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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
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DOE OSTI2025

Final Report for Theoretical High Energy Physics at the University of New Hampshire

This award supported the research activities three faculty in the University of New Hampshire Department of Physics and Astronomy: Dr. Chanda Prescod-Weinstein (PI), Dr. Per Berglund (Co-I), and Dr. David Mattingly (Co-I). These research activities broadly spanned areas of high energy physics that included dark matter cosmology, quantum gravity, and string theory.

Prescod-Weinstein, Chanda [University of New Hamps↗
DOE OSTI2025

Preparation and Qualification of Preproduction SSR2 Jacketed Cavities for PIP-II

The qualification of 325 MHz Single Spoke Resonators type 2 (SSR2) jacketed cavities to meet technical requirements represents a significant milestone in the development of the SSR2 cryomodules for the PIP-II Project at Fermilab. This poster reports the procedures and lessons learned in processing and preparing these cavities for horizontal cold testing prior to integration into a cavity string assembly, with a focus on addressing the field emission issues observed during the cold testing. A comprehensive root cause analysis identified critical fabrication, processing, and handling factors impacting field emission onset. New techniques were successfully developed and implemented to achieve field emission-free SSR2 cavities, and efforts were made to correlate radiation levels measured at the test stand with expected levels in the LINAC tunnel. Additionally, the evolution of field emission through assembly steps was thoroughly investigated, leading to a reassessment of design choices and enhancing our understanding of their effects on cavity performance.

Grassellino, L. [Fermilab]↗
DOE OSTI2026

Cavity Preparation and Assembly: Challenges and Future R&D Directions

This presentation described the state of the art in cavity string assembly for the LCLS-II, HE, and PIP-II projects, as well as cavity performance statistics. The presentation also described the knowledge gap, opportunities for improvement, and future R&D recommendations.

Wu, Genfa [Fermilab]↗
DOE OSTI2026

Calculations Document

Figure 1 shows a simplified model schematic of the Tetracage target design. In this figure the green lines represent the Tetracage yarns, which consist of two parallel yarns on the top and two parallel yarns on the bottom with the pairs in a cross hatched pattern. For simplicity, as we are only considering vertical forces, we will perform calculations without consideration for the two pairs of yarns being perpendicular to each other. Also worth noting is the model shows the yarns extending directly to the capsule then closely hugging it – in reality, the yarns behave as you would expect where they hug the capsule only as much as the geometry of their deflection allows, similarly to if you held a tennis ball with a pair of parallel strings anchored at opposing ends. The dashed black lines show the path the yarns take straight across from slot glue point to slot glue point before the target is closed and the capsule deforms them. The variable r corresponds to the capsule outer radius. The variable L corresponds to the hohlraum inner radius. The variable a corresponds to the yarn offset from the center of the diagnostic band. The variable d corresponds to the wire deflection vertically.

42 ENGINEERING↗
DOE OSTI2026

Cavity Preparation and Assembly: Challenges and Future R&D Directions

This presentation described the state of the art in cavity string assembly for the LCLS-II, HE, and PIP-II projects, as well as cavity performance statistics. The presentation also described the knowledge gap, opportunities for improvement, and future R&D recommendations.

Wu, Genfa [Fermilab]↗
DOE OSTI2026

SUSY 2025 at UC Santa Cruz (Final Technical Report)

The 32nd International Conference on Supersymmetry and the Unification of Fundamental Interactions (SUSY 2025) took place from August 18--23, 2025. During the week preceding the SUSY 2025 conference, the associated pre-SUSY school took place from August 11--15, 2025. Both events were organized and hosted by the Santa Cruz Institute for Particle Physics at the University of California, Santa Cruz. The SUSY 2025 conference brought together theorists and experimentalists specializing in particle physics, astroparticle physics, cosmology, mathematical physics, and string theory to discuss recent developments in these areas, with a focus on theoretical aspects and experimental searches associated with phenomena that lie beyond the Standard Model of particle physics and the standard mathematical framework of modern cosmology. The pre-SUSY school provided advanced pedagogical lectures for graduate students and early-career postdoctoral researchers on many of the foundational topics that were subsequently addressed in the main SUSY 2025 conference that followed. DOE support helped increase accessibility for early-career scientists by covering conference support costs that enabled free participation in the pre-SUSY school and substantially reduced registration fees for students attending the conference.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Mechanical Characterization of the NIF Ignition Target TMPSA Bonding Flexure

The Thermo-Mechanical Package Sub-Assembly (TMPSA) provides a critical mechanical, thermal, and electrical interface between a silicon arm and a TMP aluminum can in a NIF ignition target. During assembly, sixteen silicon pads are bonded to the aluminum using a fixture that positions the components and applies a repeatable prescribed displacement through a compliant flexure. The flexure converts fixture interference into displacement and reaction force. Because bondline thickness variation must be maintained within +/-4 µm, consistent flexure behavior is important to the assembly process. With a recent string of TMPSAs exhibiting low bond strength, the flexures were inspected. Despite being manufactured to the same specifications, flexures were found to exhibit variation in measured stiffness. Additionally, the measured stiffness values did not always follow the presumed beam mechanics model. This work addresses two questions: whether the bonding fixture is working as intended, and whether the previously made stiffness measurements are accurate representations of the use case. The flexures are analyzed using Euler-Bernoulli beam theory, measured beam dimensions, finite element analysis, and tolerance stack-up calculations. The analysis shows that the fixed-guided beam mechanics model appropriately represents the flexure during TMPSA bonding, but the chisel-tip stiffness measurement method introduces a deformation to the inner ring of the flexure that is not represented during use. The measured stiffness values should therefore be interpreted as test-condition stiffness values rather than direct measurements of operational flexure stiffness. The discrepancy is therefore attributed primarily to the measurement boundary condition rather than to failure of the fixed-guided beam model. Recommendations are provided for GD&T, dimensional inspection, and a representative stiffness testing method to better control bondline variation.

42 ENGINEERING↗
DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗
DOE OSTI2026

Automating Detection and Diagnosis of Faults, Failures, and Underperformance in PV Plants

The project developed hybrid physics-based and machine-learning methods for near-real-time detection of balance-of-system faults (e.g., string, combiner, and tracker outages) in utility-scale Photovoltaic plants, achieving over 50% true positive rates with under 10% false positives and significantly reducing engineering setup time. In the extended phase, the scope expanded to plant-level underperformance analysis and industry benchmarking through the SUPER.epri.com platform. SUPER standardizes data processing and performance metrics across more than 9 GWac and 120+ plants, enabling robust comparisons and insights into loss rates, inverter downtime, and capacity degradation.

14 SOLAR ENERGY↗
DOE OSTI2023

Avoiding symmetry roadblocks and minimizing the measurement overhead of adaptive variational quantum eigensolvers

Quantum simulation of strongly correlated systems is potentially the most feasible useful application of near-term quantum computers. Minimizing quantum computational resources is crucial to achieving this goal. A promising class of algorithms for this purpose consists of variational quantum eigensolvers (VQEs). Among these, problem-tailored versions such as ADAPT-VQE that build variational ansätze step by step from a predefined operator pool perform particularly well in terms of circuit depths and variational parameter counts. However, this improved performance comes at the expense of an additional measurement overhead compared to standard VQEs. Here, we show that this overhead can be reduced to an amount that grows only linearly with the number n of qubits, instead of quartically as in the original ADAPT-VQE. We do this by proving that operator pools of size 2 n − 2 can represent any state in Hilbert space if chosen appropriately. We prove that this is the minimal size of such "complete" pools, discuss their algebraic properties, and present necessary and sufficient conditions for their completeness that allow us to find such pools efficiently. We further show that, if the simulated problem possesses symmetries, then complete pools can fail to yield convergent results, unless the pool is chosen to obey certain symmetry rules. We demonstrate the performance of such symmetry-adapted complete pools by using them in classical simulations of ADAPT-VQE for several strongly correlated molecules. Our findings are relevant for any VQE that uses an ansatz based on Pauli strings.

Shkolnikov, V. O.↗
DOE OSTI2024

Confinement and Kink Entanglement Asymmetry on a Quantum Ising Chain

In this work, we explore the interplay of confinement, string breaking and entanglement asymmetry on a 1D quantum Ising chain. We consider the evolution of an initial domain wall and show that, surprisingly, while the introduction of confinement through a longitudinal field typically suppresses entanglement, it can also serve to increase it beyond a bound set for free particles. Our model can be tuned to conserve the number of domain walls, which gives an opportunity to explore entanglement asymmetry associated with link variables. We study two approaches to deal with the non-locality of the link variables, either directly or following a Kramers-Wannier transformation that maps bond variables (kinks) to site variables (spins). We develop a numerical procedure for computing the asymmetry using tensor network methods and use it to demonstrate the different types of entanglement and entanglement asymmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Quantum teleportation implies symmetry-protected topological order

We constrain a broad class of teleportation protocols using insights from locality. In the ``standard'' teleportation protocols we consider, all outcome-dependent unitaries are Pauli operators conditioned on linear functions of the measurement outcomes. We find that all such protocols involve preparing a ``resource state'' exhibiting symmetry-protected topological (SPT) order with Abelian protecting symmetry G k = ( Z 2 × Z 2 ) k . The k logical states are teleported between the edges of the chain by measuring the corresponding 2 k string order parameters in the bulk and applying outcome-dependent Paulis. Hence, this single class of nontrivial SPT states is both necessary and sufficient for the standard teleportation of k qubits. We illustrate this result with several examples, including the cluster state, variants thereof, and a nonstabilizer hypergraph state.

Hong, Yifan↗
DOE OSTI2025

Idiomatic Correctness-Checking via Julienne in Fortran 2023

This paper presents a unified approach to unit testing and runtime assertion checking using Fortran 2023. The paper describes the support for our approach in the Julienne framework. Julienne leverages recent Fortran standards to implement object-oriented design patterns, support testing parallel programs, and implement functional programming patterns in order to craft idioms inspired by natural-language expressions. The presented idioms employ novel operators to write expressions that evaluate to a test-diagnosis object encapsulating two components: (1) the test outcome or assertion outcome and (2) an automatically generated diagnostic string. Two other novel aspects of the approach include (1) the ability to enforce assertions inside pure procedures and (2) the ability to output rich diagnostic information inside pure procedures during error termination when assertions fail. The latter capability mitigates against a reason that Fortran programmers commonly cite for not writing pure procedures: difficulty obtaining useful program output inside pure procedures when debugging code. This paper demonstrates how the adoption of the proposed idioms leads naturally to a unifying theme across two otherwise disparate technologies: unit testing and runtime assertion checking. Finally, this paper describes the usage of the Julienne testing framework for writing unit tests and assertions in the Matcha high-performance computing application and the Fiats deep learning library.

Rouson, Damian↗
DOE OSTI2023

HT Model Dataset

This website contains the dataset that was used for writing the manuscript "HT Model: Using the Molecular Transformer for predicting hydrotreating reactions" (PNNL-SA-186589) The dataset includes a collection of hydrotreating reactions compiled from 41 peer-reviewed literature sources. These sources contain experimental data related to hydrotreating reactions. These reactions involve the reaction of chemical compounds with hydrogen gas in the presence of a catalyst to remove heteroatoms or to convert specific functional groups. The dataset contains reactions both with and without reaction conditions. Reaction conditions refer to the specific parameters under which the reaction takes place, such as temperature and pressure. For each reaction, the dataset includes both SMILES and SELFIES representations. SMILES (Simplified Molecular Input Line Entry System) and SELFIES (SELF-referencIng Embedded Strings) are two popular notations used to represent chemical structures in a compact and standardized format. The dataset was created with the aim of training a predictive model, specifically using the Molecular Transformer architecture.

bioprocessing, hydrotreating, deep learning algori↗
DOE OSTI2021

How Gaps in Time-Series Data Affect Asteroseismic Interpretation

Most pulsating white dwarf stars pulsate with many periods, each of which is a probe of their interior, which has made asteroseismolgy of these stars an active field. However, disentangling the multiple periodicities requires long, uninterrupted strings of data. We briefly describe the history of multi-site observing campaigns that culminated in the development of the Whole Earth Telescope in the late 1980s that still functions today. Through examples from the May 1990 campaign on GD 358, we show how critical it is to eliminate periodic gaps in data to greatly reduce aliasing in Fourier Transforms normally used to analyze the frequency content of pulsating white dwarfs. We close with a brief description of space satellite-based data, along with the advantages and disadvantages of these data compared to ground-based data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Solar-Tracker Diffuse-Response Algorithm for Balancing Energy Gain and Mechanical Wear in Photovoltaic Systems

Single-axis solar tracking maximizes photovoltaic energy production under clear-sky conditions; however, its effectiveness decreases under cloudy and overcast skies, where diffuse irradiance dominates and the optimal module orientation changes. Conventional tracking algorithms either neglect sky conditions or rely on simplified diffuse-response strategies that may trigger frequent tracker repositioning under variable cloud cover, leading to increased mechanical wear with marginal energy gains. This work proposes an enhanced diffuse-response tracking algorithm that explicitly accounts for both the intensity and temporal persistence of cloudiness. By requiring overcast conditions to persist for a minimum duration before reorienting the tracker to a diffuse-stow position, the proposed approach reduces unnecessary movements while preserving the benefits of diffuse-response operation. The algorithm is evaluated through numerical simulations based on historical meteorological data and validated using field measurements on monofacial and bifacial photovoltaic strings. The results show that the proposed strategy reduces excess tracker movement from 114% to 0.16% while maintaining nearly the same energy yield. Compared to a conventional diffuse-response algorithm, the associated energy reduction is minimal (≈0.17%) relative to the ≈0.37% yield gain observed at the studied location. These findings demonstrate that incorporating cloudiness duration enables a practical compromise between energy performance and tracker durability, particularly for monofacial photovoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Optimizing Deep Geothermal Drilling for Energy Sustainability in the Appalachian Basin

This study investigates the geological and geomechanical characteristics of the MIP 1S geothermal well in the Appalachian Basin to optimize drilling and address the wellbore stability issues encountered. Data from well logs, sidewall core analysis, and injection tests were used to derive elastic and rock strength properties, as well as stress and pore pressure profiles. A robust 1D-geomechanical model was developed and validated, correlating strongly with wellbore instability observations. This revealed significant wellbore breakout, widening the diameter from 12 ¼ inches to over 16 inches. Advanced technologies like Cerebro Force™ In-Bit Sensing were used to monitor drilling performance with high accuracy. This technology tracks critical metrics such as bit acceleration, vibration in the x, y, and z directions, Gyro RPM, stick-slip indicators, and bending on the bit. Cerebro Force™ readings identified hole drag caused by poor hole conditions, including friction between the drill string and wellbore walls and the presence of cuttings or debris. This led to higher torque and weight on bit (WOB) readings at the surface compared to downhole measurements, affecting drilling efficiency and wellbore stability. Optimal drilling parameters for future deep geothermal wells were determined based on these findings.

Environmental Sciences & Ecology↗
DOE OSTI2022

Prospects for Heavy Neutral SUSY HIGGS Scalars in the hMSSM and Natural SUSY at LHC Upgrades

We examine production and decay of heavy neutral SUSY Higgs bosons pp→H,A→ττ¯ within the hMSSM and compare against a perhaps more plausible natural supersymmetry scenario dubbed mh125(nat) which allows for a natural explanation for mweak≃mW,Z,h∼100 GeV while maintaining mh≃125 GeV. We evaluate signal against various Standard Model backgrounds from γ,Z→ττ¯, tt¯ and vector boson pair production VV. We combine the transverse mass method for back-to-back (BtB) taus along with the ditau mass peak mττ method for acollinear taus as our signal channels. This technique ultimately gives a boost to the signal significance over the standard technique of using just the BtB signal channel. We evaluate both the 95% CL exclusion and 5σ discovery reach in the mA vs. tanβ plane for present LHC with 139 fb−1, Run 3 with 300 fb−1 and high luminosity LHC (HL-LHC) with 3000 fb−1 of integrated luminosity. For tanβ=10, the exclusion limits range up to mA∼1, 1.1 and 1.4 TeV, respectively. These may be compared to the range of mA values gleaned from a statistical analysis of the string landscape wherein mA can range up to ∼8 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗