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DOE OSTI2024

Strain Field Around Individual Dislocations Controls Failure

Understanding material failure on a fundamental level is a key aspect in the design of robust structural materials, especially for metals and alloys capable to undergo plastic deformation. In the last decade, significant progress is made in quantifying the stresses associated with failure in both experiments and simulations. Nonetheless, the processes occurring on the most essential level of individual dislocations that govern semi-brittle and ductile fracture are still experimentally not accessible, limiting the failure prediction capabilities. Therefore, in the present work, a one-of-a-kind nanoscale fracture experiment is conducted on a single crystalline Cr bending beam in situ in the transmission electron microscope and for the first time quantify the transient strains around individual dislocations, as well as of the whole dislocation network during crack opening. The results reveal the importance of both pre-existing and newly emitted dislocations for crack-tip shielding via their intrinsic strain field and provide guidelines to design more damage tolerant materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Coordinated Thermal Safety Attack and Defense on EV Battery Management Systems

Battery temperature sensor and battery current sensor data which are key sensing inputs to the Battery Management Controllers in electric vehicles, are vulnerable to possible cyber/ physical manipulation due to known vulnerabilities inherited from CAN bus technology that is used for in-vehicle communications between electronic control units that transfer sensing and control data. In this paper, we first create a simulation that enables us to evaluate impact of cyber physical attacks on electric vehicle battery management system in a controlled environment that violates thermal safety. Specifically, we emulate a Level 3 - DC fast charging system with SAE J1772/CCS, integrated with standard charging controls and thermal safety controls on EVs, and various sensing data flows. Second, we propose a coordinated current and battery temperature attack that has crippling economic, and safety impacts. Third, we quantify the usability, economic and safety impacts of such attacks as a function of the extent of data manipulation. Finally, we propose a physics model driven detection technique to detect presence of such attacks.

25 ENERGY STORAGE↗

DOE OSTI2024

Opportunities for fundamental physics research with radioactive molecules

Molecules containing short-lived, radioactive nuclei are uniquely positioned to enable a wide range of scientific discoveries in the areas of fundamental symmetries, astrophysics, nuclear structure, and chemistry. Recent advances in the ability to create, cool, and control complex molecules down to the quantum level, along with recent and upcoming advances in radioactive species production at several facilities around the world, create a compelling opportunity to coordinate and combine these efforts to bring precision measurement and control to molecules containing extreme nuclei. In this paper, we review the scientific case for studying radioactive molecules, discuss recent atomic, molecular, nuclear, astrophysical, and chemical advances which provide the foundation for their study, describe the facilities where these species are and will be produced, and provide an outlook for the future of this nascent field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

The Impact of Carotenoid Energy Levels on the Exciton Dynamics and Singlet–Triplet Annihilation in Isolated Bacterial Light-Harvesting 2 Complexes

The light-harvesting 2 (LH2) complex of purple phototrophic bacteria plays a critical role in absorbing solar energy and distributing the excitation energy. Exciton dynamics within LH2 complexes are controlled by the structural arrangement and energy levels of the bacteriochlorophyll (BChl) and carotenoid (Car) pigments. However, there is still debate over the competing light-harvesting versus energy-dissipation pathways. In this work, we compared five variants of the LH2 complex from genetically modified strains of Rhodobacter sphaeroides, all containing the same BChls but different Cars with increasing conjugation: zeta-carotene (N = 7; LH2 Zeta ), neurosporene (N = 9; LH2 Neu ), spheroidene (N = 10; LH2 Spher ), lycopene (N = 11; LH2 Lyco ), and spirilloxanthin (N = 13; LH2 Spir ). Absorption measurements confirmed that the Car excited-state energy decreased with increasing conjugation. Similarly, fluorescence spectra showed that the B850 BChl emission peak had an increasing red shift from LH2 Zeta →(LH2 Neu /LH2 Spher )→LH2 Lyco →LH2 Spir . In contrast, time-resolved fluorescence and ultrafast transient absorption (fs-TA) revealed similar excited-state lifetimes (∼1 ns) for all complexes except LH2 Spir (∼0.7 ns). From fs-TA analysis, an additional ∼7 ps nonradiative dissipation step from B850 BChl was observed for LH2 Zeta . Further, singlet− singlet and singlet−triplet annihilation studies showed a ∼50% average fluorescence lifetime reduction in LH2Zeta at high laser power and high repetition rate, compared to ∼10−15% reductions in LH2 Neu /LH2 Spher /LH2 Lyco and minimal lifetime change in LH2 Spir . In LH2 Zeta , the fastest decay component (<50 ps) became prominent at high repetition rates, consistent with strong singlet−triplet annihilation. Nanosecond TA measurements revealed long-lived (>40 μs) BChl triplet states in LH2 Zeta and signs of damage caused by singlet oxygen, whereas other LH2s showed faster triplet quenching (∼18 ns) by Cars. These findings highlight a key design principle of LH2 complexes: the Car triplet energy must be significantly lower than the BChl triplet energy to efficiently quench BChl triplets that otherwise act as potent “trap states,” causing exciton annihilation in laser-based experiments or photodamage in native membranes.

Absorption↗

DOE OSTI2024

Simulation of gas mixture dynamics in a pipeline network using explicit staggered-grid discretization

Here we develop an explicit staggered finite difference discretization scheme for simulating the transport of highly heterogeneous gas mixtures through pipeline networks. This study is motivated by the proposed blending of hydrogen into natural gas pipelines to reduce end use carbon emissions while using existing pipeline systems throughout their planned lifetimes. Our computational method accommodates an arbitrary number of constituent gases with very different physical properties that may be injected into a network with significant spatiotemporal variation. In this setting, the gas flow physics are highly location- and time- dependent, so that local composition and nodal mixing must be accounted for. The resulting conservation laws are formulated in terms of pressure, partial densities and flows, and volumetric and mass fractions of the constituents. We include non-ideal equations of state that employ linear approximations of gas compressibility factors, so that the pressure dynamics propagate locally according to a variable wave speed that depends on mixture composition and density. We derive compatibility relationships for network edge boundary values that are more complex than for a homogeneous gas. The simulation method is evaluated on initial boundary value problems for a single pipe and a small network, is cross-validated with a lumped element simulation, and used to demonstrate a local monitoring and control policy for maintaining allowable concentration levels.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Multilevel Analysis of Electrochemically Mediated Methanolysis of Poly(ethylene terephthalate) (PET)

Here, this study presents a multilevel analysis of electrochemically mediated methanolysis as a promising method for reducing the environmental impacts of plastic recycling, with a focus on depolymerizing poly(ethylene terephthalate) (PET) into dimethyl terephthalate (DMT). Instead of conventional chemical PET depolymerization, this electrochemical approach provides distinct technical advantages in process control and efficiency. At the process level, key operational parameters, including applied current and reaction time, were systematically investigated to optimize PET conversion and DMT selectivity. The electrochemical approach was directly compared to equivalent chemical methanolysis systems and demonstrated superior performance in terms of PET conversion and DMT selectivity. Building on these findings, a technoeconomic assessment identified the current economic bottlenecks and revealed that improvements in process design, DMT selectivity, PET conversion, and energy efficiency are key to reducing the overall process cost and enabling future implementation. While further optimization is required for market competitiveness, these results establish a performance baseline for the electrochemically mediated PET methanolysis process and underscore the importance of combining process-level innovation with systems-level evaluation in the development of sustainable recycling technologies.

chemical recycling↗

DOE OSTI2024

Role of Tensile Stress in DNA Nanoresonators for Epigenetic Studies

The evaluation of epigenetic features such as DNA methylation is becoming increasingly important in many biochemical processes like gene expression and transcription as well as in several diseases like schizophrenia or diabetes. Here, in this work, we report that self-assembled nanomechanical resonators entirely composed of DNA molecules can be used to explore gross changes in DNA methylation levels (0–25–50%), while careful control of tensile stress is needed to reduce the variability of resonance frequency for rigorous quantification. The effect of the tensile stress retained by the suspended DNA nanoresonators on the application of the technique is extensively explored using a combination of laser Doppler vibrometry and atomic force spectroscopy. DNA nanoresonators are real-time, label-free sensors and could avoid chemical functionalization and sample amplification. Therefore, they may represent in the future a key complementary routine tool for global DNA methylation analysis needed to evaluate the consequences of environmental stresses on the human genome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Mo Atom Rearrangement Drives Layer-Dependent Reactivity in Two-Dimensional MoS 2

Two-dimensional (2D) materials offer a valuable platform for manipulating and studying chemical reactions at the atomic level, owing to the ease of controlling their microscopic structure at the nanometer scale. While extensive research has been conducted on the structure-dependent chemical activity of 2D materials, the influence of structural transformation during the reaction has remained largely unexplored. In this work, we report the layer-dependent chemical reactivity of MoS 2 during a nitridation atomic substitution reaction and attribute it to the rearrangement of Mo atoms. Our results show that the chemical reactivity of MoS 2 decreases as the number of layers is reduced in the few-layer regime. In particular, monolayer MoS 2 exhibits significantly lower reactivity compared with its few-layer and multilayer counterparts. Atomic-resolution transmission electron microscopy (TEM) reveals that MoN nanonetworks form as reaction products from monolayer and bilayer MoS 2 , with the continuity of the MoN crystals increasing with layer number, consistent with the local conductivity mapping data. The layer-dependent reactivity is attributed to the relative stability of the hypothetically formed MoN phase, which retains the number of Mo atomic layers present in the precursor. Specifically, the low chemical reactivity of monolayer MoS 2 is attributed to the high energy cost associated with Mo atom diffusion and migration necessary to form multilayer Mo lattices in the thermodynamically stable MoN phase. In conclusion, this study underscores the critical role of lattice rearrangement in governing chemical reactivity and highlights the potential of 2D materials as versatile platforms for advancing the understanding of materials chemistry at the atomic scale.

Chemical reactivity↗

DOE OSTI2024

Metal–support interactions in metal oxide-supported atomic, cluster, and nanoparticle catalysis

Supported metal catalysts are essential to a plethora of processes in the chemical industry. The overall performance of these catalysts depends strongly on the interaction of adsorbates at the atomic level, which can be manipulated and controlled by the different constituents of the active material (i.e., support and active metal). The description of catalyst activity and the relationship between active constituent and the support, or metal–support interactions (MSI), in heterogeneous (thermo)catalysts is a complex phenomenon with multivariate (dependent and independent) contributions that are difficult to disentangle, both experimentally and theoretically. So-called “strong metal–support interactions” have been reported for several decades and summarized in excellent review articles. However, in recent years, there has been a proliferation of new findings related to atomically dispersed metal sites, metal oxide defects, and, for example, the generation and evolution of MSI under reaction conditions, which has led to the designation of (sub)classifications of MSI deserving to be critically and systematically evaluated. These include dynamic restructuring under alternating redox and reaction conditions, adsorbate-induced MSI, and evidence of strong interactions in oxide-supported metal oxide catalysts. Here, we review recent literature on MSI in oxide-supported metal particles to provide an up-to-date understanding of the underlying physicochemical principles that dominate the observed effects in supported metal atomic, cluster, and nanoparticle catalysts. Critical evaluation of different subclassifications of MSI is provided, along with discussions on the formation mechanisms, theoretical and characterization advances, and tuning strategies to manipulate catalytic reaction performance. We also provide a perspective on the future of the field, and we discuss the analysis of different MSI effects on catalysis quantitatively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Control Co-Design Studies for a 22 MW Semisubmersible Floating Wind Turbine Platform

We present a control co-design software framework that can be used to optimize floating wind turbines and their controllers. Because this framework has many options for design variables, constraints, and merit figures, along with modeling fidelity levels, we seek to demonstrate best practices for using the tool while designing a floating platform for the new 22 MW offshore reference wind turbine developed within the International Energy Agency Wind Technology Commercialization Programme 55 on Reference Wind Turbines and Farms. During these studies, we evaluate the use of different simulation fidelity levels, the effect of using different load cases for controller tuning, and the difference between sequential and simultaneous control co-design solutions. Based on these efforts, we suggest using an algorithm that performs an initial search of the design space before optimization. We find that solving smaller optimization problems, in a sequential manner, leads to more reliable outcomes in fewer iterations than larger, simultaneous control co-design solutions. However a simultaneous CCD solution produces a platform with a 2% lower mass than the sequential CCD outcome.

17 WIND ENERGY↗

DOE OSTI2025

Benchmarking the performance of a high-Q cavity qudit using random unitaries

High-coherence cavity resonators are excellent resources for encoding quantum information in higher-dimensional Hilbert spaces, moving beyond traditional qubit-based platforms. A natural strategy is to use the Fock basis to encode information in qudits. One can perform quantum operations on the cavity mode qudit by coupling the system to a non-linear ancillary transmon qubit. However, the performance of the cavity-transmon device is limited by the noisy transmons. It is, therefore, important to develop practical benchmarking tools for these qudit systems in an algorithm-agnostic manner. We gauge the performance of these qudit platforms using sampling tests such as the heavy output generation test as well as the linear cross-entropy benchmark, by way of simulations of such a system subject to realistic dominant noise channels. We use selective number-dependent arbitrary phase and unconditional displacement gates as our universal gateset. Our results show that contemporary transmons comfortably enable controlling a few tens of Fock levels of a cavity mode. This framework allows benchmarking even higher dimensional qudits as those become accessible with improved transmons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Brachypodium SPEECHLESS2 Promoter Drives Expression of a Synthetic EPF to Reduce Stomatal Density in Sugarcane Without Pleiotropic Effects

Stomata are microscopic pores that regulate the exchange of CO 2 and water vapour, making them a major target for engineering plants with improved intrinsic water use efficiency (iWUE). Proof-of-concept studies have demonstrated the potential to increase iWUE by reducing stomatal density (SD) and stomatal conductance (g sw ) by ubiquitously expressing EPIDERMAL PATTERNING FACTOR (EPF) family genes. However, unwanted effects on leaf, stem and reproductive traits are often observed when EPFs are misexpressed in this fashion. We sought to test if these effects result from pleiotropy and to identify a targeted promoter that can circumvent the side effects while retaining the desired reduction in SD. A previously reported synthetic EPF (EPF syn ) was expressed in sugarcane ( Saccharum spp.) using two putatively tissue-specific promoters from Brachypodium distachyon (BdCESA7p and BdSPCH2p) and a ubiquitous control from Zea mays (ZmUBI4p). BdSPCH2p control reduced SD to statistically equivalent levels as ZmUBI4p on the abaxial (23%) and adaxial (23%) leaf surfaces. ZmUB4p and BdCESA7p induce expression in four tissue types often associated with pleiotropic effects in EPF-expressing low SD plants. Transgenic plants carrying either the BdCESA7p or ZmUBI4p EPF syn cassettes displayed leaf chlorosis, reduced leaf nitrogen and chlorophyll content, and altered stem architecture. However, transgenic events harboring the BdSPCH2p EPF syn cassette restricted EPF syn expression to the stomatal development zone and leaf nodal tissues and produced transgenic plants without the associated pleiotropic effects. These results represent an important step toward engineering low-SD crops since they show that targeted gene expression can engineer stomatal patterning without impairing agronomically important traits.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Intelligent Partitioning based Fully Parallel AC Security-Constrained Optimal Power Flow

Today’s power grid is becoming more diverse and integrated with high-level distributed energy resources and smart control technologies that is creating a new set of grid management challenges in terms of large-scale, nonlinear, and non-convex problem modeling, complex and time-consuming computation, as well as difficult uncertainty handling. This project focused on solving a challenging multi-period security-constrained generation scheduling problem, which is of great importance for maximizing the social welfare of real-time dispatch, day-ahead market, as well as weekly planning of power systems. Our developed software explored parallel optimization algorithms for complex and realistic power system models, and develop fast, efficient, and robust grid optimization solutions on the high-performance computing platform that will enable increased grid economics, flexibility, resilience, as well as energy security in the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

A Solar Fuels Nexus: Molecules and Materials for Light-Driven Catalysis

The American Chemical Society (ACS) selects two groups of graduate students each year to plan and host a one-day symposium at each national meeting (both fall and spring).This year our Graduate Student Symposium Planning Committee (GSSPC), composed of seven students from four universities, proposal entitled “A Solar Fuels Nexus: Molecules and Materials for Light-Driven Catalysis” was selected for the “Crossroads in Chemistry” ACS Meeting that will take place March 23-26, 2023 in Indianapolis, IN. All members of our GSSPC are affiliated with the DOE Fuels from Sunlight Energy Innovation Hub, with two from the Liquid Sunlight Alliance (LiSA) and five from the Center for Hybrid Approaches in Solar Energy to Liquid Fuels (CHASE). Here we request funds to support this symposium. This symposium will highlight research progress and perspectives in the solar fuels generation field and seeks to advance the four priority research objectives (PROs) established by the Department of Energy’s Office of Basic Energy Sciences (DOE-BES) Roundtable Report that are also central to many research goals within LiSA and CHASE. The symposium will consist of research presentations from 10 invited senior researcher speakers on topics such as molecular catalyst design, computational modeling of electron transfer systems, microenvironmental effects on CO2 reduction and H2O oxidation catalysis, and intelligent design of semiconductor interfaces with ample time for discussions. These research topics fit very well with the Solar Photochemistry supported research areas of “light-driven electron and energy transfer in condensed phase and interfacial molecular systems,” “electrocatalysis and photocatalysis of solar fuels reactions,” and “semiconductor photoelectrochemistry.” More broadly, this symposium seeks to advance the DOE-BES’s mission to: “support fundamental research to understand, predict, and ultimately control matter and energy at the level of electrons, atoms, and molecules” by providing a diverse atmosphere where such research will be disseminated, discussed, and debated. There will be a strong focus on Diversity, Equity, and Inclusivity (DEI) in our symposium. Of our 10 speakers, 7 will be from underrepresented demographics in STEM, including 5 who identify as women. Furthermore, we have representatives from academia accompanied by one national lab scientist and one officer from the Office of Fossil Energy and Carbon Management at the DOE. All speakers will be holding a short DEI moment ahead of their talks. In order to support the career development of attending early career scientists, we will also be hosting a luncheon specifically for graduate students and postdocs to provide them opportunities to network with the distinguished speakers and other attendees. DOE funds for this symposium will be used to support the attendance and participation of 15 graduate students from US institutions by defraying travel and registration costs. These funds will promote engagement and conversation between early career scientists in the solar fuels field, while disseminating solar fuels research funded by and relevant to the DOE.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

42 ENGINEERING↗

DOE OSTI2025

Radio Frequency Algorithms

Final Technical Report for DOE SC0019287 award titled Radio Frequency Algorithms. This project supported the design, simulation, analysis, and optimization of robust algorithms to configure, optimize, and control Radio Frequency and Low-Level RF systems for several modern accelerator systems.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

The GREEN ‘omics of Nutrient Feedbacks to Soil Warming

The GREEN ‘omics of Nutrient Feedbacks in Soil project advanced the DOE Biological and Environmental Research (BER) mission by developing and applying isotope-enabled ’omics tools to understand how soil microbes regulate carbon and nutrient cycling. Guided by the Growth Rate, growth Efficiency, and stoichiometry of Essential Nutrients (GREEN ’omics) framework, the project aimed to build a predictive, systems-level understanding of microbial traits that control ecosystem biogeochemistry. In a collaboration among Northern Arizona University (lead), West Virginia University, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory, we combined quantitative stable isotope probing (qSIP), Chip-SIP, NanoSIMS, and genome-resolved metagenomics across long-term experiments in Arctic, boreal, temperate, and tropical ecosystems. The project produced three key outcomes: 1) We showed that community-weighted temperature sensitivities of bacterial growth (Q10) can predict ecosystem-scale soil respiration responses across diverse soils. 2) We provided the first in situ evidence for density-dependent population dynamics in soil bacteria and demonstrated that nutrient additions intensify competition, concentrating carbon use into fewer taxa. 3) We improved and extended isotope-enabled ’omics methods by quantifying qSIP measurement error to guide experimental design and coupling SIP with genome-resolved metagenomics to reveal cross-kingdom interactions among bacteria, fungi, and viruses. Together, these results show that a small number of microbial traits and taxa exert disproportionate control over soil carbon and nutrient cycling, providing critical data and methods to improve representation of microbial processes in Earth system models.

54 ENVIRONMENTAL SCIENCES↗