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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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NASA NTRS1973

Remote sensing in Iowa agriculture

The author has identified the following significant results. Results include the estimation of forested and crop vegetation acreages using the ERTS-1 imagery. The methods used to achieve these estimates still require refinement, but the results appear promising. Practical applications would be directed toward achieving current land use inventories of these natural resources. This data is presently collected by sampling type surveys. If ERTS-1 can observe this and area estimates can be determined accurately, then a step forward has been achieved. Cost benefit relationship will have to be favorable. Problems still exist in these estimation techniques due to the diversity of the scene observed in the ERTS-1 imagery covering other part of Iowa. This is due to influence of topography and soils upon the adaptability of the vegetation to specific areas of the state. The state mosaic produced from ERTS-1 imagery shows these patterns very well. Research directed to acreage estimates is continuing.

Mahlstede, J. P.↗

DOE OSTI2014

Single Cell Genomics and Transcriptomics for Unicellular Eukaryotes

Despite their small size, unicellular eukaryotes have complex genomes with a high degree of plasticity that allow them to adapt quickly to environmental changes. Unicellular eukaryotes live with prokaryotes and higher eukaryotes, frequently in symbiotic or parasitic niches. To this day their contribution to the dynamics of the environmental communities remains to be understood. Unfortunately, the vast majority of eukaryotic microorganisms are either uncultured or unculturable, making genome sequencing impossible using traditional approaches. We have developed an approach to isolate unicellular eukaryotes of interest from environmental samples, and to sequence and analyze their genomes and transcriptomes. We have tested our methods with six species: an uncharacterized protist from cellulose-enriched compost identified as Platyophrya, a close relative of P. vorax; the fungus Metschnikowia bicuspidate, a parasite of water flea Daphnia; the mycoparasitic fungi Piptocephalis cylindrospora, a parasite of Cokeromyces and Mucor; Caulochytrium protosteloides, a parasite of Sordaria; Rozella allomycis, a parasite of the water mold Allomyces; and the microalgae Chlamydomonas reinhardtii. Here, we present the four components of our approach: pre-sequencing methods, sequence analysis for single cell genome assembly, sequence analysis of single cell transcriptomes, and genome annotation. This technology has the potential to uncover the complexity of single cell eukaryotes and their role in the environmental samples.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Progressive construction of a parametric reduced‐order model for PDE‐constrained optimization

Summary An adaptive approach to using reduced‐order models (ROMs) as surrogates in partial differential equations (PDE)‐constrained optimization is introduced that breaks the traditional offline‐online framework of model order reduction. A sequence of optimization problems constrained by a given ROM is defined with the goal of converging to the solution of a given PDE‐constrained optimization problem. For each reduced optimization problem, the constraining ROM is trained from sampling the high‐dimensional model (HDM) at the solution of some of the previous problems in the sequence. The reduced optimization problems are equipped with a nonlinear trust‐region based on a residual error indicator to keep the optimization trajectory in a region of the parameter space where the ROM is accurate. A technique for incorporating sensitivities into a reduced‐order basis is also presented, along with a methodology for computing sensitivities of the ROM that minimizes the distance to the corresponding HDM sensitivity, in a suitable norm. The proposed reduced optimization framework is applied to subsonic aerodynamic shape optimization and shown to reduce the number of queries to the HDM by a factor of 4‐5, compared with the optimization problem solved using only the HDM, with errors in the optimal solution far less than 0.1%. Copyright © 2014 John Wiley & Sons, Ltd.

Zahr, Matthew J.↗

DOE OSTI2024

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes

Increasing evidence emerged for non-random spatial distributions for microbes, but the underlying processes resulting in microbial assemblage variation among and within Earth’s ecosystems is still lacking. For instance, some studies showed that the deterministic processes by habitat specialization are important, while other studies hold that bacterial communities are assembled by neutral forces. Here we examine the relative importance of deterministic and stochastic processes for bacterial communities from subsurface environments, as well as stream biofilm, lake water, lake sediment and soil using pyrosequencing of 16S rRNA gene. We show that there is a general pattern in phylogenetic signal in species niches across recent evolutionary time for all studied habitats, enabling us to infer the influences of community assembly processes from patterns of phylogenetic turnover in community composition. The phylogenetic dissimilarities among habitat types were significantly higher than within them, and the communities were clustered according to their original habitat types. For communities within habitat types, the highest phylogenetic turnover rate through space was observed in subsurface environments, followed by stream biofilm on mountainsides, whereas the sediment assemblages across regional scales showed the lowest turnover rate. Quantifying phylogenetic turnover as the deviation from a null expectation suggested that measured environmental variables imposed strong selection on bacterial communities for nearly all sample groups, and for three sample groups, that spatial distance reflects unmeasured environmental variables that impose selection, as opposed to spatial isolation. Such characterization of spatial and environmental variables proved essential for proper interpretation of partial mantel results based on observed beta diversity metrics. In summary, our results clearly indicate a dominant role of deterministic processes on bacterial assemblages and highlight that bacteria show strong habitat associations that have likely emerged through evolutionary adaptation.

Bacteria↗

DOE OSTI2024

Covalent adaptable polymer networks with CO 2 -facilitated recyclability

Cross-linked polymers with covalent adaptable networks (CANs) can be reprocessed under external stimuli owing to the exchangeability of dynamic covalent bonds. Optimization of reprocessing conditions is critical since increasing the reprocessing temperature costs more energy and even deteriorates the materials, while reducing the reprocessing temperature via molecular design usually narrows the service temperature range. Exploiting CO 2 gas as an external trigger for lowering the reprocessing barrier shows great promise in low sample contamination and environmental friendliness. Herein, we develop a type of CANs incorporated with ionic clusters that achieve CO 2 -facilitated recyclability without sacrificing performance. The presence of CO 2 can facilitate the rearrangement of ionic clusters, thus promoting the exchange of dynamic bonds. The effective stress relaxation and network rearrangement enable the system with rapid recycling under CO 2 while retaining excellent mechanical performance in working conditions. This work opens avenues to design recyclable polymer materials with tunable dynamics and responsive recyclability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

A high angular resolution survey of massive stars in Cygnus OB2: Results from the Hubble space telescope fine guidance sensors

We present results of a high angular resolution survey of massive OB stars in the Cygnus OB2 association that we conducted with the fine guidance sensor 1R (FGS1r) on the Hubble Space Telescope. FGS1r is able to resolve binary systems with a magnitude difference ΔV < 4 down to separations as small as 0.''01. The sample includes 58 of the brighter members of Cyg OB2, one of the closest examples of an environment containing a large number of very young and massive stars. We resolved binary companions for 12 targets and confirmed the triple nature of one other target, and we offer evidence of marginally resolved companions for two additional stars. We confirm the binary nature of 11 of these systems from complementary adaptive optics imaging observations. The overall binary frequency in our study is 22% to 26% corresponding to orbital periods ranging from 20 to 20,000 yr. When combined with the known short-period spectroscopic binaries, the results support the hypothesis that the binary fraction among massive stars is >60%. One of the new discoveries is a companion to the hypergiant star MT 304 = Cyg OB2-12, and future measurements of orbital motion should provide mass estimates for this very luminous star.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

SU-E-J-237: Real-Time 3D Anatomy Estimation From Undersampled MR Acquisitions

Recent developments made MRI guided radiotherapy feasible. Performing simultaneous imaging during fractions can provide information about changing anatomy by means of deformable image registration for either immediate plan adaptations or accurate dose accumulation on the changing anatomy. In 3D MRI, however, acquisition time is considerable and scales with resolution. Furthermore, intra-scan motion degrades image quality.In this work, we investigate the sensitivity of registration quality on imageresolution: potentially, by employing spatial undersampling, the acquisition timeof MR images for the purpose of deformable image registration can be reducedsignificantly.On a volunteer, 3D-MR imaging data was sampled in a navigator-gated manner, acquiring one axial volume (360×260×100mm{sup 3}) per 3s during exhale phase. A T1-weighted FFE sequence was used with an acquired voxel size of (2.5mm{sup 3}) for a duration of 17min. Deformation vector fields were evaluated for 100 imaging cycles with respect to the initial anatomy using deformable image registration based on optical flow. Subsequently, the imaging data was downsampled by a factor of 2, simulating a fourfold acquisition speed. Displacements of the downsampled volumes were then calculated by the same process.In kidneyliver boundaries and the region around stomach/duodenum, prominent organ drifts could be observed in both the original and the downsampled imaging data. An increasing displacement of approximately 2mm was observed for the kidney, while an area around the stomach showed sudden displacements of 4mm. Comparison of the motile points over time showed high reproducibility between the displacements of high-resolution and downsampled volumes: over a 17min acquisition, the componentwise RMS error was not more than 0.38mm.Based on the synthetic experiments, 3D nonrigid image registration shows little sensitivity to image resolution and the displacement information is preserved even when halving the resolution. This can be employed to greatly reduce image acquisition times for interventional applications in real-time. This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

A pipeline for targeted metagenomics of environmental bacteria

Background:Metagenomics and single cell genomics provide a window into the genetic repertoire of yet uncultivated microorganisms, but both methods are usually taxonomically untargeted. The combination of fluorescence in situ hybridization (FISH) and fluorescence activated cell sorting (FACS) has the potential to enrich taxonomically well-defined clades for genomic analyses. Methods:Cells hybridized with a taxon-specific FISH probe are enriched based on their fluorescence signal via flow cytometric cell sorting. A recently developed FISH procedure, the hybridization chain reaction (HCR)-FISH, provides the high signal intensities required for flow cytometric sorting while maintaining the integrity of the cellular DNA for subsequent genome sequencing. Sorted cells are subjected to shotgun sequencing, resulting in targeted metagenomes of low diversity. Results: Pure cultures of different taxonomic groups were used to (1) adapt and optimize the HCR-FISH protocol and (2) assess the effects of various cell fixation methods on both the signal intensity for cell sorting and the quality of subsequent genome amplification and sequencing. Best results were obtained for ethanol-fixed cells in terms of both HCR-FISH signal intensity and genome assembly quality. Our newly developed pipeline was successfully applied to a marine plankton sample from the North Sea yielding good quality metagenome assembled genomes from a yet uncultivated flavobacterial clade. Conclusions: With the developed pipeline, targeted metagenomes at various taxonomic levels can be efficiently retrieved from environmental samples. The resulting metagenome assembled genomes allow for the description of yet uncharacterized microbial clades.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Management of HL deposits for the D and D of UP1 reprocessing plant - retrieval and treatment scenarios - 15295

Built in 1958 on the Marcoule CEA site, the UP1 facility, was the 1. French industrial (500 t U / year) reprocessing plant based on the PUREX process. The plant, which has stopped operation in 1997, constitutes with its auxiliary workshop (vitrification workshop, glass canister storage), one of the largest and most challenging decommissioning project in France. In about 40 years of operation, various type of fuels elements such as metallic uranium, U-Al fuel rods, Phenix breeder elements or PWR fuel have been reprocessed, thereby requiring several plant and process adaptations. Resulting from these complex process chemistry and operation history, significant fouling of the chemical plant circuits and components has occurred. The fission product (FP) concentration process is particularly concerned. Preliminary investigation performed in 2010 in the evaporator's feeding tanks revealed the presence of significant amounts of sludge and dose rates as high as 250 Gy/h. Therefore a thorough investigation campaign, including visual inspection, volume quantification, deposits sampling, and radiological characterization of the components of this workshop has been initiated in 2013. Chemical analysis performed so far show that the solids are mainly composed of zirconium phosphates, 'MoZr' compounds and nitrate salt precipitates. But the presence of insoluble fines arising from the dissolution workshop and organic residues resulting from the TBP decomposition has also been evidenced in some of the tanks. The numerous constraints associated with the management of such highly active sludge, with Cs-137 specific activity ranging from 1 to 10 GBq/g, and a complex physico-chemical composition, lead CEA to investigate the implementation of an in situ conditioning treatment able to produce a waste package complying with existing evacuation routes and/or on-site storage facilities. The full paper presents an overview of the UP1 D and D project and then focuses on the possible dismantling scenarios for the FP concentration workshop, including the evaluation of different strategies for the highly active deposits management. The investigations and deposits characterization program will be developed so as the sampling methodologies that has been specifically tuned. In the light of the best actual knowledge of the deposits properties, the recovery and conditioning treatment scenarios will be exposed, considering, as a case study, the development of a specific vitrification tool to be implemented In Situ and specifically designed to match the requirements and constraints of the D and D project: adequately dimensioned, compact, flexible with respect to the feed composition, for a limited duration of use and designed to be dismantled. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Sparse-view proton computed tomography using modulated proton beams

Purpose: Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT. Methods: Proton projection images were acquired using the modulated proton beams and the EBT2 film as an intensity detector. Four electron-density cylinders representing normal soft tissues and bone were used as imaged object and scanned at 40 views that are equally separated over 360°. Digitized film images were converted to water-equivalent thickness by use of an empirically derived conversion curve. For improving the image quality, a deconvolution-based image deblurring with an empirically acquired point spread function was employed. They have implemented iterative image reconstruction algorithms such as adaptive steepest descent-projection onto convex sets (ASD-POCS), superiorization method–projection onto convex sets (SM-POCS), superiorization method–expectation maximization (SM-EM), and expectation maximization-total variation minimization (EM-TV). Performance of the four image reconstruction algorithms was analyzed and compared quantitatively via contrast-to-noise ratio (CNR) and root-mean-square-error (RMSE). Results: Objects of higher electron density have been reconstructed more accurately than those of lower density objects. The bone, for example, has been reconstructed within 1% error. EM-based algorithms produced an increased image noise and RMSE as the iteration reaches about 20, while the POCS-based algorithms showed a monotonic convergence with iterations. The ASD-POCS algorithm outperformed the others in terms of CNR, RMSE, and the accuracy of the reconstructed relative stopping power in the region of lung and soft tissues. Conclusions: The four iterative algorithms, i.e., ASD-POCS, SM-POCS, SM-EM, and EM-TV, have been developed and applied for proton CT image reconstruction. Although it still seems that the images need to be improved for practical applications to the treatment planning, proton CT imaging by use of the modulated beams in sparse-view sampling has demonstrated its feasibility.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Determination of the magnetocaloric entropy change by field sweep using a heat flux setup

We report on a simple setup using a heat flux sensor adapted to a Quantum Design Physical Property Measurement System to determine the magnetocaloric entropy change (ΔS). The major differences for the existing setups are the simplicity of this assembly and the ease to obtain the isothermal entropy change either by a field sweep or a temperature sweep process. We discuss the use of these two processes applied to Gd and Gd{sub 5}Ge{sub 2}Si{sub 2} samples. The results are compared to the temperature sweep measurements and they show the advantages of this setup and of the field sweep procedure. We found a significant reduction of ΔS and on the refrigerating cooling power (RCP) at low field changes in a field sweep process when the sample is not driven to the same initial state for each temperature. We show that the field sweep process without any measuring protocol is the only correct way to experimentally determine ΔS and RCP for a practical regenerative refrigerator.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics

Abstract Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F ST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout ( Oncorhynchus mykiss ) in the Columbia River Basin, USA . Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes ( N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

Hand, Brian K.↗

DOE OSTI2019

Rejecting cosmic background for exclusive charged current quasi elastic neutrino interaction studies with Liquid Argon TPCs; a case study with the MicroBooNE detector

Cosmic ray (CR) interactions can be a challenging source of background for neutrino oscillation and cross-section measurements in surface detectors. We present methods for CR rejection in measurements of charged-current quasielastic-like (CCQE-like) neutrino interactions, with a muon and a proton in the final state, measured using liquid argon time projection chambers (LArTPCs). Using a sample of cosmic data collected with the MicroBooNE detector, mixed with simulated neutrino scattering events, a set of event selection criteria is developed that produces an event sample with minimal contribution from CR background. Depending on the selection criteria used a purity between 50% and 80% can be achieved with a signal selection efficiency between 50% and 25%, with higher purity coming at the expense of lower efficiency. While using a specific dataset from the MicroBooNE detector and selection criteria values optimized for CCQE-like events, the concepts presented here are generic and can be adapted for various studies of exclusive v μ CCQE interactions in LArTPCs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Fast response of fungal and prokaryotic communities to climate change manipulation in two contrasting tundra soils

Climate models predict substantial changes in temperature and precipitation patterns across Arctic regions, including increased winter precipitation as snow in the near future. Soil microorganisms are considered key players in organic matter decomposition and regulation of biogeochemical cycles. However, current knowledge regarding their response to future climate changes is limited. Here, we explore the short-term effect of increased snow cover on soil fungal, bacterial and archaeal communities in two tundra sites with contrasting water regimes in Greenland. In order to assess seasonal variation of microbial communities, we collected soil samples four times during the plant-growing season. The analysis revealed that soil microbial communities from two tundra sites differed from each other due to contrasting soil chemical properties. Fungal communities showed higher richness at the dry site whereas richness of prokaryotes was higher at the wet tundra site. We demonstrated that fungal and bacterial communities at both sites were significantly affected by short-term increased snow cover manipulation. Our results showed that fungal community composition was more affected by deeper snow cover compared to prokaryotes. The fungal communities showed changes in both taxonomic and ecological groups in response to climate manipulation. However, the changes were not pronounced at all sampling times which points to the need of multiple sampling in ecosystems where environmental factors show seasonal variation. Further, we showed that effects of increased snow cover were manifested after snow had melted. We demonstrated rapid response of soil fungal and bacterial communities to short-term climate manipulation simulating increased winter precipitation at two tundra sites. In particular, we provide evidence that fungal community composition was more affected by increased snow cover compared to prokaryotes indicating fast adaptability to changing environmental conditions. Since fungi are considered the main decomposers of complex organic matter in terrestrial ecosystems, the stronger response of fungal communities may have implications for organic matter turnover in tundra soils under future climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.

ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1971

Methodologies for optimal resource allocation to the national space program and new space utilizations. Volume 2: Resource allocation and smoothing model, programmer's manual

Appendixes are presented that provide model input requirements, a sample case, flow charts, and a program listing. At the beginning of each appendix, descriptive details and technical comments are provided to indicate any special instructions applicable to the use of that appendix. In addition, the program listing includes comment cards that state the purpose of each subroutine in the complete program and describe operations performed within that subroutine. The input requirements includes details on the many options that adapt the program to the specific needs of the analyst for a particular problem.

Source record↗

DOE OSTI2026

Ultrafast Laser Welding and Terahertz Time-domain Spectroscopy of Soda Lime Silicate Glass

Joining and welding techniques of similar and dissimilar materials have reached their limits due to the inflexibility of adapting dielectric materials, e.g., glasses and ceramics, reproducibility for transparent materials, and cycle process time. The ability to join pieces of glasses using laser irradiation allows rapid processing of vacuum insulating glass (VIG) for a widening range of commercial energy-efficient applications. We have used a 1064-nm laser wavelength with 15 picoseconds pulse width and a 155-kHz repetition rate to weld commercial plate glass pieces. The welded samples were characterized via x-ray fluorescence (XRF), time-of-flight secondary ion mass spectrometry (TOF–SIMS), polarimetry, and terahertz time-domain spectroscopy (THz-TDS) to determine the integrity of the weld and chemical changes in the welded areas. Our data shows no significant changes in glass chemistry and structure on average over nano- to micro-scales occurred from the welding process within the limits of the characterization tools. Our results demonstrate successful welding of glass plates without significant changes in the glass chemistry, structure, or properties in the laser-modified region or strains in the bulk glass.

Matthies, Kathleen [ORNL] (ORCID:0009000213135441)↗