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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Impact of Color Space and Color Resolution on Vehicle Recognition Models

In this study, we analyze both linear and nonlinear color mappings by training on versions of a curated dataset collected in a controlled campus environment. We experiment with color space and color resolution to assess model performance in vehicle recognition tasks. Color encodings can be designed in principle to highlight certain vehicle characteristics or compensate for lighting differences when assessing potential matches to previously encountered objects. The dataset used in this work includes imagery gathered under diverse environmental conditions, including daytime and nighttime lighting. Experimental results inform expectations for possible improvements with automatic color space selection through feature learning. Moreover, we find there is only a gradual decrease in model performance with degraded color resolution, which suggests the need for simplified data collection and processing. By focusing on the most critical features, we could see improved model generalization and robustness, as the model becomes less prone to overfitting to noise or irrelevant details in the data. Such a reduction in resolution will lower computational complexity, leading to quicker training and inference times.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Resolving ECRH deposition broadening due to edge turbulence in DIII-D

Microwave heat pulse propagation experiments have demonstrated a correlation between millimeter-scale turbulence and deposition profile broadening of electron cyclotron (EC) waves on the DIII-D tokamak. In a set of discharges in DIII-D, a variation in edge density fluctuations on the mm-scale is associated with 40%–150% broader deposition profiles, expressed in terms of normalized minor radius, as compared with equilibrium ray tracing. The 1D power profile is determined from transport analysis of the electron temperature response to EC power modulation using perturbative analysis with a square wave power modulation at 20–70 Hz, producing a series of Fourier harmonics that are fit collectively to resolve transport. Fitting an integrated heat flux expressed in the Fourier basis of the modulation to diffusive, convective, and coupled transport terms in a linear model can resolve the broadened EC deposition width from the power perturbation to resolve a broadening in each case. The best fit degree of beam broadening observed scales approximately linearly with the Doppler backscattering measured fluctuation level in the steep gradient region. Quantifying the effect of edge fluctuation broadening on EC current drive power needs of future devices will require 3D full-wave codes that can be validated on the current generation of machines. These DIII-D experiments provide a quantitative measure of fluctuation effects and a dataset to benchmark full-wave simulations that can model and eventually predict nonlinear effects neglected by 1D equilibrium beam and ray tracing.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Angstrom-Resolved Interfacial Structure in Buried Organic-Inorganic Junctions

Charge transport processes at interfaces which are governed by complex interfacial electronic structure play a crucial role in catalytic reactions, energy storage, photovoltaics, and many biological processes. Here, the first soft X-ray second harmonic generation (SXR-SHG) interfacial spectrum of a buried interface (boron/Parylene-N) is reported. SXR-SHG shows distinct spectral features that are not observed in X-ray absorption spectra, demonstrating its extraordinary interfacial sensitivity. Comparison to electronic structure calculations indicates a boron-organic separation distance of 1.9 {\AA}, wherein changes as small as 0.1 {\AA} result in easily detectable SXR-SHG spectral shifts (ca. 100s of meV). As SXR-SHG is inherently ultrafast and sensitive to individual atomic layers, it creates the possibility to study a variety of interfacial processes, e.g. catalysis, with ultrafast time resolution and bond specificity.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

A time-parallel method for scalable heat transfer simulations of additive manufacturing

Here, a major challenge in simulating the thermal behavior in additive manufacturing processes is the disparate length and time scales between transport phenomena occurring in the melt pool and the component. A common simulation approach relies on spatial decomposition for parallel computing, but due to the nature of heat transfer in AM, where most of the computational expenditure is localized near the melt pool, the computational speedup from spatial parallelization saturates quickly. Therefore, additional parallelism by means of time-domain decomposition is needed to fully take advantage of high-performance computing (HPC) resources. This work introduces a time-parallel method to improve the computational scalability of additive manufacturing simulations on HPC systems, while maintaining high temporal resolution of heat transfer near the melt pool. The method, inspired by the nonlinear paraexp formalism, performs an iterative superposition of nonlinear solutions to the initial value problem, integrating the heat equation across overlapping time-parallel intervals. For a single layer of the NIST AMB2018–01 L7 benchmark problem, the method achieves a 38.51x speedup in wall-clock time with a maximum error in the global temperature solution of 0.99%. This reduces the total solution time from 196.72 min to 5.11 min on 128 nodes of the ORNL Frontier supercomputer. The tradeoff between accuracy and total wall-clock time is investigated and recommendations for time-parallel deployment for AM problems are made.

Additive manufacturing↗
DOE OSTI2021

Effective kinetics driven by dynamic concentration gradients under coupled transport and reaction

Biogeochemical reaction kinetics are generally established from batch reactors where concentrations are uniform. In natural systems, many biogeochemical processes are characterized by spatially and temporally variable concentration gradients that often occur at scales which are not resolved by field measurements or biogeochemical and reactive transport models. Yet, it is not clear how these sub-scale chemical gradients affect reaction kinetics compared to batch kinetics. Here we investigate this question by studying the paradigmatic case of localized pulses of solute reacting with a solid or a dissolved species in excess. Additionally, we consider non-linear biogeochemical reactions, representative of mineral dissolution, adsorption and redox reactions, which we quantify using simplified power-law kinetics. The combined effect of diffusion and reaction leads to effective kinetics that differ quantitatively and qualitatively from the batch kinetics. Depending on the nonlinearity (reaction order) of the local kinetics, these effects lead to either enhancement or decrease of the overall reaction rate, and result in a rich variety of reaction dynamics. We derive analytical results for the effective kinetics, which are validated by comparison to direct numerical simulations for a broad range of Damköhler numbers and reaction order. Our findings provide new insights into the interpretation of imperfectly mixed lab experiments, the effective kinetics of field systems characterized by intermittent reactant release and the integration of sub-scale concentration gradients in reactive transport models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Investigating Thaw and Plant Productivity Constraints on Old Soil Carbon Respiration From Permafrost

Isotopic radiocarbon (Δ 14 C) signatures of ecosystem respiration (Reco) can identify old soil carbon (C) loss and serve as an early indicator of permafrost destabilization in a warming climate. Warming also stimulates plant productivity causing plant respiration to dominate Reco Δ 14 C signatures and potentially obscuring old soil C loss. Here, we investigate how a wide spatio-temporal gradient of permafrost thaw and plant productivity affects Reco Δ 14 C patterns and isotopic partitioning. Spatial gradients came from a warming experiment with doubling thaw depth and variable biomass, and a vegetation removal manipulation to eliminate plant contributions. We sampled in August and September to capture transitions from high to low plant productivity, decreased surface soil temperature, and relatively small seasonal thaw extensions. We found that surface processes dominate spatial variation in old soil C loss and a process-based partitioning approach was crucial for constraining old soil C loss. Resampling the same plots in different times of the year revealed that old soil C losses tripled with cooling surface temperature, and the largest old soil C losses were detected when the organic-to-mineral soil horizons thawed (~50–60 cm). We suggest that the measured increase in old soil respiration over the season and when the organic-to-mineral horizon thawed, may be explained by mobilization of nitrogen that stimulates microbial decomposition at depth. Our results suggest that soil C in the organic to mineral horizon may be an important source of soil C loss as the entire Arctic region warms and could lead to nonlinearities in projected permafrost climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mitigation of the internal p-n junction in CoS 2 -contacted FeS 2 single crystals: Accessing bulk semiconducting transport

Pyrite FeS 2 is an outstanding candidate for a low-cost, nontoxic, sustainable photovoltaic material, but efficient pyrite-based solar cells are yet to materialize. Recent studies of single crystals have shed much light on this by uncovering a p-type surface inversion layer on n-type (S-vacancy doped) crystals, and the resulting internal p-n junction. This leaky internal junction likely plays a key role in limiting efficiency in pyrite-based photovoltaic devices, also obscuring the true bulk semiconducting transport properties of pyrite crystals. Here, we demonstrate complete mitigation of the internal p-n junction in FeS 2 crystals by fabricating metallic CoS 2 contacts via a process that simultaneously diffuses Co (a shallow donor) into the crystal, the resulting heavy n doping yielding direct Ohmic contact to the interior. Low-temperature bulk transport studies of controllably Co- and S-vacancy doped semiconducting crystals then enable a host of previously inaccessible observations and measurements, including determination of donor activation energies (which are as low as 5 meV for Co), observation of an unexpected second activated transport regime, realization of electron mobility up to 2100 cm 2 V –1 s –1 , elucidation of very different mobilities in Co- and S-vacancy-doped cases, and observation of an abrupt temperaturedependent crossover to bulk Efros-Shklovskii variable-range hopping, accompanied by an unusual form of nonlinear Hall effect. Aspects of the results are interpreted with the aid of first-principles electronic structure calculations on both Co- and S-vacancy-doped FeS 2 . Furthermore, this work thus demonstrates unequivocal mitigation of the internal p-n junction in pyrite single crystals, with important implications for both future fundamental studies and photovoltaic devices

36 MATERIALS SCIENCE↗
DOE OSTI2025

PySolate : A Python‐Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform

PySolate is a Python‐based toolset that implements the continuous wavelet transform and nonlinear thresholding operations to denoise or designal seismic data, following Langston and Mousavi (2019). This filtering approach can remove microseismic noise to isolate intermediate‐period seismic signals that are key to enabling full‐waveform modeling and analysis of smaller‐magnitude regional events. This approach is best for the application to signals with frequency or time separation of signal and noise, in contrast to Fourier analysis, which is effective when signal and noise are separated in frequency. We demonstrate the Python toolset using the six announced Democratic People’s Republic of Korea declared nuclear tests, showing the effectiveness of isolating the seismic signal compared to standard bandpass filtering. In conclusion, we also demonstrate the ease of using the toolset with any Python processing tools.

Asia↗
DOE OSTI2020

Transient magnetic field diffusion considerations relevant to magnetically assisted indirect drive inertial confinement fusion

We report application of a magnetic field to an indirect drive inertial confinement fusion target requires diffusion of the field through the high-Z and electrically conducting Hohlraum. The onset of the external field generates eddy currents in the Hohlraum wall that result in (1) a reduction of the peak field at the capsule, (2) heating of the Hohlraum wall through Ohmic dissipation, and (3) wall movement due to the inward force from the eddy current interacting with the field. Heating of the wall causes an increase in blackbody radiation which can preheat the capsule and frozen deuterium–tritium fuel, while wall motion leads to potential misalignment of the lasers at the Hohlraum wall. Limiting these detrimental effects sets requirements on the tolerable magnitude of each effect. We present a nonlinear model for B-field diffusion through an infinitely long thin-walled cylinder with a temperature dependent resistivity, to show that a 15 μm thick wall of pure gold fails to meet these requirements. A new Hohlraum material made from an alloy of Au and Ta has a measured resistivity of ≥60 times that of Au and is shown with the nonlinear model to meet the requirements for magnetization. We compare the nonlinear model to simulations of the actual Hohlraum target using a finite element code which includes temperature-dependent Hohlraum resistivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Digital Miniature Cathode Ray Magnetometer

In this study, we introduce the concept and construction of an innovative Digital Miniature Cathode Ray Magnetometer designed for the precise detection of magnetic fields. This device addresses several limitations inherent to magnetic probes such as D.C. offset, nonlinearity, temperature drift, sensor aging, and the need for frequent recalibration, while capable of operating in a wide range of magnetic fields. The core principle of this device involves the utilization of a charged particle beam as the sensitivity medium. The system leverages the interaction of an electron beam with a scintillator material, which then emits visible light that is captured by an imager. The emitted scintillation light is captured by a CMOS sensor. This sensor not only records the scintillation light but also accurately determines the position of the electron beam, providing invaluable spatial information crucial for magnetic field mapping. The key innovation lies in the combination of electron beam projection, CMOS imager scintillation-based detection, and digital image signal processing. By employing this synergy, the magnetometer achieves remarkable accuracy, sensitivity and dynamic range. The precise position registration enabled by the CMOS sensor further enhances the device’s utility in capturing complex magnetic field patterns, allowing for 2D field mapping. In this work, the optimization of the probe’s performance is tailored for applications related to the characterization of insertion devices in light sources, including undulators.

Turqueti, Marcos↗
DOE OSTI2021

Understanding Self-Assembly and the Stabilization of Liquid/Liquid Interfaces: The Importance of Ligand Tail Branching and Oil-Phase Solvation

Organophosphorus-based ligands represent a versatile set of solvent extraction reagents whose chemical makeup plays an important role in extraction mechanism. We hypothesize that the branching of the extractant hydrophobic tail and its oil-phase solvation affect the liquid/liquid interfacial structure. Understanding the structure mediated adsorption and interfacial ordering becomes key in designing ligands with enhanced selectivity and efficiency for targeted extractions. We employed vibrational sum frequency generation spectroscopy and interfacial tension measurements to extract thermodynamic adsorption energies, map interfacial ordering, and rationalize disparate behaviors of model di-(2-ethylhexyl) phosphoric acid and dioctyl phosphoric acid ligands at the hexadecane water interface. With increased surface loading, ligands with branched hydrophobic tails formed stable interfaces at much lower concentrations than those observed for ligands with linear alkyl tails. The lack of an oil phase and associated solvation results in markedly different interfacial properties, and thus measurements made at air/liquid surfaces cannot be assumed to correlate with the processes occurring at buried liquid/liquid interfaces. Here, we attribute these differences in the surface mediated self-assembly to key variations in hydrophobic interactions and tail solvation taking place in the oil phase demonstrating that interactions in both the polar and nonpolar phases are essential to understand self-assembly and function.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hot Electron Scaling and Energy Coupling In Nonlinear Laser Plasma Interactions

Energy conversion from high power lasers to energetic hot electrons is a fundamental phenomenon in laser-plasma interactions. At laser intensities above a few times 10 14 W/cm 2 , nonlinear laser-plasma interactions lead to the generation of hot electrons with a broad energy distribution at typical temperatures of 10’s – 100’s kilo-electron-volt (keV). The fraction of laser energy transferred to hot electrons, their energy distribution and energy coupling efficiency to the targets are strongly affected by the laser intensity, wavelength and the plasma condition. Most investigations to date that are related to the fusion of high-energy-density laboratory plasmas (HEDLP) are carried out with relatively moderate laser intensity and lower laser wavelength to minimize hot electron generation, as electron preheating can degrade the fuel assembly. An alternative fusion scheme known as shock ignition (SI) has been proposed, requiring a high intensity spike pulse at the end of a fuel assembly phase to generate a strong shock to ignite the fuel. An initial shock pressure of 0.3 Gbar is required for ignition-scale targets using the SI scheme, requiring a relatively high on-target laser intensity of 5-10X10 15 W/cm 2 for the spike pulse. At such intensities, copious hot electrons can be produced by laser-plasma-instabilities (LPI), e.g., Stimulated Raman Scattering (SRS) and Two-Plasmon Decay (TPD). While very energetic electrons (>200 keV) could preheat the fuel, electrons with moderate energies may actually be beneficial for the SI scheme. Electrons in the 50-100 keV range can be stopped in the compressed high-density outer ablator layer leading to an increase in the ignitor shock strength and therefore enhancing overall efficiency in the SI scheme. Considering this importance of total energy and temperature of hot electrons, it is necessary to understand the LPI in the SI high intensity regime. Characterizing the hot electron source and energy coupling is key to investigating the viability of the SI concept. The overall goal of the HEDLP award was to perform a detailed study of the scaling of hot electron generation and energy coupling on high power laser systems, with intensity, wavelength, and target ablator material relevant to the nonlinear laser-plasma interaction at SI relevant conditions. This was a collaborative project between the Center for Energy Research at the University of California, San Diego (UCSD) and General Atomics. The experiment was performed at the Omega Laser Facility at the Laboratory for Laser Energetics (LLE) in the University of Rochester. Specific objectives of the work were to: understand the basic physics of laser-plasma interactions and instabilities at high laser intensities (up to 10 17 W/cm 2 ) and the effects of low-Z ablator materials and laser wavelengths (IR pulse at 1.054 µm versus UV pulse at 0.351 µm) and intensity scaling, fully characterize the resultant hot electron energy distribution, validate hot electron energy deposition via collisional and kinetic processes in the target and the induced shocks in support of electron-assisted SI concept.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems

This work proposes an extension of neural ordinary differential equations (NODEs) by introducing an additional set of ODE input parameters to NODEs. This extension allows NODEs to learn multiple dynamics specified by the input parameter instances. Our extension is inspired by the concept of parameterized ordinary differential equations, which are widely investigated in computational science and engineering contexts, where characteristics of the governing equations vary over the input parameters. We apply the proposed parameterized NODEs (PNODEs) for learning latent dynamics of complex dynamical processes that arise in computational physics, which is an essential component for enabling rapid numerical simulations for time-critical physics applications. For this, we propose an encoder-decoder-type framework, which models latent dynamics as PNODEs. We demonstrate the effectiveness of PNODEs with important benchmark problems from computational physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

LLNL FESP Theory Highlights: October 2024

I. Novikau, I. Y. Dodin, E. A. Startsev, I. Joseph, Quantum algorithms for simulating dissipative linear and nonlinear dynamics of plasmas. Invited talk at the 66th Annual Meeting of the APS Division of Plasma Physics, Atlanta, Georgia. Novikau I., Dodin I.Y., Startsev E.A., Encoding of linear kinetic plasma problems in quantum circuits via data compression, Journal of Plasma Physics. 2024;90(4):805900401, doi:10.1017/S0022377824000795. We propose an algorithm for encoding linear kinetic plasma problems in quantum circuits. The focus is on modelling electrostatic linear waves in a one-dimensional Maxwellian electron plasma. The waves are described by the linearized Vlasov–Ampère system with a spatially localized external current that drives plasma oscillations. This system is formulated as a boundary-value problem and cast in the form of a linear vector equation to be solved by using the quantum signal processing algorithm. The latter requires encoding of a matrix in a quantum circuit as a sub-block of a unitary matrix. We propose how to encode in a circuit in a compressed form and discuss how the resulting circuit scales with the problem size and the desired precision.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗
DOE OSTI2026

Collider-quality electron bunches from an all-optical plasma photoinjector

We present an approach for generating collider-quality electron bunches using a plasma photoinjector. The approach leverages recently developed techniques for the spatiotemporal control of laser pulses to produce a moving ionization front in a nonlinear plasma wave. The moving ionization front generates an electron bunch with a current profile that balances the longitudinal electric field of an electron beam-driven plasma wave, creating a uniform accelerating field across the bunch. Particle-in-cell (PIC) simulations of the ionization stage show the formation of an electron bunch with 220 pC charge and low emittance (ɛ 𝑥 = 171 nm rad, ɛ 𝑦 = 76 nm rad). Quasistatic PIC simulations of the acceleration stage show that the bunch is efficiently accelerated to 24 GeV over 2 m with a final energy spread of less than 1% and emittances of ɛ 𝑥 = 189 nm rad and ɛ 𝑦 = 80 nm rad. This high-quality electron bunch meets the requirements outlined by the Snowmass process for intermediate-energy colliders and compares favorably to the beam quality of proposed and existing accelerator facilities. The results establish the feasibility of plasma photoinjectors for future collider applications making a significant step toward the realization of high-luminosity, compact accelerators for particle physics research.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Statistical generic design of glass and optimization: Selective review on oxide glasses

Designing a single glass composition for a multidimensional property space is challenging, and the difficulty increases with the number of design criteria. Traditionally, the task is accomplished using multiple statistical models that describe the relationships between composition (C) and property (P) values, i.e., C-P models. Recently, the structure (S)-property (P) statistical modeling has emerged as a complementary approach. The S-P modeling approach has also been shown to be a preferred method for modeling glass properties, particularly when a small data set is available, such as in single-component studies, or when strong nonlinearities exist between composition and properties. The combined model package, C-S-P, implements the concept of generic glass design, i.e., designing glass for performance by first selecting a specific or optimized set of glass network structural groups using S-P models and then transferring the designed structures (genes) to a particular composition using C-S models. This article reviews a set of supporting cases from the previous C-S-P modeling studies of phosphate, silicate, and borosilicate glasses, which are relevant for many critical commercial applications. The methodology for developing the statistical C-S-P database is presented, enabling the application of P?S?C to achieve a generic glass design and optimization, targeting multiple design criteria for both performance and processing properties simultaneously.

Network structure↗