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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Heterogeneous techniques for rescaling energy deposits in the CMS Phase-2 endcap calorimeter

We present the porting to heterogeneous architectures of the algorithm used for applying linear transformations of raw energy deposits in the CMS High Granularity Calorimeter (HGCAL). This is the first heterogeneous algorithm to be fully integrated with HGCAL’s reconstruction chain. After introducing the latter and giving a brief description of the structural components of HGCAL relevant for this work, the role of the linear transformations in the calibration is reviewed. The many ways in which parallelization is achieved are described, and the successful validation of the heterogeneous algorithm is covered. Detailed performance measurements are presented, including throughput and execution time for both CPU and GPU algorithms, therefore establishing the corresponding speedup. We finally discuss the interplay between this work and the porting of other algorithms in the existing reconstruction chain, as well as integrating algorithms previously ported but not yet integrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Underground Hydrogen Storage: Transforming Subsurface Science into Sustainable Energy Solutions

As the global economy moves toward net-zero carbon emissions, large-scale energy storage becomes essential to tackle the seasonal nature of renewable sources. Underground hydrogen storage (UHS) offers a feasible solution by allowing surplus renewable energy to be transformed into hydrogen and stored in deep geological formations such as aquifers, salt caverns, or depleted reservoirs, making it available for use on demand. This study thoroughly evaluates UHS concepts, procedures, and challenges. This paper analyzes the most recent breakthroughs in UHS technology and identifies special conditions needed for its successful application, including site selection guidelines, technical and geological factors, and the significance of storage characteristics. The integrity of wells and caprock, which is important for safe and efficient storage, can be affected by the operating dynamics of the hydrogen cycle, notably the fluctuations in pressure and stress within storage formations. To evaluate its potential for broader adoption, we also examined economic elements such as cost-effectiveness and the technical practicality of large-scale storage. We also reviewed current UHS efforts and identified key knowledge gaps, primarily in the areas of hydrogen–rock interactions, geochemistry, gas migration control, microbial activities, and geomechanical stability. Resolving these technological challenges, regulatory frameworks, and environmental sustainability are essential to UHS’s long-term and extensive integration into the energy industry. This article provides a roadmap for UHS research and development, emphasizing the need for further research to fully realize the technology’s promise as a pillar of the hydrogen economy.

25 ENERGY STORAGE↗
DOE OSTI2021

Manifestly causal in-in perturbation theory about the interacting vacuum

In-In perturbation theory is a vital tool for cosmology and nonequilibrium physics. Here, we reconcile an apparent conflict between two of its important aspects with particular relevance to De Sitter/inflationary contexts: (i) the need to slightly deform unitary time evolution with an iϵ prescription that projects the free (“Bunch-Davies”) vacuum onto the interacting vacuum and renders vertex integrals well-defined, and (ii) Weinberg’s “nested commutator” reformulation of in-in perturbation theory which makes manifest the constraints of causality within expectation values of local operators, assuming exact unitarity. We show that a modified iϵ prescription maintains the exact unitarity on which the derivation of (ii) rests, while nontrivially agreeing with (i) to all orders of perturbation theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Measurement of nuclear effects on ψ(2S) production in p-Pb collisions at $ \sqrt{s_{\mathrm{NN}}}$ = 8.16 TeV

Inclusive ψ (2S) production is measured in p-Pb collisions at the centre-of-mass energy per nucleon-nucleon pair \( \sqrt{s_{\mathrm{NN}}} \) = 8.16 TeV, using the ALICE detector at the CERN LHC. The production of ψ (2S) is studied at forward (203 < y cms < 3 . 53) and backward (-4.46 < y cms < -2.96) centre-of-mass rapidity and for transverse momentum p T < 12 GeV/ c via the decay to muon pairs. In this paper, we report the integrated as well as the y cms - and p T -differential inclusive production cross sections. Nuclear effects on ψ (2S) production are studied via the determination of the nuclear modification factor that shows a strong suppression at both forward and backward centre-of-mass rapidities. Comparisons with corresponding results for inclusive J/ ψ show a similar suppression for the two states at forward rapidity (p-going direction), but a stronger suppression for ψ (2S) at backward rapidity (Pb-going direction). As a function of p T , no clear dependence of the nuclear modification factor is found. The relative size of nuclear effects on ψ (2S) production compared to J/ ψ is also studied via the double ratio of production cross sections [ σ ψ (2S) /σ J /ψ ]pPb/[ σ ψ (2S) /σ J /ψ ] pp between p-Pb and pp collisions. The results are compared with theoretical models that include various effects related to the initial and final state of the collision system and also with previous measurements at \( \sqrt{s_{\mathrm{NN}}} \) = 5.02 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Progress in the development and understanding of a high poloidal-beta tokamak operating scenario for an attractive fusion pilot plant

Abstract The high poloidal-beta ( $$\beta _{\textrm{P}}$$ β P ) regime was first proposed as a high bootstrap current scenario for a steady-state fusion pilot plant (FPP) in the 1990s (Kikuchi in Nucl Fusion 30:265, 1990). Since then, there have been many theoretical, modeling, and experimental research activities on this topic. A joint DIII-D/EAST research team began exploring the high- $$\beta _{\textrm{P}}$$ β P regime in 2013, focusing on addressing the needs of attractive FPP design by taking advantage of the extensive diagnostic set and sophisticated plasma control system on DIII-D and the well-developed integrated modeling capability at General Atomics. The ultimate goal is to demonstrate such a scenario on EAST with truly long pulse and metal wall compatibility. This paper summarizes the highlights of the research results on DIII-D by the joint team in the past decade. Experimental evidence and modeling analysis show the high- $$\beta _{\textrm{P}}$$ β P scenario has great advantages in addressing key needs for an attractive FPP design, such as high-energy confinement quality at low rotation, excellent core-edge integration, high line-averaged density above the Greenwald limit, low disruption risk, and high bootstrap current fraction for steady-state operation. This provides a relatively safe and economical option to base an FPP design on that will lead to commercial fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Instabilities and phase transitions in architected metamaterials: a gradient-enhanced continuum approach

Architected metamaterials such as foams and lattices exhibit a wide range of properties governed by microstructural instabilities and emerging phase transitions. Their macroscopic response–including energy dissipation during impact, large recoverable deformations, morphing between configurations, and auxetic behavior–remains difficult to capture with conventional continuum models, which often rely on discrete approaches that limit scalability. In this work, we propose a nonlocal continuum formulation that captures both stable and unstable responses of elastic architected metamaterials. The framework extends anisotropic hyperelasticity by introducing nonlocal variables and internal length scales reflective of microstructural features. Local polyconvex free-energy models are systematically augmented with two families of non-(poly)convex energies, enabling both metastable and bistable responses. Implementation in a finite element framework enables solution using a hybrid monolithic–staggered strategy. Simulations capture densification fronts, forward and reverse transitions, hysteresis loops, imperfection sensitivity, and globally coordinated auxetic modes. Overall, this framework provides a robust foundation for accelerated modeling of instability-driven phenomena in architected metamaterials, while enabling extensions to anisotropic, dissipative, and active systems as well as integration with data-driven and machine learning approaches.

42 ENGINEERING↗
DOE OSTI2023

Enabling site-specific well leakage risk estimation during geologic carbon sequestration using a modular deep-learning-based wellbore leakage model

Geologic carbon sequestration (GCS) is a promising technology for mitigating net carbon emissions and growing climate concern by storing CO 2 in reservoirs. Oil and gas brownfields are an attractive option for CO 2 storage, but these sites have many historical wellbores from petroleum production and can be a potential leakage pathway for CO 2 or formation brine. Therefore, risk management of GCS operations requires an assessment of potential well leakage. Due to the high uncertainty of the system, stochastic approaches are ideal for quantifying the range of risk behaviors, but they must be computationally efficient in the face of complex physics. Here, we develop a new physics-centric deep learning wellbore model to predict the leakage of CO 2 and brine through leaky wellbores. Multi-physics numerical simulations were used to generate data sets, and physics-informed features were introduced. Neural networks were optimized with an automated searching algorithm. Feature analysis quantifies the impact of each feature on model prediction and confirms the role of physics-inspired parameters. The model shows high predictive performance across a wide range of geologic and injection conditions and well attributes. In conclusion, a case study illustrates how the model is applied to assess well leakage in GCS operations.

58 GEOSCIENCES↗
DOE OSTI2026

Upcycling Polycrystalline LiNi1/3Mn1/3Co1/3O2 to High-Performance Large-Grained LiNi0.6Mn0.2Co0.2O2 via Simplified Polyol-Mediated Recycling

The escalating demand for lithium-ion batteries (LIBs) necessitates advanced recycling strategies that can address both resource scarcity and environmental impact. While conventional hydrometallurgy shows promise, it is challenged by complexity, impurity management, and environmental footprint. Here, we report a strategic polyol-metallurgy recycling process that efficiently transforms spent polycrystalline LiNi1/3Mn1/3Co1/3O2 (NMC111) into high-performance large-grained LiNi0.6Mn0.2Co0.2O2 (NMC622), offering dual benefits of compositional upcycling and morphology upgradation. Our approach leverages a polyol system with meticulous control over nickel salt addition and the precipitation process. This yields upcycled cathode materials possessing excellent structural integrity, well-defined large-grained particles (5-10?..mu..m), and robust electrochemical performance, including a specific capacity of ~182 mAh g-1 at C/10 and 88.0% capacity retention after 100 cycles. This facile and multifunctional process provides an environmental-friendly pathway for advanced cathode recycling, significantly contributing to a circular economy for LIBs through precise control over critical material attributes.

25 ENERGY STORAGE↗
DOE OSTI2021

Characterizing mineralization on low carbon steel exposed to aerated and degassed synthetic hydraulic fracture fluids

This study investigates the mineralization occurring at the interface between injected hydraulic fracturing fluids and steel production casing during the shut-in period of unconventional shale wells. Mild steel coupons were reacted with synthetic hydraulic fracturing fluids with varying base fluid and dissolved gas concentrations. Experiments were carried out in an autoclave system set at 50 °C and 2000 PSI for 2 and 14 days. Physical and mineralogical changes to the steel coupons’ surface were characterized using an FEI Quanta 600 field emission gun (FEG) scanning electron microscope (SEM) and a PANalytical XPert Pro diffractometer. Barite precipitation occurred ubiquitously during the first 48 hours in all experimental scenarios. Sulfate radicals created from degradation and reduction of ammonium persulfate breakers facilitate barite formation. Concomitant barite and corrosion related precipitates on the sample surfaces suggest iron hydroxy salts act as nucleation sites for mineral scale growth. These results suggest hydraulic fracturing fluids may have deleterious effects on the wellbore before production of the well begins.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian Entropy Neural Networks for physics-aware prediction

This article addresses the need for deep learning models to integrate well-defined constraints into their outputs, driven by their application in surrogate models, learning with limited data and partial information, and scenarios requiring flexible model behavior to incorporate non-data sample information. We introduce Bayesian Entropy Neural Networks (BENN), a framework grounded in Maximum Entropy (MaxEnt) principles, designed to impose constraints on Bayesian Neural Network (BNN) predictions. BENN is capable of constraining not only the predicted values but also their derivatives and variances, ensuring a more robust and reliable model output. To achieve simultaneous uncertainty quantification and constraint satisfaction, we employ the method of multipliers approach. This allows for the concurrent estimation of neural network parameters and the Lagrangian multipliers associated with the constraints. Our experiments, spanning diverse applications such as beam deflection modeling and microstructure generation, demonstrate the effectiveness of BENN. The results highlight significant improvements over traditional BNNs and showcase competitive performance relative to contemporary constrained deep learning methods.

14 SOLAR ENERGY↗
DOE OSTI2021

QuantImPy: Minkowski functionals and functions with Python

The Minkowski functionals and functions are a family of morphological measures and can be used to describe both the morphology (shape) and topology (connectedness) of a system. This paper presents the QuantImPy Python package which can compute both the Minkowski functionals and functions. In addition, this package can efficiently perform basic morphological operations and compute their distance maps. QuantImPy is easy to install, well documented, integrated with existing Python packages, and open source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Local Pair Natural Orbital-Based Coupled-Cluster Theory through Full Quadruples (DLPNO–CCSDTQ)

In this work, we implement a local pair natural orbitalbased coupled-cluster method through the full treatment of quadruple excitations (CCSDTQ). The domain-based local pair natural orbital (DLPNO) approach, which has successfully been applied to lower levels of coupled-cluster theory, is utilized in our algorithm, and thus our algorithm is called DLPNO-CCSDTQ. For simplicity in the working equations and in the implementation, we t 1 -dress the twoelectron integrals as well as Fock matrix elements. Our method can recover CCSDTQ-CCSDT and CCSDTQ-CCSDT(Q) energy differences on the order of 0.01−0.05 kcal mol −1 , even at a loose quadruples natural orbital (QNO) occupation number cutoff of 3.33 × 10 −6 . To highlight the capabilities of our code and its potential future applications, we showcase computations that would be intractable with canonical CCSDTQ, such as the benzene dimer, (H 2 O) 17 , and adamantane. With sufficient computing resources, computations up to 15 heavy atoms (40 atoms overall) may be feasible for fully bonded 3D systems.

Cluster chemistry↗
DOE OSTI2024

Johnson-noise-limited cancellation-free microwave impedance microscopy with monolithic silicon cantilever probes

Abstract Microwave impedance microscopy (MIM) is an emerging scanning probe technique for nanoscale complex permittivity mapping and has made significant impacts in diverse fields. To date, the most significant hurdles that limit its widespread use are the requirements of specialized microwave probes and high-precision cancellation circuits. Here, we show that forgoing both elements not only is feasible but also enhances performance. Using monolithic silicon cantilever probes and a cancellation-free architecture, we demonstrate Johnson-noise-limited, drift-free MIM operation with 15 nm spatial resolution, minimal topography crosstalk, and an unprecedented sensitivity of 0.26 zF/ √ Hz. We accomplish this by taking advantage of the high mechanical resonant frequency and spatial resolution of silicon probes, the inherent common-mode phase noise rejection of self-referenced homodyne detection, and the exceptional stability of the streamlined architecture. Our approach makes MIM drastically more accessible and paves the way for advanced operation modes as well as integration with complementary techniques.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Transient behavior of oxide fuels with controlled microstructure and Cr2O3 additive

Abstract Microstructure and Cr 2 O 3 doping profoundly impact the thermal-mechanical properties and fracture of oxides fuels. It is a challenge to study the transient behavior of nuclear fuels under loss-of-coolant-event (LOCA). In this study, the crack behavior of UO 2 pellets with controlled grain structure and Cr 2 O 3 doping was tested with rapid power ramping (300−900 °C per min) mimicking a prototypical LOCA heating profile. Dense micron-sized UO 2 pellets display well-maintained integrity without cracking with the ramping up to 1500 °C at a heating rate of 8 °C per second. Fracture occurs in both pure and Cr 2 O 3 -doped dense nano-sized UO 2 pellets. The Cr 2 O 3 doped oxide fuel pellet with a larger grain size (~ 22.2 μm) displays the best performance under LOCA testing due to its highest thermal conductivity under high temperature. FEA calculations suggest a temperature gradient across the fuel pellet during transient testing, resulting in residual stress and cracking, which can be correlated with their thermal-mechanical properties.

Zhao, Dong (ORCID:0000000191377257)↗
DOE OSTI2026

The Need for a New LLNL Pulsed Sphere Neutron Leakage Spectra Series

Here, it is shown that spectra measured as part of the Lawrence Livermore National Laboratory Pulsed Sphere (LPS) program offer decisive information to locate formatting or physics issues in nuclear data of key interest for fusion reactor simulations. However, experiments from this measurement series are not benchmarks. For instance, their uncertainties are incomplete. There are also many open questions—e.g., on the setup, the detector response, and whether LPS are accurately modeled—that cannot be answered anymore given the limited documentation and that many of the experimenters are no longer actively working. This limited knowledge has implications when one tries to adjust nuclear data to LPS spectra. Usually, one adjusts to benchmarks representing an application with the hope to get more precise nuclear data for the application of interest where differential data might be scarce and/or to reduce nuclear data uncertainties in the application simulations. However, it is demonstrated that adjustment with LPS spectra without accounting for missing uncertainties and modeling potential biases in the experimental data leads to adjusted data that are highly unphysical. That means adjusted data differ significantly from evaluated data based on information from differential experiments; also, application quantities predicted with the adjusted data deviate distinctly from experimental ones. While we can approximate our limited knowledge on these experiments with Gaussian processes in the adjustment process, this modeling of bias is arbitrary rather than based on a physics explanation, calling into doubt the validity of resulting adjusted data. Thus, we discuss here the need for a new measurement series, learning from the strengths and weaknesses of the LPS program, to yield decisive and well-benchmarked integral experiments to support fusion reactor research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Development of a FELIX based readout system for ITk strip hybrid module demonstrator for ATLAS Phase-II Upgrade

The Large Hadron Collider (LHC) will undergo a major upgrade around 2024 with a roughly tenfold increase in luminosity. It results in corresponding increases in particle rates and radiation doses that the current ATLAS Inner Tracking Detector cannot cope with. Therefore the ATLAS experiment will build a new all-silicon tracking system called the ITk (Inner Tracker) that includes an inside pixel detector close to the beam line and a strip detector in outside layer. Meanwhile the ATLAS experiment will adopt the Front-End Link eXchange (FELIX) system as the interface between the data acquisition and front-end electronics for all sub-detectors in the Phase II Upgrade. In this contribution, we present a prototype of FELIX based readout system for the strip hybrid module. Its hardware, firmware and software GUI application will be discussed, as well as integration test results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures

We present our recent development of an integrated mesoscale digital twin (DT) framework for relating processing conditions, microstructures, and mechanical responses of additively manufactured (AM) metals. In particular, focusing on the laser powder bed fusion technique, we describe how individual modeling and simulation capabilities are coupled to investigate and control AM microstructural features at multiple length and time scales. We review our prior case studies that demonstrate the integrated modeling schemes, in which high-fidelity melt pool dynamics simulations provide accurate local thermal profiles and histories to subsequent AM microstructure simulations. We also report our new mechanical response modeling results for predicted AM microstructures. In addition, we illustrate how our DT framework has been validated through modeling–experiment integration, as well as how it has been practically utilized to guide and analyze AM experiments. Finally, we share our perspectives on future directions of further development of the DT framework for more efficient, accurate predictions and wider ranges of applications.

36 MATERIALS SCIENCE↗