Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Advanced Measurement Technique”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Review of Nanocarbon-Based Anode Materials for Lithium-Ion Batteries

Renewable and non-renewable energy harvesting and its storage are important components of our everyday economic processes. Lithium-ion batteries (LIBs), with their rechargeable features, high open-circuit voltage, and potential large energy capacities, are one of the ideal alternatives for addressing that endeavor. Despite their widespread use, improving LIBs’ performance, such as increasing energy density demand, stability, and safety, remains a significant problem. The anode is an important component in LIBs and determines battery performance. To achieve high-performance batteries, anode subsystems must have a high capacity for ion intercalation/adsorption, high efficiency during charging and discharging operations, minimal reactivity to the electrolyte, excellent cyclability, and non-toxic operation. Group IV elements (Si, Ge, and Sn), transition-metal oxides, nitrides, sulfides, and transition-metal carbonates have all been tested as LIB anode materials. However, these materials have low rate capability due to weak conductivity, dismal cyclability, and fast capacity fading owing to large volume expansion and severe electrode collapse during the cycle operations. Contrarily, carbon nanostructures (1D, 2D, and 3D) have the potential to be employed as anode materials for LIBs due to their large buffer space and Li-ion conductivity. However, their capacity is limited. Blending these two material types to create a conductive and flexible carbon supporting nanocomposite framework as an anode material for LIBs is regarded as one of the most beneficial techniques for improving stability, conductivity, and capacity. This review begins with a quick overview of LIB operations and performance measurement indexes. It then examines the recently reported synthesis methods of carbon-based nanostructured materials and the effects of their properties on high-performance anode materials for LIBs. These include composites made of 1D, 2D, and 3D nanocarbon structures and much higher Li storage-capacity nanostructured compounds (metals, transitional metal oxides, transition-metal sulfides, and other inorganic materials). The strategies employed to improve anode performance by leveraging the intrinsic features of individual constituents and their structural designs are examined. The review concludes with a summary and an outlook for future advancements in this research field.

25 ENERGY STORAGE↗
DOE OSTI2024

Advancing Li-plating detection: Motivating a multi-signal correlation approach

Facilitating fast charging in lithium-ion batteries (LiBs) is often linked to Li-plating, which harms performance, longevity, and safety. Early detection of Li-plating is essential for rapid technological development and for preventing performance deterioration and ensuring safety during operation. Fast and real-time detection, using commonly collected measurements like voltage (V), current (I), temperature (T), and pressure (P), is highly desirable. Existing standalone methods relying on electrochemical and mechanical signatures, using half, smaller, or specially designed cells often operated at lower temperatures, fail to account for real-world fast-charging conditions. These signatures may also have inherent unreliability in aged LiBs, a phenomenon currently not-well understood. All these uncertainties have complicated practical implementation of a robust Li-plating detection technique. This study, through multiple case studies involving real-world fast-charging conditions using automotive-grade 11.6 Ah LiBs, shows that many single signal-based diagnostic techniques may be inadequate to detect Li-plating. Among various signatures, end-of-charge rest pressure, differential pressure-sensing, and end-of-charge rest voltage were identified as particularly useful in detecting Li-plating. Furthermore, A multi-signal-based detection technique is shown to be more robust in detecting Li-plating. Using both fresh and aged cells, the results and analysis highlight how detection capabilities are influenced by various factors, including battery design, size, charging speed, operating temperature, and degradation level. Adopting such a multi-signal Li-plating detection approach may be instrumental in the rapid development of battery technology in laboratories, as well as ensuring the enhanced safety of next-generation LiBs in real-world fast-charging applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Quantitative Electron Beam‐Single Atom Interactions Enabled by Sub‐20‐pm Precision Targeting

The ability to probe and control matter at the picometer scale is essential for advancing quantum and energy technologies. Scanning transmission electron microscopy offers powerful capabilities for materials analysis and modification, but sample damage, drift, and scan distortions hinder single atom analysis and deterministic manipulation. Materials analysis and modification via electron–solid interactions can be transformed by precise delivery of electrons to a specified atomic location, maintaining the beam position despite drift, and minimizing collateral dose. Here a fast, low-dose, sub-20-pm precision electron beam positioning technique is developed, “atomic lock-on,” (ALO), which offers the ability to position the beam on a specific atomic column without previously irradiating that column. This technique is used to lock onto a single selected atomic location to repeatedly measure its weak electron energy loss signal despite sample drift. Moreover, electron beam-matter interactions in single atomic events are measured with μ s time resolution. This enables observation of single-atom dynamics, such as atomic bistability, revealing partially bonded atomic configurations and recapture phenomena. This opens prospects for using electron microscopy for high-precision measurements and deterministic control of matter for quantum technologies.

2D materials↗
DOE OSTI2022

Advanced Laboratory and Field Arrays: Debris Modeling, Detection,& Mitigation (Task 1)

The statement of project objectives for this task was: develop tools, methods and models to assess, and mitigate the risk of damage to MHK infrastructure from woody debris. Develop the capability to detect woody debris using sonar and/or physical methods for purposes of characterizing debris statistics in river (at UAF’s Tanana River Test Site) and near-shore wave (at Yakutat, AK) environments and to activate debris mitigation measures. Develop debris impact risk maps and tables using statistics on debris size, geometry, type, prevalence, mobility and location. Improve and apply the COUPi discrete element method (DEM) to develop models of debris movement and impact on MHK infrastructure to evaluate risk of damage, and interference, to operations from debris. The proposed final deliverable for the task was a set of tools or techniques for providing estimates of the probability of debris impact, and resulting impact forces, on MHK infrastructure as a function of debris size, type, wave regime, and current velocity. Such estimates are required to assess damage risks to operational MHK infrastructure.

13 HYDRO ENERGY↗
DOE OSTI2022

Sizes of pure and doped helium droplets from single shot x-ray imaging

Advancements in x-ray free-electron lasers on producing ultrashort, ultrabright, and coherent x-ray pulses enable single-shot imaging of fragile nanostructures, such as superfluid helium droplets. Furthermore, this imaging technique gives unique access to the sizes and shapes of individual droplets. In the past, such droplet characteristics have only been indirectly inferred by ensemble averaging techniques. Here, we report on the size distributions of both pure and doped droplets collected from single-shot x-ray imaging and produced from the free-jet expansion of helium through a 5 μm diameter nozzle at 20 bars and nozzle temperatures ranging from 4.2 to 9 K. This work extends the measurement of large helium nanodroplets containing 10 9 –10 11 atoms, which are shown to follow an exponential size distribution. Additionally, we demonstrate that the size distributions of the doped droplets follow those of the pure droplets at the same stagnation condition but with smaller average sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Addressing Critical Problems in Materials Science Through Multiscale and Multimode Characterization (Project 1); Characterization and Optimization of Novel Triple-Conducting Oxide Materials for Energy Applications (Project 2) (CRADA Final Report)

PROJECT 1: Address critical problems in materials science and simultaneously advance the state-of-the-art in multiscale and multimode characterization using the combined advanced analytical capabilities and expertise of Colorado School of Mines (CSM) and the National Renewable Energy Laboratory (NREL). The primary effort of the Phase I of this CRADA is to establish the International Center for Multiscale Characterization using shared resources at both NREL and CSM. Phase II will focus on capability development and marketing, choosing candidate materials science issues in the areas of structure imaging, chemical composition mapping, and correlating properties and performance of materials for impact in energy-related, environmental and critical materials areas. The CRADA will be modified to include specific topics of concern in materials science to industry member partners. Advanced analytical capabilities and expertise at CSM and NREL will be used to advance materials understanding and performance through characterization of multiscale phenomena including structural imaging, chemical composition mapping, and other techniques correlating properties and performance of materials. PROJECT 2: As part of the International Center for Materials Characterization, work under Modification #1 will be led by Colorado School of Mines (CSM), working in collaboration with NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments. The purpose of the modification is to provide for NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments, including mentoring and advising the CSM-NREL team on proper Secondary Ion Mass Spectrometry (SIMS) data analysis as needed. SIMS measurements of 10-20 samples will be performed at NREL during the project duration.

08 HYDROGEN↗
DOE OSTI2026

Wind and Temperature Consensus at Horn Point, HU-Beltsville, Piney Run (Maryland) in support of CoURAGE

The Maryland Department of the Environment (MDE) operates a ground-based atmospheric profiling network consisting of collocated radar wind profilers (RWP) and radio acoustic sounding systems (RASS) as part of its Ambient Air Monitoring Program. This network provides continuous observations of wind and temperature structure in the lower troposphere to support air quality forecasting, regulatory analysis, and atmospheric research. The network currently includes three fixed sites across Maryland: Horn Point (HP, lower eastern shore) [38.587525°,-76.141006°], Howard University-Beltsville (HUB, central Maryland) [39.055277°, -76.878632°], and Piney Run (PR, western Maryland) [39.705950°, -79.012000°] The network is designed to capture regional variability in atmospheric transport and boundary-layer processes. These systems measure vertical profiles of horizontal wind speed and direction using Doppler radar techniques, with observations typically spanning from ~100 m above ground level up to approximately 2.5–4 km. Measurements are derived from the Doppler shift of backscattered electromagnetic signals, enabling retrieval of wind vectors at multiple altitudes with high temporal resolution (e.g., 30-minute averages reported every 6 minutes). Each radar wind profiler is paired with a Radio Acoustic Sounding System (RASS) to provide profiles of virtual temperature in the lower atmosphere (~100–200 m AGL) by measuring the propagation speed of acoustic waves. Together, the RWP/RASS system yields a coupled data set of thermodynamic and kinematic atmospheric structure, including additional parameters such as vertical velocity, radial velocity, signal-to-noise ratio, and spectral width for advanced analysis. There are two types of files for each station: wind data (files with a "w" prefix) and virtual temperature RASS data (files with a "t" prefix). The wind data files are in the format wYYDDD.cns, where YY is the 2-digit year and DDD is the day of the year. The RASS virtual temperature data files are in the format tYYDDD.cns. Each record has the following header structure: Line 1 : Station Name RASS files Line 2 : RASS rev DeTect_2.0, WINDS files Line 2 : WINDS rev ATI 5.1 Line 3 : N latitude, W longitude, and site elevation (m) Line 4 : Date and begin time of consensus: yy mm dd hh mn ss plus # minutes to add to get UTC Line 5 : Consensus averaging time (minutes); number of beams; number of range gates Line 6 : Number of records required to make consensus (num) total number of records (tot) and the consensus window size (m/s) in the format: num:tot (window) RASS files Line 7 : no. of coded cells, no. of spec, pulse width (ns), and inter-pulse period (µs), WINDS files Line 7 : No. of coded cells, no. of spectra, pulse width (ns), and inter-pulse period (µs), each with a pair of values: first value is for oblique beams, second for vertical RASS files Line 8 : Full scale Doppler value (m/s) Delay to first gate (ns) Number of gates Spacing of gates (ns), WINDS files Line 8 : Full scale Doppler velocity (m/s), oblique and vertical Vertical correction applied to oblique beams? (0 = no, 1 = yes) Delay to first gate (ns), oblique and vertical Number of gates, oblique and vertical Spacing of gates (ns), oblique and vertical Line 9 : Azimuth and elevation (9s indicate vertical beam not used) RASS files Line 10, values : HT = Height above ground (km), T = Uncorrected virtual temperature consensus (deg C), Tc = Corrected virtual temperature consensus (deg C), W = Vertical wind consensus (9s indicate vertical beam not used, w-component, positive upward, m/s), CNT = Number of records that made consensus (for the 3 values in same order), SNR = Average signal to noise ratio (dB) of records in consensus (same order) WINDS files Line 10, values : HT = Height above ground (km), SPD = Wind speed (m/s), DIR = Wind direction (deg E of N from N), RAD = Radial velocities for each beam (m/s) in order given in azimuth and elevation line (positive toward radar; 9s indicate vertical beam not used, CNT = Number of records that made consensus, SNR = Average signal to noise ratio (dB) of records in consensus

{"wind speed and direction",temperature}↗
DOE OSTI2021

The In Situ Ion Irradiation Toolbox: Time-Resolved Structure and Property Measurements

Abstract The dynamic interactions of ions with matter drive a host of complex evolution mechanisms, requiring monitoring on short spatial and temporal scales to gain a full picture of a material response. Understanding the evolution of materials under ion irradiation and displacement damage is vital for many fields, including semiconductor processing, nuclear reactors, and space systems. Despite materials in service having a dynamic response to radiation damage, typical characterization is performed post-irradiation, washing out all information from transient processes. Characterizing active processes in situ during irradiation allows the mechanisms at play during the dynamic ion-material interaction process to be deciphered. In this review, we examine the in situ characterization techniques utilized for examining material structure, composition, and property evolution under ion irradiation. Covering analyses of microstructure, surface composition, and material properties, this work offers a perspective on the recent advances in methods for in situ monitoring of materials under ion irradiation, including a future outlook examining the role of complementary and combined characterization techniques in understanding dynamic materials evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

CubeSats for Gamma-Ray Astronomy [Book Chapter]

After many years of flying in space primarily for educational purposes, CubeSats – tiny satellites with form factors corresponding to arrangements of “1U” units, or cubes, each 10 cm on a side – have come into their own as valuable platforms for technology advancement and scientific investigations. CubeSats offer comparatively rapid, low-cost access to space for payloads that can be built, tested, and operated by relatively small teams, with substantial contributions from students and early career researchers. Continuing advances in compact, low-power detectors, readout electronics, and flight computers have now enabled X-ray and gamma-ray sensing payloads that can fit within the constraints of CubeSat missions, permitting in-orbit demonstrations of new techniques and innovative high-energy astronomy observations. Gamma-ray-sensing CubeSats are certain to make an important contribution in the new era of multi-messenger, time-domain astronomy by detecting and localizing bright transients such as gamma-ray bursts, solar flares, and terrestrial gamma-ray flashes; however, other astrophysical science areas requiring long observations in a low-background environment, including gamma-ray polarimetry, studies of nuclear lines, and measurement of diffuse backgrounds, will likely benefit as well. Here we present the primary benefits of CubeSats for high-energy astronomy, highlight the scientific areas currently or soon to be studied, and review the missions that are currently operating, under development, or proposed. A rich portfolio of CubeSats for gamma-ray astronomy already exists, and the potential for a broad range of creative and scientifically productive missions in the near future is very high.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗
DOE OSTI2022

Automatic Qubit Characterization and Gate Optimization with QubiC

As the size and complexity of a quantum computer increases, quantum bit (qubit) characterization and gate optimization become complex and time-consuming tasks. Current calibration techniques require complicated and verbose measurements to tune up qubits and gates, which cannot easily expand to the large-scale quantum systems. We develop a concise and automatic calibration protocol to characterize qubits and optimize gates using QubiC, which is an open source FPGA (field-programmable gate array) based control and measurement system for superconducting quantum information processors. We propose multi-dimensional loss-based optimization of single-qubit gates and full XY-plane measurement method for the two-qubit CNOT gate calibration. We demonstrate the QubiC automatic calibration protocols are capable of delivering high-fidelity gates on the state-of-the-art transmon-type processor operating at the Advanced Quantum Testbed at Lawrence Berkeley National Laboratory. Finally, the single-qubit and two-qubit Clifford gate infidelities measured by randomized benchmarking are of 4.9(1.1) × 10 -4 and 1.4(3) × 10 -2 , respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Microanalytical Approaches to Characterizing REE in Appalachian Basin Underclays

The search for a reliable U.S. domestic source of rare earth elements (REE) is necessary to support the demand of advanced energy applications (e.g., catalysts, electronics, magnets). Sedimentary deposits may be sources for selectively recovering REE and critical metals—specifically the interbedded seat rock, or underclay, that underlies or forms the floor of a coal seam. This material is often a major component of coal waste fines and refuse and thus readily available. This study examines several Appalachian Basin underclays associated with actively mined coal seams as potential feedstocks for the REE. Multimodal microanalytical electron microscopy (SEM, FIB-SEM, EMPA) synchrotron-based µXRF, and image processing techniques are coupled with detailed elemental and mineral data to classify the 2D and 3D petrophysical properties of the materials. The REE contents of Appalachian Basin underclays were measured from 235–399 ppm and predominantly observed as discrete REE-bearing minerals such as monazite and xenotime on the order of 10–100 µm in size. These REE-bearing minerals typically accounted for less than 1% of the scanned areas and volumes under SEM and FIB-SEM analysis, with the exception of regions enriched in crandallite. Synchrotron-based µXRF elemental maps further identified several REE deposition environments in different underclays, including micro-scale (10–100 µm) light REEs co-localizing with Ca and P, micro-scale heavy REEs with Fe, and large-scale light REEs (>200 µm) co-localizing with Sr, Ba, Ca and P.

36 MATERIALS SCIENCE↗
DOE OSTI2020

UO 2 + 5 vol% ZrB 2 nano composite nuclear fuels with full boron retention and enhanced oxidation resistance

The boron isotope ( 10 B) can be used as a neutron absorber in UO 2 to control the reactivity of nuclear fuel pellets, however, the boron source can react with oxygen source in UO 2 to form B 2 O 3 that vaporize readily at temperatures above 1200 °C. Unfortunately, the sintering of UO 2 fuel requires hours holding at high temperature (>1700 °C), resulting in an inevitable B loss during sintering and unpredictable B concentration in final product. It is challenging to incorporate boron through a conventional sintering method. In this work, we demonstrated that spark plasma sintering (SPS), a field assisted sintering technology, can effectively densify UO 2 + 5 vol% ZrB 2 composite fuel pellets by rapid consolidation at 1600 °C for a short duration of 5 min under an applied pressure of 40 MPa. Further, thermogravimetric analysis (TGA) measurements confirm that ZrB 2 is fully retained inside the composite fuel pellets. Inside the composite fuel pellets, nano sized ZrB 2 particles are uniformly distributed along the grain boundaries of the UO 2 matrix. The ZrB 2 particle transforms to a glassy B 2 O 3 phase covering the sample surface and grain boundaries of UO 2 matrix after a simple post-sintering annealing at 1000 °C in flowing Argon gas for 4 h. The formed glassy B 2 O 3 slows down the diffusion of oxygen ions and postpones the onset temperature for oxidation of UO 2 from 400 °C to 550 °C. This study demonstrates the capability of SPS, an advanced fuel manufacturing technique, to achieve a full retention of ZrB 2 in UO 2 oxide fuel and increase oxidation resistance through a simple post-sintering annealing. The reported work holds great engineering potential for development of advanced oxide fuel for nuclear application.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Porous potassium tantalate-reduced graphene oxide nano cube architecture for high performance hybrid supercapacitors

Energy storage has always been a major concern in the present-day situation. Advanced energy storage devices are batteries, supercapacitor and solar cells. However, advancements have been noteworthy in the field of high-performance hybrid supercapacitors. On this note, we have fabricated a hybrid supercapacitor electrode material Potassium tantalate nano cube (KT NCs) and its reduced graphene oxide composite (KT-rGO NCs) and tested its electrochemical performance. The materials showed high performances with specific capacitance of 565 F/g for KT NCs and 850 F/g for KT-rGO NCs respectively. Energy densities of both KT NCs & KT-rGO NCs are 28.24 Wh/Kg and 29.50 Wh/kg with good retention capacities. Further detailed study of both KT NCs and KT-rGO NCs are carried out with characterization techniques like XRD, FTIR, BET, Raman and HRTEM for structural analysis and electrochemical measurements to analyse various parameters pertaining to its charge storage capacity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strong Local Passivity in Unconventional Scenarios: A New Protocol for Amplified Quantum Energy Teleportation

Quantum energy teleportation (QET) has been proposed to overcome the restrictions of strong local passivity (SLP) and to facilitate energy transfer in quantum systems. Traditionally, QET has only been considered under strict constraints, including the requirements that the initial state be the ground state of an interacting Hamiltonian, that Alice’s measurement commute with the interaction terms, and that entanglement be present. These constraints have significantly limited the broader applicability of QET protocols. In this work, we demonstrate that SLP can arise beyond these conventional constraints, establishing the necessity of QET in a wider range of scenarios for local energy extraction. This leads to a more flexible and generalized framework for QET. Furthermore, we introduce the concept of a “local effective Hamiltonian,” which eliminates the need for optimization techniques in determining Bob’s optimal energy extraction in QET protocols. As an additional advantage, the amount of energy that can be extracted using our new protocol is amplified to be 7.2 times higher than that of the original protocol. These advancements enhance our understanding of QET and extend its broader applications to quantum technologies. To support our findings, we implement the protocol on quantum hardware, confirming its theoretical validity and experimental feasibility.

amplified energy extraction↗
DOE OSTI2025

Tracking Dendritic Growth in Hydrogen-Based Hematite Reduction via Computer Vision

The reduction of hematite to metallic iron using hydrogen (H2) as a reducing agent presents a promising pathway for decarbonizing steel production. In this study, we employ a combination of in situ confocal scanning laser microscopy (CSLM) and advanced computer vision techniques to quantitatively analyze dendritic growth of ferrite during H2-based reduction of iron oxide at high temperatures. A workflow integrating Watershed Image Segmentation (WIS) and Lucas-Kanade Optical Flow (LKOF) is developed to extract both global and local kinetic information from time-resolved micrograph sequences. H2 reduction experiments conducted at 1400 degrees C and 1500 degrees C demonstrate a clear correlation between temperature and reduction rate, as evidenced by accuracy of fitted Johnson-Mehl-Avrami-Kolmogorov (JMAK) parameters. Optical flow analysis further elucidates the anisotropic and branched nature of dendritic growth, providing spatially resolved velocity fields that correlate well with global transformation kinetics. The proposed methodology demonstrates strong agreement with experimental measurements and literature values, offering a robust framework for automated image-based analysis to study kinetics through microstructural evolution in the reduction of iron ore, and likely other reaction-diffusion phenomena.

08 HYDROGEN↗
DOE OSTI2025

Improved liquid lithium surfaces in the Lithium Tokamak Experiment-β

Advances in vacuum, surface, and lithium conditioning techniques throughout five years of continuous operations in LTX-β have produced mirror-like liquid lithium surfaces and demonstrated the feasibility of high-performance tokamak discharges fully surrounded by liquid metal without significant operational problems. Improvements in conditioning techniques and procedures, including many weeks of baking and accumulation of 70 g of Li, led to reduced residual gasses and clean Li surfaces - all while still maintaining enough operational flexibility for multiple in-vacuum diagnostic upgrades and calibrations. Coatings had a visibly clean appearance, with reflective liquid metal demonstrating good wetting and surface adhesion with films that were now macroscopically thick. Solidified Li showed large crystal grains, while surface science measurements observed reduced impurities in the lithium. Steadily improved plasma performance was achieved with liquid lithium, with discharges able to match solid Li in terms of evolution of I p and n e , including rapid density pumping indicating low recycling. There were indications of moderately increased Li impurity influx, though few significant disturbances by the large liquid surfaces on tokamak operations over hundreds of discharges. Liquid metal plasma facing components are a potential solution to the extreme heat and particle fluxes that could cause unacceptable damage to solid materials, while liquid lithium also has the potential for greatly increased confinement in the low-recycling regime. While many liquid metal approaches are possible, and numerous experiments have been conducted in test stands and small modules in fusion devices, LTX-β is the only tokamak operated while fully surrounded by liquid metal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗