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At least 163 records · Page 9

Acoustic mapping by picosecond ultrasonics for elastic property measurement: Experimental demonstration on a TRISO fuel compact

Picosecond ultrasonics has been demonstrated on a tristructural isotropic (TRISO) fuel compact to measure the elastic properties of each compact layer. This technique utilizes an ultrashort pump laser pulse to excite vibrations in a gold transducer film covering the surface of each component and a second probe laser pulse to record the resulting acoustic strain induced change in optical reflectance. From the damping of this film vibration, the acoustic reflection coefficient, which couples the elastic properties of the transducer film and the sample, can be obtained, enabling a calculation of the sample’s acoustic velocity and elastic modulus. Overall, results obtained from this method are consistent with known values of elastic moduli, namely that the SiC coating is the stiffest component of the compact while the carbonaceous matrix is the most compliant. Nanoindentation was conducted as a benchmark technique on the same sample and shows satisfactory agreement with the results of picosecond ultrasonics. Compared to other methods like nanoindentation, picosecond ultrasonics is multimodal with a capability of measuring several key properties simultaneously and has potentials to be coupled into optical fibers for remote sensing. Thus, these demonstration measurements reveal the methodology to be a promising candidate for in-situ and high-throughput optical characterizations of nuclear materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Identification and demonstration of roGFP2 as an environmental sensor for cryogenic correlative light and electron microscopy

Cryogenic correlative light and electron microscopy (cryo-CLEM) seeks to leverage orthogonal information present in two powerful imaging modalities. While recent advances in cryogenic electron microscopy (cryo-EM) allow for the visualization and identification of structures within cells at the nanometer scale, information regarding the cellular environment, such as pH, membrane potential, ionic strength, etc., which influences the observed structures remains absent. Fluorescence microscopy can potentially be used to reveal this information when specific labels, known as fluorescent biosensors, are used, but there has been minimal use of such biosensors in cryo-CLEM to date. Here we demonstrate the applicability of one such biosensor, the fluorescent protein roGFP2, for cryo-CLEM experiments. At room temperature, the ratio of roGFP2 emission brightness when excited at 425 nm or 488 nm is known to report on the local redox potential. When samples containing roGFP2 are rapidly cooled to 77 K in a manner compatible with cryo-EM, the ratio of excitation peaks remains a faithful indicator of the redox potential at the time of freezing. Using purified protein in different oxidizing/reducing environments, we generate a calibration curve which can be used to analyze in situ measurements. As a proof-of-principle demonstration, we investigate the oxidation/reduction state within vitrified Caulobacter crescentus cells. The polar organizing protein Z (PopZ) localizes to the polar regions of C. crescentus where it is known to form a distinct microdomain. Finally, by expressing an inducible roGFP2-PopZ fusion we visualize individual microdomains in the context of their redox environment.

59 BASIC BIOLOGICAL SCIENCES↗

Self-regulating behavior of hybrid membrane systems as demonstrated in an element-scale forward osmosis-reverse osmosis hybrid system

Hybrid membrane systems can be difficult to design due to the requisite flow rate matching between up- and downstream unit operations. In this work, we use a forward osmosis-reverse osmosis (FO-RO) hybrid system to demonstrate how some membrane systems can exhibit self-regulating behavior due to osmotic coupling. This can reduce the need for complex control systems for flow balancing. We show this behavior using a module-scale test bed that can mimic the behavior of larger scale operations. The system shows permeate flow rate near-convergence between the FO and RO modules after startup or when perturbed by a change in RO module pressure. The behavior of this hybrid system demonstrates that some membrane operations can exploit osmotic interdependence, rather than expensive control systems, to achieve steady state operation.

Debottlenecking↗

Demonstration of sub-micron UCN position resolution using room-temperature CMOS sensor

High spatial resolution of ultracold neutron (UCN) measurement is of growing interest to UCN experiments such as UCN spectrometers, UCN polarimeters, quantum physics of UCNs, and quantum gravity. Here we utilize physics informed deep learning to enhance the experimental position resolution and to demonstrate sub-micron spatial resolutions for UCN position measurements obtained using a room-temperature CMOS sensor, extending our previous work that demonstrated a position uncertainty of 1.5 microns. We explore the use of the open-source software Allpix Squared to generate experiment-like synthetic hit images with ground-truth position labels. We use physics-informed deep learning by training a fully connected neural network (FCNN) to learn a mapping from input hit images to output hit position. The automated analysis for sub-micron position resolution in UCN detection combined with the fast data rates of current and next generation UCN sources will enable improved precision for future UCN research and applications.

10B nanometer thin film↗

Initial demonstration of automated fuel performance modeling with 1977 EBR-II metallic fuel pins using BISON code with FIPD and IMIS databases

Using the BISON fuel performance code, simulations were conducted using an automated process to read initial and operating conditions from the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor materials information system (IMIS) database, which contains metallic fuel data from the Experimental Breeder Reactor-II (EBR-II). This work demonstrates use of an integrated framework to access the vast majority of EBR-II experimental fuel pin data to support rapid development of fuel performance models for next-generation metallic fuel systems. With this capability, validation for fuel qualification can be performed rapidly. Between IMIS and FIPD, there is enough information to conduct 1977 unique EBR-II metallic fuel pin histories from 24 different experiments, at varying levels of detail between the two databases. Each of these histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures. Fission gas release (FGR), cumulative damage fraction (CDF), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON. The results were compared to post-irradiation examination (PIE) results for the initial demonstration of automated BISON modeling. BISON simulations conducted with IMIS and FIPD were in rough agreement with PIE measurements and calculations. Cladding profilometry, FGR, and fuel axial swelling were found to be in rough agreement with PIE measurements, depending on the physics used within the BISON input files. Here, the mechanical contact solver chosen was found to significantly impact axial fuel swelling and cladding strain predictions. CDF values were assessed to see whether pin failure may have been predicted (CDF ≥ 1). This work suggests that continued development of an automated tool for BISON should focus on inclusion of the Fast Flux Test Facility (FFTF) experimental data for a larger database for metallic fuel, improved physical models to better capture fuel performance, such as fuel-cladding interactions, and a more detailed comparison with available PIE data to further the BISON model development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Addressing wellbore integrity and thief zone permeability using microbially-induced calcium carbonate precipitation (MICP): A field demonstration

Microbially-induced calcium carbonate precipitation (MICP) is an emerging biotechnology for wellbore integrity applications including sealing defects in wellbore cement and modifying the permeability of rock formations. The goal of this field demonstration was to characterize a failed waterflood injection well and provide proof of principle that MICP can reduce permeability in the presence of oil using conventional oilfield fluid delivery methods. Here we compared well logs performed at the time the well was drilled with ultrasonic logs, sonic cement evaluation, and temperature logs conducted after the well failed. Analysis of these logs suggested that, rather than entering the target waterflood formation, injectate was traveling through defects in the well cement to a higher permeability sandstone layer above the target formation. Sporosarcina pasteurii cultures and urea-calcium media were delivered 2290 ft (698 m) below ground surface using a 3.75 gal (14.2 L) slickline dump bailer to promote mineralization in the undesired flow paths. By Day 6 and after 25 inoculum and 49 calcium media injections, the injectivity [gpm/psi] had decreased by approximately 70%. This demonstration shows that 1) common well logs can be used to identify scenarios where MICP can be employed to reduce system permeability, remediate leakage pathways, and improve waterflood efficiency, and 2) MICP can occur in the presence of hydrocarbons.

42 ENGINEERING↗

Experimental demonstration and performance evaluation of a complex fenestration system for daylighting and thermal harvesting

Two significant design strategies for mitigating building energy consumption are daylight redirection and solar energy harvesting. Effective daylighting implementation enhances the amount of useful natural light within a space and offsets the need for electric lighting. Solar energy harvesting systems can mitigate energy costs from mechanical systems by managing incoming thermal loads or capturing solar energy that can be used to supplement thermal systems in the building. While there are many available façade-based technologies that can perform daylighting or solar thermal energy harvesting, there remains a limitation in available systems that can perform both of them simultaneously. This paper, describes the design and experimental demonstration of a Liquid Filled Prismatic Louver (LFPL) system, which combines both energy-saving strategies. The LFPL system was installed in a south-facing room in New York City and evaluated for indoor daylight penetration and potential for thermal energy harvesting. Daylight redirection is achieved through the prismatic louver geometry and proper orientation, whereas thermal energy harvesting is achieved through IR absorption from the liquid (e.g., water) within the prisms. Daylighting performance was evaluated by illuminance measurements at key locations within the space, whereas thermal harvesting performance was evaluated through temperature measurements and thermal imaging analysis. We show that the LFPL system, with all prismatic elements oriented at the same angle, achieve a 2-fold and 8-fold enhancement in daylight redirection to the ceiling, for prism orientations of 10° and 20°, respectively. We also demonstrate the system’s capability to adjust to specific lighting needs, within the space, through the dynamic individual orientation of prismatic elements; thus, achieving a concentrated ceiling illuminance enhancement of ~100 times and ~200 times at 2.5 and 4.3 m away from the window sill, providing workplane illuminance enhancement of 6 and 2 times more than in the case of the control room with regular windows. Furthermore, we illustrate a reduction of potential heating loads at locations close to the window from the combination of infrared absorption in the water volume and the redirection of the incoming solar radiation, leading to a reduction of the workplane temperature by an average of 7–10 °C.

14 SOLAR ENERGY↗

FAK-targeting PROTAC demonstrates enhanced antitumor activity against KRAS mutant non-small cell lung cancer

Focal adhesion kinase (FAK) has been established as a promising therapeutic target for KRAS mutant non-small cell lung cancer (NSCLC). However, phase II clinical trials of a FAK inhibitor (Defactinib) have only shown modest antitumor activity. To address this challenge, here we report the use of a FAK-targeting proteolysis targeting chimera (D-PROTAC) to treat KRAS mutant NSCLC. We validated that D-PROTAC could efficiently eliminate FAK protein via the ubiquitin-proteasome pathway in KRAS mutant NSCLC A427 cells, causing over 90% degradation at 800 nM. After comparing both in vitro and in vivo therapeutic efficacies, we demonstrated that D-PRTOAC outperformed Defactinib in inhibiting tumor growth. Specifically, D-PROTAC at 800 nM reduced cell viability, migration, and invasion by ∼80%. Furthermore, a ∼85% suppression of tumor growth was elicited by D-PROTAC when intratumorally administrated at 10 mg/kg in subcutaneous A427-bearing mice. These results thus demonstrate for the first time that PROTACs may serve as promising therapeutic agents for the intractable NSCLC harboring KRAS mutations.

60 APPLIED LIFE SCIENCES↗

Design and demonstration of a direct air capture system with moisture-driven CO 2 delivery into aqueous medium

Two direct air capture (DAC) systems were designed and demonstrated to passively capture CO 2 from ambient air and use moisture to release the CO2 into an alkaline medium. A bench-scale system delivering ∼1 g CO 2 d –1 was demonstrated in a laminar flow hood, and a small pilot-scale system that could deliver ∼100 g CO 2 d –1 was operated outdoors in a 4.2 m 2 raceway pond. Novel elongated mesh-tube packets containing anion-exchange resin (AER) beads were found to reduce drying and CO 2 loading time 4.3-fold compared to larger mesh bags. Technoeconomic analysis (TEA) estimates the cost of capturing CO 2 into an alkaline solution, suitable for cultivating photosynthetic microorganisms, to be $\$229$ per tonne for a practical scenario based on current results and $\$72$ per tonne for an aspirational scenario considering improvements to sorbent capacity, hydrophobicity, and sorbent lifetime. TEA further estimates an additional $\$110$ per tonne to extract CO 2 from solution, purify it, and compress it to 15 MPa, suitable for sequestration. Furthermore, moisture-driven processes have the potential to use up to 87% less energy than thermal and/or vacuum swing DAC by using energy from water evaporation.

09 BIOMASS FUELS↗

Demonstration of Capture, Cooling, Tagging, and Spectroscopic Characterization of UV Photoproduct Ions in a Cryogenic Ion Trap: Application to 266 nm Photofragment Ions from Rhodamine 6G

We demonstrate a method to determine the structures of the primary photodissociation products from a cryogenically cooled parent ion. In this approach, a target ion is cooled by a pulse of buffer gas and tagged in a 20 K Paul trap. The cold ion is then photodissociated by pulsed (~5 ns) UV laser excitation, and the ionic products are trapped, cooled, and tagged by introduction of a second buffer gas pulse in the same trap. The tagged fragments are then ejected into a triple focusing, UV/vis/IR time-of-flight photofragmentation mass spectrometer which yields vibrational and electronic spectra of the mass-selected photofragments. Furthermore, these methods are demonstrated by application to the 266 nm photodissociation of the Rhodamine 6G cation to yield the R575 fragment ion based on loss of ethene as well as to a weaker secondary fragment arising from loss of m/z 43.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Demonstration of Energy-Resolved γ-Ray Detection at Room Temperature by the CsPbCl 3 Perovskite Semiconductor

The detection of gamma-rays at room temperature with high-energy resolution using semiconductors is one of the most challenging applications. The presence of even the smallest amount of defects is sufficient to kill the signal generated from gamma-rays which makes the availability of semiconductors detectors a rarity. Lead halide perovskite semiconductors exhibit unusually high defect tolerance leading to outstanding and unique optoelectronic properties and are poised to strongly impact applications in photoelectric conversion/detection. Here we demonstrate for the first time that large size single crystals of the all-inorganic perovskite CsPbCl 3 semiconductor can function as a high-performance detector for gamma-ray nuclear radiation at room temperature. CsPbCl 3 is a wide-gap semiconductor with a bandgap of 3.03 eV and possesses a high effective atomic number of 69.8. We identified the two distinct phase transitions in CsPbCl 3 , from cubic (Pm-3m) to tetragonal (P4/mbm) at 325 K and finally to orthorhombic (Pbnm) at 316 K. Despite crystal twinning induced by phase transitions, CsPbCl 3 crystals in detector grade can be obtained with high electrical resistivity of similar to 1.7 X 10 9 Ω∙cm. The crystals were grown from the melt with volume over several cubic centimeters and have a low thermal conductivity of 0.6 W m -1 K -1 . The mobilities for electron and hole carriers were determined to similar to 30 cm 2 /(V s). Using photoemission yield spectroscopy in air (PYSA), we determined the valence band maximum at 5.66 +/- 0.05 eV. Under gamma-ray exposure, our Schottky-type planar CsPbCl 3 detector achieved an excellent energy resolution (similar to 16% at 122 keV) accompanied by a high figure-of-merit hole mobility-lifetime product (3.2 x 10 -4 cm 2 /V) and a long hole lifetime (16 mu s). The results demonstrate considerable defect tolerance of CsPbCl 3 and suggest its strong potential for gamma-radiation and X-ray detection at room temperature and above.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

“Did you eat a MOLEcule today?” An Interactive Demonstration of Molecular Weight with Real-Time Breath Analysis Using Mass Spectrometry for All Ages

Although mass spectrometry is a widely used analytical tool, age-appropriate, interactive outreach activities for laboratory visitors, especially children, are lacking. Furthermore, the presented interactive demonstration, “Did you eat a MOLEcule today?”, introduces all ages to molecular weight concepts and mass spectrometry in a research laboratory, while connecting the concepts to real-world applications. Through real-time breath analysis, participants explore the concepts of molecular weight, electrostatic field manipulation of charged molecules, and analyte identification by mass analysis. This module is rapid and highly adaptable for outreach activities but also includes age- or classroom-appropriate variations to decrease or increase difficulty levels. The presented interactive demonstration has repeatedly been implemented, with over 2300 participants during six annual “Take Our Daughters & Sons to Work Day” and two corporate “Family Day” outreach activities, successfully engaging, exciting, and educating both kids and parents.

36 MATERIALS SCIENCE↗

Multidimensional Distributional Neural Network Output Demonstrated in Super‐Resolution of Surface Wind Speed

Accurate quantification of uncertainty in neural network predictions remains a central challenge for scientific applications involving high-dimensional, correlated data. While existing methods capture either aleatoric or epistemic uncertainty, few offer closed-form, multidimensional distributions that preserve spatial correlation while remaining computationally tractable. In this work, we present a framework for training neural networks with a multidimensional Gaussian loss, generating a closed-form predictive distribution over outputs informed by non-identically distributed training data. Our approach captures aleatoric uncertainty by iteratively estimating the means and covariance matrices, and is demonstrated on a super-resolution example out-of-training-sample. We leverage a Fourier representation of the covariance matrix to stabilize network training and preserve spatial correlation. We introduce a novel regularization strategy—referred to as information sharing—that interpolates between image-specific and global covariance estimates, enabling convergence of the super-resolution downscaling network trained on image-specific distributional loss functions. This framework allows for efficient sampling, explicit correlation modeling, and extensions to more complex distribution families all without disrupting prediction performance. We demonstrate the method on a surface wind speed downscaling task and discuss its broader applicability to uncertainty-aware prediction in scientific models.

17 WIND ENERGY↗

Demonstration of resonant tunneling effects in metal-double-insulator-metal (MI2M) diodes

Abstract Although the effect of resonant tunneling in metal-double-insulator-metal (MI 2 M) diodes has been predicted for over two decades, no experimental demonstrations have been reported at the low voltages needed for energy harvesting rectenna applications. Using quantum-well engineering, we demonstrate the effects of resonant tunneling in a Ni/NiO/Al 2 O 3 /Cr/Au MI 2 M structures and achieve the usually mutually exclusive desired characteristics of low resistance ( $${R}_{0}^{DC} \sim$$ R 0 D C ~ 13 kΩ for 0.035 μm 2 ) and high responsivity ( β 0 = 0.5 A W −1 ) simultaneously. By varying the thickness of insulators to modify the depth and width of the MI 2 M quantum well, we show that resonant quasi-bound states can be reached at near zero-bias, where diodes self-bias when driven by antennas illuminated at 30 THz. We present an improvement in energy conversion efficiency by more than a factor of 100 over the current state-of-the-art, offering the possibility of engineering efficient energy harvesting rectennas.

42 ENGINEERING↗

Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy

X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be time-consuming. While adaptive sampling methods exist for efficiently collecting spectroscopic data, they often lack domain-specific knowledge about the structure of XANES spectra. Here we demonstrate a knowledge-injected Bayesian optimization approach for adaptive XANES data collection that incorporates understanding of spectral features like absorption edges and pre-edge peaks. We show this method accurately reconstructs the absorption edge of XANES spectra using only 15–20% of the measurement points typically needed for conventional sampling, while maintaining the ability to determine the x-ray energy of the sharp peak after the absorption edge with errors less than 0.03 eV, the absorption edge with errors less than 0.1 eV; and overall root-mean-square errors less than 0.005 compared to traditionally sampled spectra. Our experiments on battery materials and catalysts demonstrate the method’s effectiveness for both static and dynamic XANES measurements, improving data collection efficiency and enabling better time resolution for tracking chemical changes. This approach advances the degree of automation in XANES experiments, reducing the common errors of under- or over-sampling points near the absorption edge and enabling dynamic experiments that require high temporal resolution or limited measurement time.

Bayesian optimization↗

Uncovering the active sites and demonstrating stable catalyst for the cost-effective conversion of ethanol to 1-butanol

We report the recent emergence of a robust renewable ethanol industry has provided a sustainable platform molecule toward the production of value-added chemicals and fuels; what is lacking now are viable conversion processes from ethanol that can displace the current production pathways from non-renewable pathways. Here in the work, we demonstrate the highly selective conversion of ethanol to higher alcohols over low copper loaded MgAl mixed oxide catalysts, with 50% improvement in higher alcohol yields over the current state of the art. At these copper concentrations, atomically dispersed Cu +1 were found to be stable even at highly reductive conditions and highly active towards higher alcohol products (e.g. butanol, hexanol) while suppressing side reaction pathways and leading to extended lifetimes of over 150 hours time on stream. Technoeconomic analysis conducted based on these experimental results demonstrate that this catalytic system is cost-competitive with the conventional process. This marks significant progress in the development of Guerbet coupling of ethanol as a viable renewable process and offers a pathway toward sustainable chemical and fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Demonstration of transmission high energy electron microscopy

Charged particle radiography with 800 MeV protons has been used for decades at LANL and developed around the world to study dynamic material properties. Recently, charged particle radiography has been demonstrated with the use of high-energy electrons. Because of the difference in the mass of the electron compared to the mass of the proton, the radiographic processes are substantially different and well suited to the study of fast dynamic processes in relatively thin systems. This presentation will show the layout required for such measurements, along with data collected from this recent demonstration performed with 14 GeV electrons generated at the SLAC National Accelerator Laboratory. The radiographic performance for flash measurements will be presented, along with the limitations of this measurement technique.

Merrill, F. E.↗