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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

cuZ-Checker: A GPU-Based Ultra-Fast Assessment System for Lossy Compressions

Lossy compression is becoming an indispensable technique for the success of today's extreme-scale high-performance computing projects that produce vast volumes of data during scientific simulations or instrument data acquisitions. Comprehensively understanding the compression quality and performance of different lossy compressors is critical to selecting the best-fit compressors and using them properly and efficiently in practice. A few lossy compression assessment tools (e.g., Z-checker) have been developed, but none of them support the execution in a GPU environment. This is a significant gap because many recent extreme-scale applications and lossy compressors (e.g., cuSZ) can run entirely within GPUs. In this work, we develop an efficient lossy compression measuring system (called cuZ-Checker) on the GPU platform, which aims to perform the lossy compression quality and performance assessment completely within the GPU environment. Our contribution is threefold. (1) We develop a novel GPU-based lossy compression measuring framework using a computation pattern-based design approach. This approach classifies the computing-intensive metrics into three categories based on their patterns which creates large opportunities for kernel fusion and data reuse. (2) For each pattern in cuZ-Checker, we develop a CUDA kernel and provide fine-grained optimizations to boost its performance. (3) We thoroughly evaluate our cuZ-checker on a V100 GPU using four real-world scientific application datasets. Experiments show that cuZ-Checker can significantly accelerate the overall lossy compression assessment performance by 23X similar to 31X compared with the OpenMP-based multithreading CPU performance. To the best of our knowledge, this is the first lossy compression measuring system designed for GPU devices.

GPU↗
DOE OSTI2019

Final Report – Cooperative Research and Development Agreement between National Energy Technology Laboratory and Oxergy, Inc.

The NETL Raman Gas Analyzer (RGA) has been demonstrated to have an extremely fast response (<1 second) multi-gas analysis capability. All but the noble gases are Raman active, although the Raman interaction is weak. The RGA uses a reflectively lined capillary as the optical cell, providing both a small sample volume for fast gas exchange, and a much greater Raman signal collection than traditional instrument configurations. This allows very fast measurement of fuel gases (hydrogen, methane, ethane, propane) as well as other common industrial gases (carbon monoxide, carbon dioxide, nitrogen, oxygen, and water). This provides a new enabling technology for faster, smarter process control based on the chemical composition of the gases in the process – including improved fuel flexibility and efficiency for power generation systems. Research and development up to 2016 resulted in the construction of two field prototypes of the NETL RGA, which has been in applied to various laboratory applications for testing. The results of the testing have been used to improve the RGA design, with the intent to support technology transfer. The quality of the optical capillary used in the RGA is critical to its performance, and prior work at NETL produced a few optical capillaries superior to those commercially available. The production of high optical quality capillaries, however, was inconsistent in its results. With the support of the DOE Office of Technology Transitions, through the Technology Commercialization Fund program, this project was undertaken to address this commercialization barrier and to also evaluate the possible application of Raman gas analysis to a supercritical water gasification process being developed by Oxergy Inc. Oxergy, a small business located in Fairbanks, Alaska, is developing ultra-compact thermochemical reaction devices built with advanced manufacturing processes. Chief Technology Officer Jonathan Kamler holds the (pending) patent to Oxergy’s core reactor technology. Oxergy maintains wet-lab and combustion-lab space at the University of Alaska Fairbanks Center for Sustainable Living in Palmer, Alaska, where Mr. Kamler operates a pilot-scale, supercritical water gasification system designed and built by Oxergy. Mr. Kamler also operates an All Powers Labs Power Pallet gasifier coupled to a 10KW electrical generator as a dry biomass test platform at the Palmer facility. Both systems are suitable for real-world, collaborative testing of Raman gas analysis applications. The objectives of the CRADA include making the production of high-quality optical capillaries consistent and high yield, investigating other options for optical waveguides, and testing the capillaries for measurements in supercritical water gasification. Success on these objectives will support commercialization of both the RGA and supercritical water gasification technologies. Through the work performed on this project, a new apparatus was constructed and optimized to provide consistent production of high-quality optical capillaries. Several thick-walled capillaries were coated using this apparatus and shipped to Oxergy in September 2018 for testing in both dry gasification and supercritical water gasification process monitoring applications at University of Alaska Fairbanks facilities in Palmer. The strong earthquake near Anchorage and Palmer in November 2018 caused extensive damage and closure of the facilities used by Oxergy, preventing Oxergy from proceeding with experimental testing before the end of the project; the facility has been closed indefinitely. Earthquake damage prohibited the completion of all the project objectives prior to the end of the project. However, significant progress was made toward addressing a core technology commercialization barrier. The largest and most mature potential market for Raman gas analysis is its use in analytical instruments, which require sensitivity and low detection limits, and Oxergy’s market research found that market inertia is a barrier to commercial success in this market. Although NETL’s innovations in capillary coating have substantially improved Raman gas analysis capability, the likely market is expected to be niche applications that value the fast detection of real-time changes in gas composition.

Chorpening, Benjamin↗
DOE OSTI2024

Establishing a clostridia foundry for biosystems design by integrating computational modeling, systems-level analyses, and cell-free engineering technologies (Final Report)

Rapid population growth, a rise in global living standards, and economic competitiveness have intensified the need for sustainable, low-cost biofuels and bioproducts production. Industrial biotechnology using microbial cell factories – and waste and/or renewable feedstocks – is one of the most attractive approaches for addressing this need, particularly when large-scale chemical synthesis is untenable. Unfortunately, designing, building, and optimizing biosynthetic pathways in cells remains a complex challenge. With support from the Department of Energy, we worked to address this challenge in a new interdisciplinary venture that established the world’s first clostridial Foundry for Biosystems Design (cBioFAB). Working both in vitro (cell-free) and in vivo, the goal of this project was to interweave and advance state-of-the-art computational modeling, genome editing, omics measurements, systems-biology analyses, and cell-free technologies to expand the set of platform organisms that meet DOE bioenergy goals. Specifically, we manufactured fuel and chemical intermediates via existing and de novo pathways. This report covers the outcomes of our research project.

09 BIOMASS FUELS↗
DOE OSTI2025

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗
DOE OSTI2016

Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.

Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often been perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.

25 ENERGY STORAGE↗
DOE OSTI2016

Porous Nanomaterials for Ultrabroadband Omnidirectional Anti‐Reflection Surfaces with Applications in High Concentration Photovoltaics

Materials for nanoporous coatings that exploit optimized chemistries and self‐assembly processes offer capabilities to reach ≈98% transmission efficiency and negligible scattering losses over the broad wavelength range of the solar spectrum from 350 nm to 1.5 µm, on both flat and curved glass substrates. These nanomaterial anti‐reflection coatings also offer wide acceptance angles, up to ±40°, for both s‐ and p‐polarization states of incident light. Carefully controlled bilayer films have allowed for the fabrication of dual‐sided, gradient index profiles on plano‐convex lens elements. In concentration photovoltaics platforms, the resultant enhancements in the photovoltaics efficiencies are ≈8%, as defined by experimental measurements on systems that use microscale triple‐junction solar cells. These materials and their applications in technologies that require control over interface reflections have the potential for broad utility in imaging systems, photolithography, light‐emitting diodes, and display technologies.

Yao, Yuan↗
DOE OSTI2026

Single-Particle Isotopic Analysis Using the Liquid Sampling-Atmospheric Pressure Glow Discharge Microplasma Coupled to an Orbitrap Mass Spectrometer

Isotope ratio (IR) determinations on individual particles can provide valuable information relative to the sample, including processing and dating, which could be valuable to geological and nuclear material analysis communities. In comparison to “bulk” measurements, in which all particle information is lost and homogenized within a sample, “particle” measurements allow for fingerprinting and can provide unique insights related to the sample’s nano- and micro- compositions. Furthermore, the complex nature of particles, with potential isobaric interferences from either the matrix or other elements within the same particle, poses a significant analytical challenge for conventional mass spectrometry platforms employed for elemental analysis due to their limited mass resolution. Presented here is the first demonstration of an ultrahigh resolution method for single particle (SP) isotopic analysis using the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled to an Orbitrap mass spectrometer and FTMS Booster X2T acquisition/processing system. For proof of concept, well-characterized CeO 2 microparticles with a nominal diameter of 1.0 μm were analyzed at a mass resolution of ∼330,000. Important instrumental parameters were optimized to enable the detection of single particles. The 142 Ce/ 140 Ce ratio of individual particles and the population average were determined and compared to an SP inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) analysis. The isotopic accuracy and precision were determined by two methods and found to be in good agreement with the SP-ICP-TOF-MS method, with the linear regression slope method providing a more accurate ratio, showing a ∼1.4% relative difference from the ratio determined from a particle digest. The encouraging performance of the method was further supported by a determined detection limit of 2.9 fg ( 142 Ce). The developed method is anticipated to overcome many of the challenges posed by isobaric interferences encountered in conventional mass spectrometry techniques when analyzing real-world samples for particle isotopic composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Gigahertz-frequency acousto-optic phase modulation of visible light in a CMOS-fabricated photonic circuit

Optical phase modulators operating at visible wavelengths are essential components for photonic technologies such as those for quantum control, communications, and laser ranging. However, they remain challenging to implement in scalable, integrated platforms capable of handling high optical powers. Here we present a visible-light, gigahertz-frequency acousto-optic phase modulator, fabricated on a 200-mm wafer in a volume CMOS foundry, that supports greater than 500 mW of optical power at 730 nm. The device combines a piezoelectric transducer and a photonic waveguide within a single, wavelength-scale structure that confines both a propagating optical mode and an electrically excitable breathing-mode mechanical resonance. By tuning the device’s geometry to optimize the optomechanical interaction, we achieve modulation depths up to 4.85 rad with 80 mW of applied microwave power at 2.31 GHz in a 2-mm-long device. This corresponds to resonant modulation figures of merit of V π = 1.32V and V π ⋅ L = 0.26V cm. To our knowledge, this is the lowest V π ever demonstrated in any acousto-optic phase modulator and represents a 15-fold reduction in V π and a 100-fold reduction in required microwave power relative to state-of-the-art modulators with high visible-wavelength power handling commonly employed in quantum control systems.

Freedman, Jacob M. [Univ. of Arizona, Tucson, AZ (↗
DOE OSTI2023

Evaluating performance and portability of high-level programming models: Julia, Python/Numba, and Kokkos on exascale nodes

We explore the performance and portability of the high-level programming models: the LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) nodes: AMD Epyc CPUs and MI250X graphical processing units (GPUs) on Frontier’s test bed Crusher system and Ampere’s Arm-based CPUs and NVIDIA’s A100 GPUs on the Wombat system at the Oak Ridge Leadership Computing Facilities. We compare the default performance of a hand-rolled dense matrix multiplication algorithm on CPUs against vendor-compiled C/OpenMP implementations, and on each GPU against CUDA and HIP. Rather than focusing on the kernel optimization per-se, we select this naive approach to resemble exploratory work in science and as a lower-bound for performance to isolate the effect of each programming model. Julia and Kokkos perform comparably with C/OpenMP on CPUs, while Julia implementations are competitive with CUDA and HIP on GPUs. Performance gaps are identified on NVIDIA A100 GPUs for Julia’s single precision and Kokkos, and for Python/Numba in all scenarios. We also comment on half-precision support, productivity, performance portability metrics, and platform readiness. We expect to contribute to the understanding and direction for high-level, high-productivity languages in HPC as the first-generation exascale systems are deployed.

Godoy, William↗
DOE OSTI2015

Non‐invasive, whole‐plant imaging of chloroplast movement and chlorophyll fluorescence reveals photosynthetic phenotypes independent of chloroplast photorelocation defects in chloroplast division mutants

Summary Leaf chloroplast movement is thought to optimize light capture and to minimize photodamage. To better understand the impact of chloroplast movement on photosynthesis, we developed a technique based on the imaging of reflectance from leaf surfaces that enables continuous, high‐sensitivity, non‐invasive measurements of chloroplast movement in multiple intact plants under white actinic light. We validated the method by measuring photorelocation responses in Arabidopsis chloroplast division mutants with drastically enlarged chloroplasts, and in phototropin mutants with impaired photorelocation but normal chloroplast morphology, under different light regimes. Additionally, we expanded our platform to permit simultaneous image‐based measurements of chlorophyll fluorescence and chloroplast movement. We show that chloroplast division mutants with enlarged, less‐mobile chloroplasts exhibit greater photosystem II photodamage than is observed in the wild type, particularly under fluctuating high levels of light. Comparison between division mutants and the severe photorelocation mutant phot1‐5 phot2‐1 showed that these effects are not entirely attributable to diminished photorelocation responses, as previously hypothesized, implying that altered chloroplast morphology affects other photosynthetic processes. Our dual‐imaging platform also allowed us to develop a straightforward approach to correct non‐photochemical quenching ( NPQ ) calculations for interference from chloroplast movement. This correction method should be generally useful when fluorescence and reflectance are measured in the same experiments. The corrected data indicate that the energy‐dependent ( qE ) and photoinhibitory ( qI ) components of NPQ contribute differentially to the NPQ phenotypes of the chloroplast division and photorelocation mutants. This imaging technology thus provides a platform for analyzing the contributions of chloroplast movement, chloroplast morphology and other phenotypic attributes to the overall photosynthetic performance of higher plants.

Dutta, Siddhartha↗
DOE OSTI2016

Image Processing Occupancy Sensor

The Image Processing Occupancy Sensor, or IPOS, is a novel sensor technology developed at the National Renewable Energy Laboratory (NREL). The sensor is based on low-cost embedded microprocessors widely used by the smartphone industry and leverages mature open-source computer vision software libraries. Compared to traditional passive infrared and ultrasonic-based motion sensors currently used for occupancy detection, IPOS has shown the potential for improved accuracy and a richer set of feedback signals for occupant-optimized lighting, daylighting, temperature setback, ventilation control, and other occupancy and location-based uses. Unlike traditional passive infrared (PIR) or ultrasonic occupancy sensors, which infer occupancy based only on motion, IPOS uses digital image-based analysis to detect and classify various aspects of occupancy, including the presence of occupants regardless of motion, their number, location, and activity levels of occupants, as well as the illuminance properties of the monitored space. The IPOS software leverages the recent availability of low-cost embedded computing platforms, computer vision software libraries, and camera elements.

Source record↗
DOE OSTI2015

Advanced Code for Photocathode Design

The Phase I activity demonstrated that PhotoQE could be upgraded and modified to allow input using a graphical user interface. Specific calls to platform-dependent (e.g. IMSL) function calls were removed, and Fortran77 components were rewritten for Fortran95 compliance. The subroutines, specifically the common block structures and shared data parameters, were reworked to allow the GUI to update material parameter data, and the system was targeted for desktop personal computer operation. The new structures overcomes the previous rigid and unmodifiable library structures by implementing new, materials library data sets and repositioning the library values to external files. Material data may originate from published literature or experimental measurements. Further optimization and restructuring would allow custom and specific emission models for beam codes that rely on parameterized photoemission algorithms. These would be based on simplified and parametric representations updated and extended from previous versions (e.g., Modified Fowler-Dubridge, Modified Three-Step, etc.).

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Discovery Science and Inertial Fusion Energy Research at the Jupiter Laser Facility (Research Performance Progress Report)

The goal of this project is to provide operational support to run the Jupiter Laser Facility within the LaserNetUS network to achieve the following four objectives: • Develop new science, techniques, and platforms for discovery science and IFE research, in partnership with academia, other LaserNetUS nodes, and the greater community. • Advance the development of secondary sources of photons and particles for applications relevant to discovery science and IFE; • Serve as a testbed for new laser, optical, target, and diagnostic capabilities that will advance IFE; • Attract, train, and retain talent in high-energy-density and laser science that will be essential in furthering development of IFE, and help build new collaborations between national laboratory and academic researchers. We have accomplished our four objectives by: • Providing access to the three JLF platforms (Titan, Janus, and COMET) to LaserNetUS users after their proposals have been independently reviewed and ranked by the LaserNetUS PRP; • Providing expertise and technical capabilities to support focused science research thrusts at the facility; • Promoting and maintaining technical relationships and collaborations with other members of the LaserNetUS community to nurture and grow the discovery science and IFE workforce— especially students and early career scientists—on LaserNetUS facilities. • Augmenting JLF with specific improvements while coordinating efforts with LLNL organizations and collaborators to provide users with optimal laser, target, and diagnostic resources to help them maximize technical impact.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Potential for Applying Continuous Directed Evolution to Plant Enzymes: An Exploratory Study

Plant evolution has produced enzymes that may not be optimal for maximizing yield and quality in today’s agricultural environments and plant biotechnology applications. By improving enzyme performance, it should be possible to alleviate constraints on yield and quality currently imposed by kinetic properties or enzyme instability. Enzymes can be optimized more quickly than naturally possible by applying directed evolution, which entails mutating a target gene in vitro and screening or selecting the mutated gene products for the desired characteristics. Continuous directed evolution is a more efficient and scalable version that accomplishes the mutagenesis and selection steps simultaneously in vivo via error-prone replication of the target gene and coupling of the host cell’s growth rate to the target gene’s function. However, published continuous systems require custom plasmid assembly, and convenient multipurpose platforms are not available. We discuss two systems suitable for continuous directed evolution of enzymes, OrthoRep in Saccharomyces cerevisiae and EvolvR in Escherichia coli, and our pilot efforts to adapt each system for high-throughput plant enzyme engineering. To test our modified systems, we used the thiamin synthesis enzyme THI4, previously identified as a prime candidate for improvement. Our adapted OrthoRep system shows promise for efficient plant enzyme engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The Model System Saccharomyces cerevisiae Versus Emerging Non-Model Yeasts for the Production of Biofuels

Microorganisms are effective platforms for the production of a variety of chemicals including biofuels, commodity chemicals, polymers and other natural products. However, deep cellular understanding is required for improvement of current biofuel cell factories to truly transform the Bioeconomy. Modifications in microbial metabolic pathways and increased resistance to various types of stress caused by the production of these chemicals are crucial in the generation of robust and efficient production hosts. Recent advances in systems and synthetic biology provide new tools for metabolic engineering to design strategies and construct optimal biocatalysts for the sustainable production of desired chemicals, especially in the case of ethanol and fatty acid production. Yeast is an efficient producer of bioethanol and most of the available synthetic biology tools have been developed for the industrial yeast Saccharomyces cerevisiae. Non-conventional yeast systems have several advantageous characteristics that are not easily engineered such as ethanol tolerance, low pH tolerance, thermotolerance, inhibitor tolerance, genetic diversity and so forth. Currently, synthetic biology is still in its initial steps for studies in non-conventional yeasts such as Yarrowia lipolytica, Kluyveromyces marxianus, Issatchenkia orientalis and Pichia pastoris. Therefore, the development and application of advanced synthetic engineering tools must also focus on these underexploited, non-conventional yeast species. Herein, we review the basic synthetic biology tools that can be applied to the standard S. cerevisiae model strain, as well as those that have been developed for non-conventional yeasts. In addition, we will discuss the recent advances employed to develop non-conventional yeast strains that are efficient for the production of a variety of chemicals through the use of metabolic engineering and synthetic biology.

09 BIOMASS FUELS↗
DOE OSTI2015

Sodium silicate treatment for uranium (vi) bearing groundwater systems at f/h area at savannah river site - 15709

The Savannah River Site (SRS) was one of the most significant manufacturing facilities during the Cold War era for producing nuclear materials. At the end of the Cold War, the Site's mission changed to support the environmental restoration of the Site due to over six decades of research, development, and production of nuclear weapons. Currently SRS is a major hazardous waste management facility responsible for nuclear materials storage, and remediation of contaminated soil and groundwater from radionuclides. This research focuses on controlling the mobilization of the contaminants, specifically uranium (VI) located in groundwater plumes at the Site's F/H Area Seepage Basin, where approximately 1.8 billion gallons of hazardous waste were deposited. Objective: To evaluate the potential use of sodium silicate for uranium removal from the aqueous phase, as well as to restore the pH of the treatment zone. Adding sodium silicate increases the pH of the treatment zone and uranium precipitation is achieved, therefore immobilizing the contaminant. Through a series of experiments the optimal concentration of sodium silicate was investigated. Part 1: An experiment was conducted in order to determine the effect of sodium silicate on the pH of a solution containing Savannah River Site soil and synthetic groundwater replicated after the Site's natural groundwater composition. Each sample was spiked with the appropriate volume from the sodium silicate stock solution in order to achieve final desired sodium silicate concentrations of 10, 20, 40,50,60,70, and 80 parts per million. The samples were placed on a platform shaker for three days during which pH readings were collected in regular intervals to determine which silicate concentration produced a pH in the neutral range (6 > pH < 8). Part 2: A sequential experiment was conducted specifically using 40 and 50 ppm of sodium silicate with Savannah River Site soil, synthetic groundwater, and 0.5 ppm of uranium (VI), in order to investigate the removal of uranium in the aqueous phase via precipitation. Samples were extracted and categorized into a filtered and non-filtered control group. Each sample was diluted 1:20 with 1% nitric acid and analyzed using the Kinetic Phosphorescence Analyzer (KPA) in order to measure uranium concentrations in the supernatant. By measuring the concentration of uranium in the supernatant the percent removal is obtained for the comparison between the filtered and non-filtered samples, revealing the amount of uranium precipitation that occurred for each silicate concentration. Results: A sodium silicate concentration of between 40-50 ppm proved ideal for achieving uranium precipitation and creating a circum-neutral pH environment in the aqueous phase. 50 ppm achieved the larger percent of uranium precipitation with a range of 30-50% removal for the filtered samples and between 60-95% removal for the non-filtered samples. A large difference between the removal of filtered and non- filtered samples from the same day was observed for both sodium silicate concentrations tested, indicating that there is a considerable amount of uranium species retained in the filter. The addition of sodium silicate proved effective in the removal of uranium precipitation from the aqueous phase. Future work: Determine potential re-solubilization of uranium concentrations; Examine mineralogy and surface morphology of dried precipitate using XRD and SEM/EDS.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Smart Energy Storage Integration and Management Platform for Buildings (SESIMP-B)

This project involved the design, development, and testing of a commercial smart service panel. It includes an innovative AI-driven control method to manage smart functions of the panel and a technical-economic feasibility assessment for enhancing building energy resilience and grid-edge technology integration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Ultra‐Flexible Pixelated Perovskite Photodetectors Enabled by Honeycomb Polymer Grids for High‐Resolution Imaging

Abstract A nature‐inspired fabrication method based on a photolithography‐free flexible polymer grid is reported for high‐resolution pixelation of perovskite photodiode arrays with exceptional mechanical ductility and a morphology resembling that of natural compound eyes. The resulting pixelated perovskite photosensitive layer has a ≈1 µm pixel size with 2000 Pixels per inch (PPI) resolution when fully assembled as a photodetector array, delivering a detectivity of >10 13 Jones while providing cross‐talk free imaging. Using a polymer grid effectively releases stress on the perovskite platform, greatly increasing the mechanical agility of the otherwise brittle perovskite film. This novel fabrication methodology and device design offer new possibilities for applications in robotics, biomedical imaging, and virtual and augmented reality.

Zheng, Ding [Department of Chemistry and the Mater↗