepaper, “Use Case-Informed Framework for Utility Cloud Migration,” details the guiding strategy, research, and deployment of cloud solutions within electric and interconnected grid systems. Before implementing the controls suggested in this document, it is recommended that stakeholders complete Cirrus's cloud integration assessment and pair the results with their unique cybersecurity controls to form a comprehensive cloud-based utility cybersecurity plan. The Cirrus outcome will consider a series of future architectures for the grid before and after the energy transition and evaluate the arguments for and against cloud applications for each electric and interconnected grid layer. This document is a companion to the original whitepaper, "Use Case-Informed Framework for Utility Cloud Migration" to further identify and recommend security controls based on Cirrus’s cloud integration assessment output. The following whitepaper outlines the cybersecurity controls that secure cloud-service models pertinent to the electric sector using the predefined categories identify, protect, detect, and respond and recover. The objective is to outline prescriptive security controls based on the type of architecture and data stored in the cloud. The focus includes dissecting the shared responsibility model and elucidating what on-premises Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) entail. A pivotal consideration in this context is allocating responsibility for foundational cybersecurity aspects—having used Cirrus for the cloud integration assessment. The ensuing controls detailed herein also represent a checklist of controls necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and strategic foresight in a safe and responsible manner.

42 ENGINEERING↗

Rational Design Principles for the Transport and Subcellular Distribution of Nanomaterials into Plant Protoplasts

The ability to control the subcellular localization of nanoparticles within living plants offers unique advantages for targeted biomolecule delivery and enables important applications in plant bioengineering. However, the mechanism of nanoparticle transport past plant biological membranes is poorly understood. Here, a mechanistic study of nanoparticle cellular uptake into plant protoplasts is presented. An experimentally validated mathematical model of lipid exchange envelope penetration mechanism for protoplasts, which predicts that the subcellular distribution of nanoparticles in plant cells is dictated by the particle size and the magnitude of the zeta potential, is advanced. The mechanism is completely generic, describing nanoparticles ranging from quantum dots, gold and silica nanoparticles, nanoceria, and single-walled carbon nanotubes (SWNTs). In addition, the use of imaging flow cytometry to investigate the influence of protoplasts' morphological characteristics on nanoparticle uptake efficiency is demonstrated. Using DNA-wrapped SWNTs as model nanoparticles, it is found that glycerolipids, the predominant lipids in chloroplast membranes, exhibit stronger lipid–nanoparticle interaction than phospholipids, the major constituent in protoplast membrane. This work can guide the rational design of nanoparticles for targeted delivery into specific compartments within plant cells without the use of chemical or mechanical aid, potentially enabling various plant engineering applications.

36 MATERIALS SCIENCE↗

The ballad of LLM agents: philosophical reasoning for chemistry

Large language models (LLMs) show remarkable potential for scientific reasoning but often produce unreliable or scientifically unactionable outputs when faced with multi-step logic, domain grounding, and interpretability challenges, especially in complex fields like chemistry and materials science. Here, we introduce a framework of philosophical reasoning agents, inspired by canonical thinkers such as Socrates, Descartes, Kant, and Hume, to guide LLM behavior via structured prompt engineering. These agents embody distinct reasoning paradigms (dialectical inquiry, deductive logic, rule-based judgment, and empirical validation) and are evaluated across multiple chemistry subdomains, physical, analytical, general, inorganic, and organic chemistry, using the ChemBench benchmark. Our agentic prompting approach yields substantial accuracy gains on open-ended numerical chemistry questions, with gains of +11.5 percentage points for GPT-4o with Hume, +4.5 percentage points for GPT-5 with Kant, and +21.8 percentage points for GPT-5.1 with Socrates at the strict 1% error threshold, relative to the corresponding base models. Beyond accuracy, we observe benchmark-level model–agent performance patterns, suggesting that different prompting styles interact differently with each base model. These findings demonstrate that embedding philosophy-of-science principles into multi-agent frameworks can improve and produce interpretable, adaptive, and domain-aligned scientific LLMs.

Harb, Hassan [Argonne National Laboratory (ANL), A↗

First-Principles Characterization of Surface Phonons of Halide Perovskite CsPbI 3 and Their Role in Stabilization

The stability of halide perovskites has been a long-standing issue for their real-world application. Approaches to improve stability include nanostructuring, dimensionality reduction, and strain engineering, where surfaces play an important role in the formation of a stable structure. To understand the mechanism we compute the lattice dynamics of the surface of CsPbI 3 using density functional theory. We demonstrate, for the first time, that CsPbI 3 crystals exhibit surface phonons that are localized on the outermost layers of the slabs, and we perform a complete symmetry characterization including an identification of the Raman/IR active modes. These surface phonons are present in the optically active cubic phase but are absent in the optically inactive "yellow" phase. Furthermore, we show that the surface suppresses bulk instabilities by hardening soft modes of the bulk cubic phase, resulting in phase stabilization and quenching of dynamical disorder. Finally, this study is fundamental for understanding the structural behavior of halide perovskite materials with high surface area-to-volume ratios, and for guiding stabilization strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Charged Defects in UO 2 Bulk and Surface: A First-Principles Study

Uranium dioxide (UO 2 ) is the primary fuel used in nuclear reactors. Under the extreme heat and radiation inside a reactor, this material inevitably develops defects in its crystal structure. To investigate the nature and behavior of these defects, DFT+U calculations were employed to investigate charged point defects in both bulk UO 2 and its most stable surface, the (111) plane. The formation of defects and their impact on the electronic structure were systematically examined. The results reveal that these defects introduce localized electronic states, alter magnetic behavior, and modify the structural properties. In general, such defects act as deep traps capable of capturing and retaining charge carriers. The stability of these defects depends strongly on the chemical environment and the position of the Fermi level. Surface defect calculations reveal that oxygen vacancies form more readily at the surface than in the bulk over a wide range of electron chemical potential, with subsurface oxygen vacancies being more stable than those in the top layer. Overall, the findings demonstrate how charged defects influence magnetism, transport, and stability in UO 2 , providing insights that may guide improvements in the safety and efficiency of nuclear fuel.

36 MATERIALS SCIENCE↗

Energy and momentum conservation in the Euler–Poincaré formulation of local Vlasov–Maxwell-type systems

The action principle by Low for the classic Vlasov–Maxwell system contains a mix of Eulerian and Lagrangian variables. This renders the Noether analysis of reparametrization symmetries inconvenient, especially since the well-known energy- and momentum-conservation laws for the system are expressed in terms of Eulerian variables only. While an Euler–Poincaré formulation of Vlasov–Maxwell-type systems, effectively starting with Low's action and using constrained variations for the Eulerian description of particle motion, has been known for a while Cendra et al, it is hard to come by a documented derivation of the related energy- and momentum-conservation laws in the spirit of the Euler–Poincaré machinery. To our knowledge only one such derivation exists in the literature so far, dealing with the so-called guiding-center Vlasov–Darwin system Sugama et al. The present exposition discusses a generic class of local Vlasov–Maxwell-type systems, with a conscious choice of adopting the language of differential geometry to exploit the Euler–Poincaré framework to its full extent. After reviewing the transition from a Lagrangian picture to an Eulerian one, we demonstrate how symmetries generated by isometries in space lead to conservation laws for linear- and angular-momentum density and how symmetry by time translation produces a conservation law for energy density. Here, we also discuss what happens if no symmetries exist. Finally, two explicit examples will be given—the classic Vlasov–Maxwell and the drift-kinetic Vlasov–Maxwell—and the results expressed in the language of regular vector calculus for familiarity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The information content of jet quenching and machine learning assisted observable design

Jets produced in high-energy heavy-ion collisions are modified compared to those in proton-proton collisions due to their interaction with the deconfined, strongly-coupled quark-gluon plasma (QGP). In this work, we employ machine learning techniques to identify important features that distinguish jets produced in heavy-ion collisions from jets produced in proton-proton collisions. We formulate the problem using binary classification and focus on leveraging machine learning in ways that inform theoretical calculations of jet modification: (i) we quantify the information content in terms of Infrared Collinear (IRC)-safety and in terms of hard vs. soft emissions, (ii) we identify optimally discriminating observables that are in principle calculable in perturbative QCD, and (iii) we assess the information loss due to the heavy-ion underlying event and background subtraction algorithms. We illustrate our methodology using Monte Carlo event generators, where we find that important information about jet quenching is contained not only in hard splittings but also in soft emissions and IRC-unsafe physics inside the jet. This information appears to be significantly reduced by the presence of the underlying event. We discuss the implications of this for the prospect of using jet quenching to extract properties of the QGP. Since the training labels are exactly known, this methodology can be used directly on experimental data without reliance on modeling. We outline a proposal for how such an experimental analysis can be carried out, and how it can guide future measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Identification of Ebola Virus Inhibitors Targeting GP2 Using Principles of Molecular Mimicry

A key step in the Ebola virus (EBOV) replication cycle involves conformational changes in viral glycoprotein 2 (GP2) which facilitate host-viral membrane fusion and subsequent release of the viral genome. Ebola GP2 plays a critical role in virus entry and has similarities in mechanism and structure to the HIV gp41 protein for which inhibitors have been successfully developed. In this work, a putative binding pocket for the C-terminal heptad repeat in the N-terminal heptad repeat trimer was targeted for identification of small molecules that arrest EBOV-host membrane fusion. Two computational structure-based virtual screens of ~1.7 M compounds were performed (DOCK program) against a GP2 five-helix bundle, resulting in 165 commercially available compounds purchased for experimental testing. Based on assessment of inhibitory activity, cytotoxicity, and target specificity, four promising candidates emerged with 50% inhibitory concentration values in the 3 to 26 μM range. Molecular dynamics simulations of the two most potent candidates in their DOCK-predicted binding poses indicate that the majority of favorable interactions involve seven highly conserved residues that can be used to guide further inhibitor development and refinement targeting EBOV. The most recent Ebola virus disease outbreak, from 2014 to 2016, resulted in approximately 28,000 individuals becoming infected, which led to over 12,000 causalities worldwide. The particularly high pathogenicity of the virus makes paramount the identification and development of promising lead compounds to serve as inhibitors of Ebola infection. To limit viral load, the virus-host membrane fusion event can be targeted through the inhibition of the class I fusion glycoprotein of. In the current work, several promising small-molecule inhibitors that target the glycoprotein GP2 were identified through systematic application of structure-based computational and experimental drug design procedures.

59 BASIC BIOLOGICAL SCIENCES↗

Variational Excitations in Real Solids: Optical Gaps and Insights into Many-Body Perturbation Theory

We present an approach to studying optical band gaps in real solids in which quantum Monte Carlo methods allow for the application of a rigorous variational principle to both ground and excited state wave functions. In tests that include small, medium, and large band gap materials, optical gaps are predicted with a mean absolute deviation of 3.5% against experiment, less than half the equivalent errors for typical many-body perturbation theories. The approach is designed to be insensitive to the choice of density functional, a property we exploit in order to provide insight into how far different functionals are from satisfying the assumptions of many-body perturbation theory. Here, we explore this question most deeply in the challenging case of ZnO, where we show that, although many commonly used functionals have shortcomings, there does exist a one-particle basis in which perturbation theory’s zeroth-order picture is sound. Insights of this nature should be useful in guiding the future application and improvement of these widely used techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Principles of stereo reconstruction of aerial objects using stationary cameras

An overview is given here of the principles and mathematics of stereo reconstruction of objects in the sky using stationary cameras with an emphasis on meteorological applications. Through its Atmospheric Radiation Measurement program, the Department of Energy has operated stereo-photogrammetric cameras since 2017 as part of an effort to measure the life-cycle properties of clouds. At the core of that technology is stereo reconstruction, which calculates the real-world position of an object from the location of the object’s image in two cameras’ photographs. Here, stereo reconstruction is stripped down to its basic elements and presented using conventions tailored to applications in atmospheric science. In addition, the resulting equations are used to illustrate the high sensitivity of reconstructed cloud positions to errors in the cameras’ Euler angles. The interested reader will find here a self-contained guide to performing stereo reconstructions using distortion-corrected images from a pair of calibrated, stationary cameras, as well as a demonstration of the need for high accuracy in the measurement of camera properties and orientations.

47 OTHER INSTRUMENTATION↗

Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

54 ENVIRONMENTAL SCIENCES↗

First-Principles Examination of Multiple Criteria of Organic Solvent Oxidative Stability in Batteries

Oxidative instability of the liquid electrolyte at or near battery cathode oxide surfaces has significant detrimental effects on batteries. Organic solvent molecules are often the fuel and precursors of such degradation processes, releasing electrons and protons that react with cathode oxides and electrolyte anions. These reactions contribute to cathode–electrolyte interphase (CEI) film formation, transition-metal ion dissolution, and phase transformation of the surface regions of the cathode. Here we apply density functional theory calculations to examine four criteria of oxidative stability (oxidation potential, hydrogen removal energies, and initial reactivity on two types of oxide facets) using four different solvent/additive molecules (ethylene carbonate, fluoroethylene carbonate, 1,3-dioxolane, and dimethyl ether). The ranking of molecular stability differs with each criterion. Surprisingly, the all-oxygen-terminated basal planes of layered oxides exhibit lower reaction barriers than spinel surface facets with exposed transition-metal cations, especially for ether solvents; the calculations also suggest basal planes contribute to the dissolution of transition-metal ions. Further, the structure–degradation relation complexity underscores the challenge of understanding the function of the CEI but also offers a guide to future degradation-mitigation strategies including facet engineering. Our predictions and models help establish a framework for future studies relevant to high-voltage conditions.

25 ENERGY STORAGE↗