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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Entrapment Behavior of Solid Surrogate Fission Products at Engineered UN Nano‐Hetero‐Interfaces Within Metallic Nuclear Fuels

Nanometric hetero-interfaces provide a wealth of scientific and engineering opportunities due to their complex and often misunderstood properties that can differ from their respective bulk constituents. In this work, the ability for engineered nanostructures within a bulk U─Mo alloy to arrest simulant fission products is investigated experimentally and computationally. Nanostructured 90 wt% U/ 10 wt% Mo (U-10Mo) with 7.1 at% Nd is consolidated using spark-plasma- sintering (SPS) techniques and is heat-treated at 500 °C under vacuum for 24, 100, 500, and 1000 h. Analysis on the sintered and heat-treated U-10Mo reveals rapid kinetics in Nd diffusion to nanocluster sites, with evidence of Nd diffusion occurring during sintering and during the following heat-treatment. The segregation behavior of Nd at two different U─Mo/UN interfaces is computationally verified using density functional theory (DFT) to reinforce experimental data.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Soft and Stretchable Thienopyrroledione–Based Polymers via Direct Arylation

π-conjugated polymers (CPs) that are concurrently soft and stretchable are needed for deformable electronics. Molecular-level modification of indacenodithiophene (IDT) copolymers, a class of CPs that exhibit high hole mobilities (μ hole ), is an approach that can help realize intrinsically soft and stretchable CPs. Numerous examples of design strategies to adjust the stretchability of CPs exist, but imparting softness is comparatively less studied. In this study, a systematic molecular weight (MW) series is constructed on a promising candidate for soft CPs, poly(indacenodithiophene-co-thienopyrroledione) (p(IDT C16- TPD C8 )), by optimizing direct arylation polymerization conditions in hopes of improving stretchability and μhole without significantly impacting softness. We found p(IDT C16- TPD C8 ) at a degree of polymerization of 32 shows high stretchability (crack onset strain, CoS > 100%) without significantly impacting softness (elastic modulus, E = 32 MPa), which to the best of our knowledge outperforms previously reported stretchable and soft CPs. To further study how molecular-level modifications impact polymer properties, a MW series of a new extended donor unit polymer, poly(indacenodithienothiophene-co-thienopyrroledione) (p(IDTT C16- TPD C8 )), was synthesized. The IDTT C16 copolymers did not result in a greater average μ hole when comparing between p(IDTT C16- TPD C8 ) and p(IDT C16- TPD C8 ) despite their higher crystallinity observed by GIWAXS. While these findings warrant further investigation, this study points toward unique charge transport properties of IDT-based polymers.

direct arylation polymerization↗
DOE OSTI2025

Interdisciplinary Approaches Improve Understanding of Cryptogenic Species: A Historical Case Study of Crayfish in Montana, USA

ABSTRACT Cryptogenic species are those that are not yet “demonstrably native or introduced” in a given area, such as crayfish in western Montana, USA. Delving into evidence from diverse fields can help clarify the status of cryptogenic species. Primary historical sources and indigenous knowledge have informed various ecological questions but are seldom used to clarify the status of cryptogenic species, especially aquatic taxa. We summarize types of evidence used to illuminate species status and offer a case study applying historical sources to cryptogenic crayfish in Montana. We searched for crayfish mentions in dictionaries of indigenous languages and primary historical documents (e.g., travel journals, newspaper accounts, early biological surveys). Early explorer accounts we examined did not mention crayfish in Montana, though they noted them in the nearby Snake River drainage of Idaho and Wyoming. The first mention of crayfish in Montana that we found was from an 1868 newspaper account, probably referencing the upper Missouri River. The species was not noted, but an 1887 article suggested signal crayfish Pacifastacus leniusculus introductions near Bozeman, where non‐native signal crayfish still persist. The earliest crayfish mention we found west of the Great Divide in Montana was from 1934 in Ninepipes and probably referred to non‐native virile crayfish ( Faxonius virilis ). Signal crayfish were not mentioned west of the Divide until a 1944 newspaper account noted their 1937 introduction to the Bitterroot River drainage. The case study demonstrates the value of historical sources in identifying the absence of species and documenting their presence or introduction during periods predating scientific data.

Kennedy, Hampton L. [USDA Forest Service, Southern↗
DOE OSTI2025

Universal scaling of electron transmission for nearly ballistic and quantum dragon nanodevices

Here, we predict two different universal scaling regimes for the quantum transmission of metallic nanodevices following the addition of a small amount of uncorrelated disorder. A nanodevice is connected to two thin semi-infinite uniform leads, and the Non-Equilibrium Green’s Function (NEGF) methodology yields the electron transmission $\mathscr{T}(E)$ as a function of the injected electron energy $E$. Ballistic nanodevices have no disorder and have $\mathscr{T}(E)=1$for all $E$ that allow electron propagation in the leads. Quantum dragon nanodevices can have extremely strong properly correlated disorder, and still have $\mathscr{T}(E)=1$for all $E$. Additional uncorrelated site disorder leads to Fano resonances in $\mathscr{T}(E)$. Averaging over the uncorrelated disorder we predict using perturbation theory two universal scaling regimes for $\mathscr{T}_{ave}(E)$. The functional form of both universal scaling regimes depend on the device length and width, energy, and variance of the uncorrelated disorder. The second scaling regime, valid for small but somewhat larger uncorrelated disorder than the first scaling regime, also has the form dependent on the density of states of the system. These two scaling regimes are demonstrated to be valid via large scale computer calculations.

Ballistic transport↗
DOE OSTI2026

Machine learning guided prediction of solute segregation at coherent and semi-coherent metal/oxide interfaces

Investigation of semi-coherent metal/oxide interfaces with misfit dislocations using density functional theory (DFT) is computationally intensive to the point of being prohibitive, as it involves several hundreds to many thousands of atoms. In this study, we examined the solute segregation behavior at the Fe/Y 2 O 3 interface—a model interface for cladding applications in nuclear fission reactors—using a combination of DFT calculations and machine learning (ML) approaches. Both coherent and semi-coherent interfaces were considered. ML models were trained on DFT-calculated segregation energies to identify the key chemical, geometric and strain energy related features that govern solute segregation behavior at coherent Fe/Y 2 O 3 interfaces. Furthermore, it was found that ML models when trained on DFT calculated segregation energy of elements at a coherent interface, comprising of about a hundred-atom supercell, can predict the segregation energy of elements at a semi-coherent Fe/Y 2 O 3 interface (with multiple hundreds of atoms) at a fraction of computational cost (1/35th), with an accuracy comparable to DFT calculations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Energy resolution and gain measurements in Argon-based gas mixtures: Exploring Ar:CF 4 for low energy measurements with TPCs

Time Projection Chambers (TPCs) are among the most advanced charged-particle detectors. Gas-filled TPCs have tracking capabilities that provide 3D-imaging of charged particles with a good energy resolution for spectroscopy. Different gas mixtures have different properties that determine the energy resolution as well as the spatial resolution. Therefore, optimization of operating conditions is required to simultaneously obtain adequate gain, energy resolution, spatial/track resolution, as well as higher drift velocities for high counting rates applications. Ar:CF 4 gas mixture has higher electron drift velocities and lower electron diffusion, which makes it an attractive candidate for TPC filling gas for low energy nuclear physics applications as compared to commonly used Ar:CH 4 and Ar:CO 2 gas mixtures, namely when tracking information is needed. However, other properties, including energy resolution and gain, remain largely unexplored in Ar:CF 4 especially at pressures and other operating conditions relevant for low-energy nuclear physics applications. Here, in this paper we report on gain and energy resolution measurements, using Gas Electron Multipliers (GEMs), in the less explored Ar:CF 4 mixture (Alfonsi et al., 2006), as well as in the more commonly used gas mixtures Ar:CH 4 and Ar:CO 2 . In addition to obtaining energy resolution and gain, we provide results from Garfield++ simulations for gain fluctuations, and their impact on energy resolution is discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Framework development for a SAVY-4000 nuclear material storage container structural integrity surveillance tool

Here, this work presents the preliminary design of an automated surveillance tool to assess the health of SAVY-4000 nuclear material storage containers. This tool is designed by training several machine learning (ML) regression models to predict maximum residual stress in plain dents on the container sidewall. The model is trained on an experimentally validated Finite Element Analysis (FEA) model built in Abaqus FEA. The accuracy of each ML model is compared. The potential for application as well as model shortcomings are assessed. Necessary FEA model improvements are outlined and the various ML models are proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Excited states in semi-magic 82 Ge populated in the βn-decay of 83 Ga

For this work, the βn and β-decay of the neutron-rich 83 Ga isotopes produced in proton-induced fission of 238 U were studied at the Holifield Radioactive Ion Beam Facility (HRIBF) at Oak Ridge National Laboratory using on-line mass separation and the hybrid-3Hen neutron-γ detector array. Excited states in semi-magic 82 Ge populated in βn decay of 83 Ga were identified using neutron-γ coincidences. The measured relative population of excited states in 82 Ge is compared with a βn emission model, where the neutron emission model combines the strength distribution obtained from the shell-model calculations with the statistical Hauser-Feshbach model.

3HEN↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Long-Range Resonant Charge Transport through Open-Shell Donor–Acceptor Macromolecules

A grand challenge in molecular electronics is the development of molecular materials that can facilitate efficient longrange charge transport. Research spanning more than two decades has been fueled by the prospects of creating a new generation of miniaturized electronic technologies based on molecules whose synthetic tunability offers tailored electronic properties and functions unattainable with conventional electronic materials. However, current design paradigms produce molecules that exhibit off-resonant transport under low bias, which limits the conductance of molecular materials to unsatisfactorily low levels several orders of magnitude below the conductance quantum 1 G 0 and often results in an exponential decay in conductance with length. Here, we demonstrate a chemically robust, air-stable, and highly tunable molecular wire platform comprised of open-shell donor−acceptor macromolecules that exhibit remarkably high conductance close to 1 G 0 over a length surpassing 20 nm under low bias, with no discernible decay with length. Single-molecule transport measurements and ab initio calculations show that the ultralong-range resonant transport arises from extended π-conjugation, a narrow bandgap, and diradical character, which synergistically enables excellent alignment of frontier molecular orbitals with the electrode Fermi energy. The implementation of this long-sought-after transport regime within molecular materials offers new opportunities for the integration of manifold properties within emerging nanoelectronic technologies.

36 MATERIALS SCIENCE↗