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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 757 records · Page 42

Experiments and Simulations on the Turbulent, Rarefaction Wave Driven Rayleigh–Taylor Instability

Experiments were performed to observe the growth of the turbulent, Rayleigh–Taylor unstable mixing layer generated between air and SF 6 , with an Atwood number of A=(ρ 2 –ρ 1 )/(ρ 2 +ρ 1 ) = 0.64, where ρ 1 and ρ 2 are the densities of air and SF 6 , respectively. A nonconstant acceleration with an average value of 2300g 0 , where g 0 is the acceleration due to gravity, was generated by interaction of the interface between the two gases with a rarefaction wave. Three-dimensional, multimode perturbations were generated on the diffuse interface, with a diffusion layer thickness of δ = 3.6 mm, using a membraneless vertical oscillation technique, and 20 experiments were performed to establish a statistical ensemble. The average perturbation from this ensemble was extracted and used as input for a numerical simulation using the Lawrence Livermore National Laboratory (LLNL) Miranda code. Good qualitative agreement between the experiment and simulation was observed, while quantitative agreement was best at early to intermediate times. Several methods were used to extract the turbulent growth constant α from experiments and simulations while accounting for time varying acceleration. Experimental, average bubble and spike asymptotic self-similar growth rate values range from α = 0.022 to α = 0.032 depending on the method used, and accounting for variable acceleration. Values found from the simulations range from α = 0.024 to α = 0.041. Here, the values of α measured in the experiments are lower than what are typically measured in the literature but are more in line with those found in recent simulations.

42 ENGINEERING↗

Progress on Understanding Rayleigh–Taylor Flow and Mixing Using Synergy Between Simulation, Modeling, and Experiment

Simultaneous advances in numerical methods and computing, theoretical techniques, and experimental diagnostics have all led independently to better understanding of Rayleigh–Taylor (RT) instability, turbulence, and mixing. In particular, experiments have provided significant motivation for many simulation and modeling studies, as well as validation data. Numerical simulations have also provided data that is not currently measurable or very difficult to measure accurately in RT unstable flows. Thus, simulations have also motivated new measurements in this class of buoyancy-driven flows. This overview discusses simulation and modeling studies synergistic with experiments and examples of how experiments have motivated simulations and models of RT instability, flow, and mixing. First, a brief summary of measured experimental and calculated simulation quantities, of experimental approaches, and of issues and challenges in the simulation and modeling of RT experiments is presented. Implicit large-eddy, direct numerical, and large-eddy simulations validated using RT experimental data are then discussed. This is followed by a discussion of modeling using analytical, modal, buoyancy–drag, and turbulent transport models of RT mixing experiments. The discussion will focus on three-dimensional RT mixing arising from multimode perturbations. Finally, this focused review concludes with a perspective on future simulation, modeling, and experimental directions for further research. Research in simulation and modeling of RT unstable flows, coupled with experiments, has made significant progress over the past several decades. This overview serves as an opportunity to both discuss progress and to stimulate future research on simulation and modeling of this unique class of hydrodynamically unstable turbulent flows.

42 ENGINEERING↗

In situ , in vivo , and in operando imaging and spectroscopy of liquids using microfluidics in vacuum

This review offers a succinct overview of the development of a vacuum-compatible microfluidic reactor system for analysis at the liquid vacuum interface (SALVI), and its diverse applications in in situ, in vivo, and in operando imaging of liquid surfaces as well as the air-liquid (a-l), liquid-liquid (l-l), and solid-liquid (s-l) interfaces in the past decade. SALVI is one of the first microfluidics-based reactors that has enabled direct analysis of volatile liquids in vacuum surface tools such as scanning electron microscopy (SEM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). Its integration into ambient and vacuum spectroscopy and microscopy is illustrated. Several applications are highlighted including (1) imaging nanoparticles in liquid using in situ SEM; (2) mapping the evolving l-l interface using in situ x-ray absorption spectroscopy and ToF-SIMS; (3) following complex a-l interfacial oxidation reaction products using in situ ToF-SIMS; (4) capturing biological interfaces of cells and microbes via in vivo multimodal and correlative imaging; and (5) monitoring the dynamic solid electrode and liquid electrolyte interface using in operando molecular imaging. Finally, outlook and recommendations are presented. Besides showing the holistic information volume obtained by real-time multiplexed imaging, this review intends to convey the importance of tool development in revolutionizing surface and interface analysis using vacuum platforms previously limited to solid surfaces. Microfluidics is manifested to be not limited to ambient conditions in many examples in this review. Moreover, fundamental interfacial phenomena underpinning mass and charge transfer can now be pursued in real time via innovated chemical imaging and spectroscopy.

42 ENGINEERING↗

Characterization of groove density variation of VLS gratings with ALS XROL LTP-II in different operation modes

The long trace profiler, LTP-II, available at the Advanced Light Source (ALS) X-ray Optics Laboratory (XROL), was recently upgraded by replacing a multimode diode laser light source with a single-mode, wavelength-stabilized, fibercoupled diode laser system. The upgrade enables us to reliably characterize the lateral variation of groove density of variable-line-spacing (VLS) x-ray diffraction gratings. Here, we discuss the LTP-II performance with an example of measurements with a VLS grating with the groove density at the grating center of 300 lines/mm. For the measurements, we use the LTP-II in two different operation arrangements, the single Gaussian beam and the pencil beam interferometer arrangements. For each operation arrangement, we apply two data processing algorithms: with calculating the centroid position and with determining the position of a characteristic features of the detected beam intensity distributions. Additionally, we discuss the observed strong correlation between the LTP-II modes of operation and the resulted (extracted) groove density variations. We also speculate on possible origin of the correlation.

42 ENGINEERING↗

Enabling robust, stable, and accurate nonlinear optical measurements from squeezed light generated in hot rubidium vapor

The feasibility of nonlinear optical (NLO) imaging and spectroscopy using low intensity quantum states of light including entangled photon and squeezed light sources, such as those driven by two-photon absorption (TPA), has been a topic of ongoing debate. An unambiguous identification of the appreciable quantum advantage in such quantum light applications could enable NLO imaging of biological samples without photodegradation and phototoxicity. Recently, we have constructed a two-mode squeezed light source based on four-wave mixing in 85Rb vapor, which is capable of 7.9 dB of intensity-difference squeezing (IDS), corresponding to 8.7 dB upon electronic noise correction. In this talk, we discuss the stability of our system, including implementation details on achieving and maintaining 8.7 dB of IDS for several hours, and ensuring the two spatially multimode beams are properly overlapped in a sample with minimal optical loss.

Allen, Harry [ORNL] (ORCID:0000000190253914)↗

Mechanisms of ultrafast GHz burst fs laser ablation

Gigahertz (GHz) femtosecond (fs) lasers have opened possibilities for enhancing and controlling the laser machining quality to engineer the physicochemical properties of materials. However, fundamental understanding of laser-material interactions by GHz fs laser has remained unsolved due to the complexity of associated ablation dynamics. Here, we study the ablation dynamics of copper (Cu) by GHz fs bursts using in situ multimodal diagnostics, time-resolved scattering imaging, emission imaging, and emission spectroscopy. A combination of probing techniques reveals that GHz fs bursts rapidly remove molten Cu from the irradiated spot due to the recoil pressure exerted by following fs pulses. Material ejection essentially stops right after the burst irradiation due to the limited amount of remnant matter, combined with the suppressed heat conduction into the target material. Our work provides insights into the complex ablation mechanisms incurred by GHz fs bursts, which are critical in selecting optimal laser conditions in cross-cutting processing, micro/nano-fabrication, and spectroscopy applications.

47 OTHER INSTRUMENTATION↗

A composite electrodynamic mechanism to reconcile spatiotemporally resolved exciton transport in quantum dot superlattices

Quantum dot (QD) solids are promising optoelectronic materials; further advancing their device functionality requires understanding their energy transport mechanisms. The commonly invoked near-field Förster resonance energy transfer (FRET) theory often underestimates the exciton hopping rate in QD solids, yet no consensus exists on the underlying cause. In response, we use time-resolved ultrafast stimulated emission depletion (STED) microscopy, an ultrafast transformation of STED to spatiotemporally resolve exciton diffusion in tellurium-doped cadmium selenide–core/cadmium sulfide–shell QD superlattices. We measure the concomitant time-resolved exciton energy decay due to excitons sampling a heterogeneous energetic landscape within the superlattice. The heterogeneity is quantified by single-particle emission spectroscopy. This powerful multimodal set of observables provides sufficient constraints on a kinetic Monte Carlo simulation of exciton transport to elucidate a composite transport mechanism that includes both near-field FRET and previously neglected far-field emission/reabsorption contributions. Uncovering this mechanism offers a much-needed unified framework in which to characterize transport in QD solids and additional principles for device design.

36 MATERIALS SCIENCE↗

Halide segregation to boost all-solid-state lithium-chalcogen batteries

Mixing electroactive materials, solid-state electrolytes, and conductive carbon to fabricate composite electrodes is the most practiced but least understood process in all-solid-state batteries, which strongly dictates interfacial stability and charge transport. Here, we report on universal halide segregation at interfaces across various halogen-containing solid-state electrolytes and a family of high-energy chalcogen cathodes enabled by mechanochemical reaction during ultrahigh-speed mixing. Bulk and interface characterizations by multimodal synchrotron x-ray probes and cryo–transmission electron microscopy show that the in situ segregated lithium halide interfacial layers substantially boost effective ion transport and suppress the volume change of bulk chalcogen cathodes. Various all-solid-state lithium-chalcogen cells demonstrate utilization close to 100% and extraordinary cycling stability at commercial-level areal capacities.

36 MATERIALS SCIENCE↗

A roadmap toward scaling, reasoning and self-evolving foundation models for nuclear and particle physics

Foundation models have revolutionized artificial intelligence, with Large Language Models demonstrating unprecedented capabilities in multimodal understanding, reasoning and tool use. Nuclear and particle physics stands at a critical juncture where similar transformative potential awaits realization. The field generates exabytes of experimental data, exascale simulations, and decades of theoretical insights — yet these remain largely disconnected from modern Artifical Intelligence (AI) capabilities, with most physics AI applications confined to narrow, task-specific models that suffer from domain shifting when applied to real experimental data. We present a roadmap for FM4NPP (Foundation Model for Nuclear and Particle Physics), systematically scaling from current proof-of-concept models to trillion-parameter architectures capable of autonomous discovery. Our approach advances three critical frontiers: unified data infrastructure integrating detector data, scientific knowledge and computational tools across global facilities; multi-facility foundation models enabling cross-experiment knowledge transfer and accelerated discovery; and agentic AI capabilities for reasoning and autonomous tool use. The resulting self-evolving FM4NPP will transform physics research by converting time-intensive data analysis, theory derivation and computational bottlenecks into rapid AI–human collaborative discovery. This paradigm shift promises to fundamentally accelerate scientific progress in nuclear and particle physics, enabling researchers to focus on high-level insights while AI handles routine analysis and explores vast parameter spaces beyond human capacity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data

Zero-shot and prompt-based models have excelled at visual reasoning tasks by leveraging large-scale natural image corpora, but they often fail on sparse and domain-specific scientific image data. We introduce Zenesis, a no-code interactive computer vision platform designed to reduce data readiness bottlenecks in scientific imaging workflows. Zenesis integrates lightweight multimodal adaptation for zero-shot inference on raw scientific data, human-in-the-loop refinement, and heuristic-based temporal enhancement. We validate our approach on Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) datasets of catalyst-loaded membranes. Zenesis outperforms baselines, achieving an average accuracy of 0.947, Intersection over Union (IoU) of 0.858, and Dice score of 0.923 on amorphous catalyst samples; and 0.987 accuracy, 0.857 IoU, and 0.923 Dice on crystalline samples. These results represent a significant performance gain over conventional methods such as Otsu thresholding and standalone models like the Segment Anything Model (SAM). Zenesis enables effective image segmentation in domains where annotated datasets are limited, offering a scalable solution for scientific discovery.

Mukherjee, Shubhabrata↗

CRISPR Tools for Engineering Prokaryotic Systems: Recent Advances and New Applications

In the past decades, the broad selection of CRISPR-Cas systems has revolutionized biotechnology by enabling multimodal genetic manipulation in diverse organisms. Rooted in a molecular engineering perspective, we recapitulate the different CRISPR components and how they can be designed for specific genetic engineering applications. We first introduce the repertoire of Cas proteins and tethered effectors used to program new biological functions through gene editing and gene regulation. We review current guide RNA (gRNA) design strategies and computational tools and how CRISPR-based genetic circuits can be constructed through regulated gRNA expression. Then, we present recent advances in CRISPR-based biosensing, bioproduction, and biotherapeutics across in vitro and in vivo prokaryotic systems. Finally, we discuss forthcoming applications in prokaryotic CRISPR technology that will transform synthetic biology principles in the near future.

59 BASIC BIOLOGICAL SCIENCES↗

Bismuth Enables the Formation of Disordered Birnessite in Rechargeable Alkaline Batteries

Recent advances in rechargeable Zn/MnO$_2$ alkaline batteries have shown promise for scalable energy storage systems which provide a safe, low-cost alternative with a demonstrated lifetime over thousands of cycles. This cathode technology is based on a 2-electron Mn redox process where a layered birnessite-type phase has been shown to form after the first cycle with excellent reversibility between the discharge product, Mn(OH)$_2$. Herein, we investigate the reversible reaction between birnessite and Mn(OH)$_2$ with and without a Bi$_2$O$_3$ additive using multimodal structural characterization techniques during active battery cycling. Diffraction results provide evidence of Bi$^{3+}$ residing in the interlayer of birnessite which prevents irreversible Mn$_3$O$_4$ formation by limiting Mn$^{3+}$ diffusion within the crystal lattice. Also, upon charge no MnOOH intermediate phases are observed. Instead, X-ray absorption and Raman spectroscopy indicate a disordered, non-crystalline birnessite-type phase consisting of mostly neutral H$_2$O within the interlayer. Birnessite phases will reform without Bi$_2$O$_3$ present, but Mn$_3$O$_4$ formation severely polarizes the potential they are formed at, leading to capacity fade. Also, we discuss the reversible Bi$_2$O$_3$ conversion to Bi$^0$ and its contribution to the observed capacity. We expect the results will provide crucial insight into the development of aqueous, rechargeable battery systems utilizing MnO 2 .

25 ENERGY STORAGE↗

Review—Fundamental Uranium Electrochemistry and Spectroscopy in Molten Salt Systems

Uranium is a key element used for nuclear energy production. Some advanced reactor designs, specifically molten salt reactors, will continue to use uranium as the fissile material for energy production. These new technologies require an intimate understanding of uranium chemistry during and after energy production. This review covers contemporary research on the coordination chemistry and behavior of uranium with the coolant and pyroprocessing salts as proposed for use in future reactor designs. Discussed topics include the nature of U redox reactions involving the reduction of U(III) to U metal and oxidation of U(III) to U(IV). These systems have been interrogated using cyclic voltammetry, chronopotentiometry, and optical and X-ray absorption spectroscopies. Insights obtained into the electrode potentials, the uranium species, and their diffusion coefficients in alkali halide melts from decades of research are summarized selectively. Further, perspectives are provided on the importance of unifying studies for comparison across multiple institutions. The application of synchrotron radiation research and multimodal approaches involving two (or more) probes, such as the widespread combination of UV–visible spectroscopy and electroanalysis known as spectroelectrochemistry, can provide new knowledge about the main process of uranium electrorefining—diffusion, as will be demonstrated in this review through the lack of comparable results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

pnnl/Multimodal-Few-Shot

This project combines few-shot machine learning with a multimodal framework for electron microscope data quantification.

Doty, Christina↗

SysCaps (Language Interfaces for Simulation Surrogates of Complex Systems) [SWR-24-97]

You've found the official code repository for the paper "SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems," presented at the Foundation Models for Science: Progress, Opportunities, and Challenges workshop at NeurIPS 2024. Our paper conjectures that interfaces (both text templates as well as conversational) makes interacting with simulation surrogate models for complex systems more intuitive and accessible for both non-experts and experts. "System captions", or SysCaps, are text-based descriptions of systems based on information contained in simulation metadata. Our paper's goal is to train multimodal regression models that take text inputs (SysCaps) and timeseries inputs (exogenous system conditions such as hourly weather) and regress timeseries simulation outputs (e.g. hourly building energy consumption). The experiments in our paper with building and wind farm simulators, which can be reproduced using this codebase, aim to help us understand whether a) accurate regression in this setting is possible and b) if so, how well can we do it. Paper: https://arxiv.org/abs/2405.19653

Emami, Patrick↗

pnnl/SciTune

Scientific multimodal instruction tuning with large language and vision models.

Horawalavithana, Sameera [Pacific Northwest Nation↗

CQM-Analysis v1.0

This repository contains the data and code necessary to reproduce the primary analysis and figures for the manuscript "Pathways to productivity: mapping the relationship between multimodal transportation infrastructure, commute quality, and economic vitality for the United States workforce". The analysis demonstrates a newly defined commute quality metric (CQM) characterizing the quality, as a monetized consumer surplus, of travel for the purpose of work for every census tract in the continental United States. The analysis additionally demonstrates the correlation of that CQM with key economic vitality indicators. Specifically median household income and unemployment rate.

Spurlock, C Anna [Lawrence Berkeley National Labor↗

LLaMP v0.1.0

Reducing hallucination of Large Language Models (LLMs) is imperative for use in the sciences, where reliability and reproducibility are crucial. However, LLMs inherently lack long-term memory, making it a nontrivial, ad hoc, and inevitably biased task to fine-tune them on domain-specific literature and data. LLaMP is a multimodal retrieval-augmented generation (RAG) framework of hierarchical reasoning and acting (ReAct) agents that can dynamically and recursively interact with Materials Project to ground large language models on high-fidelity materials informatics.

Riebesell, Janosh [Lawrence Berkeley National Labo↗