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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Rational designs to enable 10-min fast charging and long cycle life in lithium-ion batteries

A daunting challenge in the design of lithium ion batteries (LiBs) is enabling 10-min extreme fast charging (XFC) while achieving appreciable charge acceptance and cycle life. This desirable outcome requires both a comprehensive understanding of LiB operation and aging behavior at different length scales and careful optimization. Lithium plating has been a critical bottleneck because, at XFC rates, it consumes cyclable lithium causing distinct aging and safety concerns even in moderate-loading LiBs. Here, we propose combining multiple solutions, including materials-to-electrode design-to-charging protocols, that are intended to overcome limitations in lithium-ion transport in the electrolyte phase, thus enabling 10-min XFC in LiBs. Some implemented strategies include cathode chemistry, optimized carbon binder domain in the cathode, dual layer anode design, improved separator and advanced electrolyte. Further, innovative charging protocols in moderately loading (~3 mAh/cm 2 anode/2.7 mAh/cm 2 cathode) single-layer pouch cells are proposed, together with demonstrated 10-min XFC with higher charge acceptance between 87.3 and 92.1% (or 2–2.1 mAh/cm 2 ) for 600 cycles without lithium plating. This methodical study with well-defined cells shows promise in combining multiple solution strategies to enable 10-min XFC, charting a pathway to achieve XFC in higher-loading energy-optimized LiBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Nuclear Data Sheets for A=267,271,275,279,283,287,291,295,299

Information on the production, identification, half-lives and decay modes for experimentally known nuclides with mass numbers of 267, 271, 275, 279, 283, 287, and 291, along with attempts to observe nuclides with mass numbers of 295 and 299, are presented along with the recommended values. Data here supersede data from the previous evaluation in this region, 2005Gu33. Since the previous evaluation many new and conclusive experiments have explored the region of superheavy nuclei, thus significantly expanding our knowledge of the nuclear chart in this area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Nuclear Data Sheets for A=269,273,277,281,285,289, and 293

Herein, information on the production, identification, half-lives and decay modes for experimentally known nuclides with mass numbers of 269, 273, 277, 281, 285, 289, and 293 are presented along with the recommended values. Data here supersede data from the previous evaluation in this region, 2005Gu33. Since the previous evaluation many new and conclusive experiments have explored the region of superheavy nuclei, thus significantly expanding our knowledge of the nuclear chart in this area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Systematic trends of 0 2 + , 1 1 - , 3 1 - and 2 1 + excited states in even-even nuclei

Here, the spin and parity ( J π ) assignments in even-even nuclei were reviewed across the nuclear chart using the Evaluated Nuclear Structure Data File (ENSDF). The prevalence of 2$+\atop{1}$ first or lowest excited states is confirmed. The properties of 0$+\atop{2}$, 1$-\atop{1}$, and 3$-\atop{1}$ lowest excited states were reexamined using the ENSDF data evaluation procedures. The J π systematic trends and correlations between level quantum numbers and nuclear physics phenomena are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Towards next-generation optical potentials for nuclear reactions and structure calculations

Optical-model potentials (OMPs) are critical ingredients for basic and applied nuclear physics. Present-day computational capabilities allow us to generate data-driven nucleon-nucleus OMPs that are non-local and exactly dispersive (as theoretically required to be), include statistically-sound uncertainty quantification, and are trained on both scattering and bound-state data from a wide area of the nuclear chart. Combined together, these features allow for significant improvement in fidelity and extrapolative power of the model. Here, we present preliminary work toward the development and training of such an OMP. The capability of the model to describe data at this first stage is encouraging.

Perrotta, Salvatore Simone [Lawrence Livermore Nat↗
DOE OSTI2024

Mixed polyester recycling can enable a circular plastic economy with environmental benefits

The mixed and varied nature of fossil-based and bio-based plastic waste requires complex and costly separations to enable compatibility with recycling technologies. A circular plastic economy based on mixed polyesters through cleaving ester bonds to produce monomers, while re-utilizing bio-based monomers to produce high-quality sustainable plastics, charts an exciting solution. However, the feasibility of such a circular economy solution remains underexplored. Here, in this study, we conducted a techno-economic analysis and life-cycle assessment of three polyester depolymerization recycling processes-methanolysis, glycolysis, and acid hydrolysis-for a mixed feedstock (polyethylene terephthalate [PET], polylactic acid [PLA], and polybutylene adipate terephthalate [PBAT]). Methanolysis outperforms glycolysis and hydrolysis economically and environmentally due to more efficient downstream separations, generating products with a 31% decrease in selling price and 21%-46% reduction in acidification, carcinogenic toxicity, fossil-fuel depletion, global warming potential, particulate formation, and smog formation compared to conventional polyester manufacturing. This study highlights the viability of a circular plastic economy for mixed polyesters via a single chemical recycling process.

09 BIOMASS FUELS↗
DOE OSTI2022

Emergence of an island of extreme nuclear isomerism at high excitation near 208 Pb

Metastable states with $T_{1/2}$ = 8(2) ms in 205Bi and $T_{1/2}$ = 0.22(2) ms in 204 Pb, with ≈ 8 MeV excitation energy and angular momentum ≥ 22 $\hbar$, have been established. These represent, by up to two orders of magnitude, the longest-lived nuclear states above an excitation energy of 7 MeV, ever identified in the nuclear chart. Additionally, the half-life of the 10.17 MeV state in 206 Bi has been determined to be 0.027(2) ms, the next highest value in this highly excited regime. These observations indicate the emergence of an island of extreme nuclear isomerism arising from core-excited configurations at high excitation in the vicinity of the doubly closed-shell nucleus 208 Pb. These results are expected to provide discriminating tests of the effective interactions used in current large-scale shell-model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Controlling extrapolations of nuclear properties with feature selection

Predictions of nuclear properties far from measured data are inherently inaccurate because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model bias can be directly calculated when experimental data is available, only an estimate can be made in the absence of such measurements. Current approaches to compute the estimated bias quickly lose predictive power when their input variables are taken far from the training region, resulting in uncontrolled uncertainties in applications such as nucleosynthesis simulations. In this letter, we present a novel technique to identify the input variables of machine learning algorithms that can provide robust estimates of model bias. Our process is based on selecting input variables, or features, based on their probability distribution functions across the entire nuclear chart. We illustrate our approach on the problem of quantifying the model bias in nuclear binding energies calculated with Density Functional Theory (DFT). We prove that building model biases with only Z and N as features leads to highly unreliable extrapolations. Conversely, we show that proper feature selection can systematically improve theoretical predictions without increasing uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Electroweak nuclear radii constrain the isospin breaking correction to V ud

We lay out a novel formalism to connect the isospin-symmetry breaking correction to the rates of superallowed nuclear beta decays, δ C , to the isospin-breaking sensitive combinations of electroweak nuclear radii that can be accessed experimentally. We individuate transitions in the superallowed decay chart where a measurement of the neutron skin of a stable daughter even at a moderate precision could already help discriminating between models used to compute δ C . We review the existing experimental situation and make connection to the existing and future experimental programs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Atomic masses with machine learning for the astrophysical r process

The astrophysical r process plays a vital role in the production of heavy elements. Modeling of the r process is sensitive to masses and further requires knowledge of masses beyond current experimental reach. Therefore, simulations of the r process offer a unique test bed for predicting mass extrapolations. We take a Machine-Learning (ML) approach to model the masses across the entire chart of nuclides. For the first time, we simulate r-process nucleosynthesis with a physics-based ML mass model. We compare simulated abundances to solar data in order to evaluate the model's performance far from stability. The resulting r-process abundances up to thorium and uranium qualitatively match those of the observed solar system abundance pattern, with the characteristic peaks well positioned. We propagate the mass uncertainties obtained from the ML model to r-process abundance yields to estimate an uncertainty band associated with our approach. The size of the uncertainty band is approximately one order of magnitude which aligns with the uncertainty reported using alternative techniques.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

SMEFT ATLAS: The landscape beyond the Standard Model

The Standard Model Effective Field Theory (SMEFT) based on the unbroken gauge group SU(3) 𝐶 ⊗SU(2) 𝐿 ⊗U(1) 𝑌 and containing only particles of the Standard Model (SM) has developed in the last decade to a mature field. It is the framework to be used in the energy gap from scales sufficiently higher than the electroweak scale up to the lowest energy scale at which new particles show up. We summarize the present status of this theory with a particular emphasize on its role in the indirect search for new physics (NP). While flavour physics of both quarks and leptons is the main topic of our review, we also discuss electric dipole moments, anomalous magnetic moments (𝑔−2) 𝜇,𝑒 , 𝑍-pole observables, Higgs observables and high-𝑝𝑇 scattering processes within the SMEFT. We group the observables into ten classes and list for each class the most relevant operators and the corresponding renormalization group equations (RGEs). We exhibit the correlations between different classes implied both by the operator mixing and the SU(2) 𝐿 gauge symmetry. Our main goal is to provide an insight into the complicated operator structure of this framework which hopefully will facilitate the identification of valid ultraviolet completions behind possible anomalies observed in future data. Numerous colourful charts, and 85 tables, while representing rather complicated RG evolution from the NP scale down to the electroweak scale, beautify the involved SMEFT landscape. Over 1000 references to the literature underline the importance and the popularity of this field. We discuss both top-down and bottom-up approaches as well as their interplay. This allows us eventually to present an atlas of different landscapes beyond the SM that includes heavy gauge bosons and scalars, vector-like quarks and leptons and leptoquarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Beyond-mean-field approaches for nuclear neutrinoless double beta decay in the standard mechanism

Nuclear weak decays provide important probes to fundamental symmetries in nature. A precise description of these processes in atomic nuclei requires comprehensive knowledge on both the strong and weak interactions in the nuclear medium and on the dynamics of quantum many-body systems. In particular, an observation of the hypothetical double beta decay without emission of neutrinos (0νββ) would unambiguously demonstrate the Majorana nature of neutrinos and the existence of the lepton-number-violation process. It would also provide unique information on the ordering and absolute scale of neutrino masses. The next-generation tonne-scale experiments with sensitivity up to 10 28 years after a few years of running will probably provide a definite answer to these fundamental questions based on our current knowledge on the nuclear matrix element (NME), the precise determination of which is a challenge to nuclear theory. Beyond-mean-field approaches have been frequently adapted for the study of nuclear structure and decay throughout the nuclear chart for several decades. In this review, we summarize the status of beyond-mean-field calculations of the NMEs of 0νββ decay assuming the standard mechanism of an exchange of light Majorana neutrinos. In conclusion, the challenges and prospects in the extension and application of beyond-mean-field approaches for 0νββ decay are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Laser spectroscopy for the study of exotic nuclei

Investigation into the properties and structure of unstable nuclei far from stability is a key avenue of research in modern nuclear physics. These efforts are motivated by the continual observation of unexpected structure phenomena in nuclei with unusual proton-to-neutron ratios. In recent decades, laser spectroscopy techniques have made significant contributions in our understanding of exotic nuclei in different mass regions encompassing almost the entire nuclear chart. This is achieved through determining multiple fundamental properties of nuclear ground and isomeric states, such as nuclear spins, magnetic dipole and electric quadrupole moments and charge radii, via the measurement of hyperfine structures and isotope shifts in the atomic or ionic spectra of the nuclei of interest. These properties offer prominent tests of recently developed state-of-the-art nuclear theory and help to stimulate new developments in improving the many-body methods and nucleon–nucleon interactions at the core of these models. With the aim of exploring more exotic short-lived nuclei located ever closer to the proton and neutron driplines, laser spectroscopy techniques, with their continuous technological developments towards higher resolution and higher sensitivity, are extensively employed at current- and next-generation radioactive ion beam facilities worldwide. Ongoing efforts in parallel promise to improve the availability of these even more exotic species at next-generation facilities. Very recently, an innovative application of laser spectroscopy on molecules containing short-lived nuclei has been demonstrated offering additional opportunities for several fields of research, e.g. fundamental symmetry studies and astrophysics. Here, in this review, the basic nuclear properties measurable with laser spectroscopy will be introduced. How these observables are associated with nuclear structure and nucleon–nucleon interactions will be discussed. Following this, a general overview of different laser spectroscopy methods will be given with particular emphasis on technical advancements reported in recent years. The main focus of this article is to review the numerous highlights that have resulted from studying exotic nuclei in different mass regions with laser spectroscopy techniques since the last edition in this series. Finally, the challenges facing the field in addition to future opportunities will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Band inversion-driven warping and high valley degeneracy

Band inversion is a physical phenomenon that can warp the band structure in topological insulators, generating multiple electronic valleys for conducting carriers. However, the conditions under which band inversion induces warping are not well understood. Here, we derive two general rules that must be satisfied for band warping to occur in centrosymmetric and non-magnetic topological insulators: (1) bands must be sufficiently inverted, and (2) secondary bands must have opposite parity and be close in energy to the band edges. We chart the valley degeneracies that can emerge from band inversion in each of the 11 centrosymmetric point groups, revealing that an increase in the valley degeneracy between 2- and 48-fold is possible from band inversion. The generalized rules offer a unique band engineering approach by capitalizing on the non-trivial electronic structures of topological insulators.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Correlated Ion Transport Governed by Dynamic Local Structure in High Concentration and Localized High Concentration Electrolytes

Understanding the dynamics of cluster formation and network percolation provides the mechanistic link between microscopic solvation structure and transport in concentrated electrolytes, including localized high-concentration electrolytes (LHCEs). Although recent studies have shown LHCEs to form micelle-like aggregates at specific compositions, a quantitative understanding of how solvation structures and transport properties depend on salt–solvent–diluent ratios remains limited. Here, we integrate molecular dynamics with Onsager transport analyses to chart the evolution of solvation microstructure and associated ionic transport in LiFSI/DMC/TTE, achieving good agreement with experimental conductivities across composition. We show that micelle formation arises from a dynamic instability of the cation–anion network, and that network percolation is the primary determinant of conductivity. Two compositional thresholds emerge: A critical network concentration (CNC) and a critical micelle concentration (CMC) that delineate transitions from extended percolating networks to micelle-like clusters and then to fragments. These structural transitions rationalize the nonintuitive conductivity decrease at intermediate dilution despite monotonically decreasing viscosity and provide composition-level design rules for LHCEs.

Mohanakrishnan, Rohith Srinivaas [University of Ca↗
DOE OSTI2025

Bound and Continuum Intersubband Transitions in Colloidal Quantum Wells

Quantum well intersubband transitions are critical for quantum cascade lasers and infrared photodetectors. Control of band offsets allows bound-to-bound intersubband transitions, with confinement of both initial and final states, and bound-to-continuum transitions, in which only the initial state is energetically confined within the potential well. Both types of transitions are also achieved in colloidal CdSe wells by changing the heterostructure shell. Bare wells have narrow intersubband transitions spanning the near-infrared spectrum following effective mass predictions. Atomically precise core/shells enable a readily adjusted potential well for electrons. For CdSe/ZnS, bound-to-bound transitions are narrow and redshift with shell thickness. By contrast, broad bound-to-continuum absorptions are found in CdSe/CdS. Due to small conduction band offsets, higher conduction band states of the well are more delocalized into the CdS shell. In conclusion, these measurements provide unique data to understand the electronic structure of colloidal quantum wells and chart a path to atomically precise optoelectronic materials for the mid-infrared.

colloidal atomic layer deposition↗
DOE OSTI2024

Elucidating Polymer Binder Entanglement in Freestanding Sulfide Solid-State Electrolyte Membranes

This study advances the development of flexible, sheet-type sulfide solid-state electrolytes (SSEs) for use in all-solid-state batteries, emphasizing the important and previously insufficiently investigated role of polymer binder entanglement. Here, the molecular weight of polymer binders is pivotal in crafting robust, freestanding SSE films. Our research uncovers a dual impact: higher molecular weight binders bolster the structural integrity of SSE films but elevate grain boundary resistance and diminish critical current density, whereas lower molecular weight poly(isobutylene) films, despite their more uniform distribution, lack the essential strain hardening or strength for sustained active material contact. Crucially, full cells employing higher molecular weight binders demonstrate improved discharge capacity retention, contrasting sharply with the notable capacity degradation in lower molecular weight cells. Our findings not only deepen the comprehension of binder influences in solid-state batteries but also chart a course for refining all-solid-state battery technologies, a key stride for the future of energy storage solutions.

25 ENERGY STORAGE↗
DOE OSTI2026

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗