X-ray absorption spectroscopy of organic sulfoxides
This study develops an understanding of the X-ray absorption near-edge spectra of organic sulfoxides using the sulfur and oxygen K-edges.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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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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A New 2.5 MeV Injector and Beam Test Facility for the Spallation Neutron Source
The U.S. Spallation Neutron Source (SNS) now operates with 1.2 MW of beam power on target with the near-term goal of delivering 1.4 MW and a longer-term goal of delivering >2 MW to support a planned second target station. Presently, H- beam pulses (50-60 mA, 1 ms, 60 Hz) from an RF-driven, Cs-enhanced, multi-cusp ion source are first accelerated to 2.5 MeV by a Radio Frequency Quadrupole (RFQ) accelerator, injected into a ~1 GeV linac, compressed to <1μs in an accumulator ring and ultimately delivered to a liquid mercury target for pulsed neutron production. In recent years concerns about the RFQ performance has motivated the procurement of a new RFQ and the creation of a Beam Test Facility (BTF) to allow off-line testing. The purpose of the BTF is to first validate performance of the new RFQ before installing it in place of the existing RFQ and later to serve as a stand-alone 2.5 MeV research accelerator employing the original SNS RFQ. After validating the new RFQ with respect to energy, emittance and transmission, the initial applications of the BTF will be to conduct 6D beam dynamic studies, develop & demonstrate ion sources capable of meeting the current and future requirements of the SNS, and contribute to neutron moderator development. This report provides a facility update, description of the BTF ion source systems as well as a discussion of the first LEBT and RFQ beam current measurements performed at the BTF.REFERENCES
Welton, Robert F.↗
A physics-constrained neural network for multiphase flows
The present study develops a physics-constrained neural network (PCNN) to predict sequential patterns and motions of multiphase flows (MPFs), which includes strong interactions among various fluid phases. To predict the order parameters, which locate individual phases in the future time, a neural network (NN) is applied to quickly infer the dynamics of the phases by encoding observations. The multiphase consistent and conservative boundedness mapping algorithm (MCBOM) is next implemented to correct the predicted order parameters. This enforces the predicted order parameters to strictly satisfy the mass conservation, the summation of the volume fractions of the phases to be unity, the consistency of reduction, and the boundedness of the order parameters. Then, the density of the fluid mixture is updated from the corrected order parameters. Finally, the velocity in the future time is predicted by another NN with the same network structure, but the conservation of momentum is included in the loss function to shrink the parameter space. The proposed PCNN for MPFs sequentially performs (NN)-(MCBOM)-(NN), which avoids nonphysical behaviors of the order parameters, accelerates the convergence, and requires fewer data to make predictions. Numerical experiments demonstrate that the proposed PCNN is capable of predicting MPFs effectively.
Mechanics↗
A curvature-based mechanism for the spontaneous emission of electromagnetic radiation at curved plasma–vacuum interfaces
In this work, we derive from first principles the dispersion relation for electromagnetic radiation that is spontaneously emitted at a 2D curved plasma–vacuum interface in the absence of both background and external electric and magnetic fields. This plasma geometry is motivated by plasmas generated through hypervelocity impact projectiles—an area that is of importance to satellite safety in the aerospace community, and may be of importance for the developing study of projectile impact-driven inertial confinement fusion. We find spontaneous radiation occurs when thermal surface waves propagate along the edge of a circular plasma, with a frequency lower than the plasma frequency and spatial decay proportional to 1/r. This is distinct from more well-known mechanisms of radiation, in which the radiation frequency is greater than or equal to the plasma frequency. This theory is validated against 2D, electromagnetic particle-in-cell simulations and shows reasonable agreement. Finally, we discuss the effects of plasma geometry and attribute the radiation generation mechanism to the acceleration of charged surface waves as they traverse azimuthally along a curved path.
Lau, Raymond (ORCID:0000000299318101)↗
Phonon screening and dissociation of excitons at finite temperatures from first principles
The properties of excitons, or correlated electron–hole pairs, are of paramount importance to optoelectronic applications of materials. A central component of exciton physics is the electron–hole interaction, which is commonly treated as screened solely by electrons within a material. However, nuclear motion can screen this Coulomb interaction as well, with several recent studies developing model approaches for approximating the phonon screening of excitonic properties. While these model approaches tend to improve agreement with experiment, they rely on several approximations that restrict their applicability to a wide range of materials, and thus far they have neglected the effect of finite temperatures. Here, we develop a fully first-principles, parameter-free approach to compute the temperature-dependent effects of phonon screening within the ab initio GW -Bethe–Salpeter equation framework. We recover previously proposed models of phonon screening as well-defined limits of our general framework, and discuss their validity by comparing them against our first-principles results. We develop an efficient computational workflow and apply it to a diverse set of semiconductors, specifically AlN, CdS, GaN, MgO, and SrTiO 3 . We demonstrate under different physical scenarios how excitons may be screened by multiple polar optical or acoustic phonons, how their binding energies can exhibit strong temperature dependence, and the ultrafast timescales on which they dissociate into free electron–hole pairs.
Science & Technology - Other Topics↗
An atypical lipoteichoic acid from Clostridium perfringens elicits a broadly cross-reactive and protective immune response
Clostridium perfringens is a leading cause of food-poisoning and causes avian necrotic enteritis, posing a significant problem to both the poultry industry and human health. No effective vaccine against C. perfringens is currently available. Using an antiserum screen of mutants generated from a C. perfringens transposon-mutant library, here we identified an immunoreactive antigen that was lost in a putative glycosyltransferase mutant, suggesting that this antigen is likely a glycoconjugate. Following injection of formalin-fixed whole cells of C. perfringens HN13 (a laboratory strain) and JGS4143 (chicken isolate) intramuscularly into chickens, the HN13-derived antiserum was cross-reactive in immunoblots with all tested 32 field isolates, whereas only 5 of 32 isolates were recognized by JGS4143-derived antiserum. The immunoreactive antigens from both HN13 and JGS4143 were isolated, and structural analysis by MALDI-TOF-MS, GC-MS, and 2D NMR revealed that both were atypical lipoteichoic acids (LTAs) with poly-(β1→4)-ManNAc backbones substituted with phosphoethanolamine. However, although the ManNAc residues in JGS4143 LTA were phosphoethanolamine-modified, a few of these residues were instead modified with phosphoglycerol in the HN13 LTA. The JGS4143 LTA also had a terminal ribose and ManNAc instead of ManN in the core region, suggesting that these differences may contribute to the broadly cross-reactive response elicited by HN13. In a passive-protection chicken experiment, oral challenge with C. perfringens JGS4143 lead to 22% survival, whereas co-gavage with JGS4143 and α-HN13 antiserum resulted in 89% survival. This serum also induced bacterial killing in opsonophagocytosis assays, suggesting that HN13 LTA is an attractive target for future vaccine-development studies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Do people spend travel time the way they think they would? a comparative study of generic and trip-specific travel time allocation using hybrid multiple discrete continuous (MDC) framework
Unlike driving alone, public transportation allows one to engage in extraneous activities while traveling – often referred to as travel-based multitasking. Research involving travel-based multitasking often relies on either generic (i.e. not related to an actual trip) or revealed (i.e. related to an executed trip) data. The data collected for this study provided a unique opportunity to compare the generic and trip-specific preferences while traveling on public transportation. To this end, the study develops two integrated choice and latent variable models with multiple discrete-continuous (MDC) kernels to simultaneously model the activity selection and the time allocation for generic and trip-specific data, respectively. According to the results the trip-specific data could identify more nuances in the travel-based multitasking behavior than the generic data. Finally, the heterogeneity identified by the developed models will be helpful for the transit operators in providing appropriate facilities (e.g. internet access, reading lights) along various transit corridors.
99 GENERAL AND MISCELLANEOUS↗
Lighting up yeast: overview of optogenetics in yeast and their applications to yeast biotechnology
Abstract Optogenetics is an empowering technology that uses light-responsive proteins to control biological processes. Because of its genetic tractability, abundance of genetic tools, and robust culturing conditions, Saccharomyces cerevisiae has served for many years as an ideal platform in which to study, develop, and apply a wide range of optogenetic systems. In many instances, yeast has been used as a steppingstone in which to characterize and optimize optogenetic tools to later be deployed in higher eukaryotes. More recently, however, optogenetic tools have been developed and deployed in yeast specifically for biotechnological applications, including in nonconventional yeasts. In this review, we summarize various optogenetic systems responding to different wavelengths of light that have been demonstrated in diverse yeast species. We then describe various applications of these optogenetic tools in yeast, particularly in metabolic engineering and recombinant protein production. Finally, we discuss emerging applications in yeast cybergenetics—the interfacing of yeast and computers for closed-loop controls of yeast bioprocesses—and the potential impact of optogenetics in other future biotechnological applications.
Biotechnology & Applied Microbiology↗
Resonant control of photoelectron directionality by interfering one- and two-photon pathways
Coherent control of interfering one- and two-photon processes has for decades been the subject of research to achieve the redirection of photocurrent. The present study develops two-pathway coherent control of ground-state helium atom above-threshold photoionization for energies up to the N = 2 threshold, based on a multichannel quantum defect and R-matrix calculation. Three parameters are controlled in our treatment: the optical interference phase ΔΦ, the reduced electric field strength χ = $\mathscr{E}^2_ω$$\mathscr{E}_{2ω}$, and the final state energy ε. A small energy change near a resonance is shown to flip the emission direction of photoelectrons with high efficiency, through an example where 90% of photoelectrons whose energy is near the 2p 2 1 S e resonance flip their emission direction. However, the large fraction of photoelectrons ionized at the intermediate state energy, which are not influenced by the optical control, make this control scheme challenging to realize experimentally.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Optimal Proactive Vehicle Relocation for On-Demand Mobility Service with Deep Convolution-LSTM Network
This study develops an innovative model for inferring optimal proactive relocation strategy for empty vehicles of on-demand mobility service (OMS) directly from past observations of passenger demand. The output of our model is a row stochastic relocation matrix which gives the probability that an empty vehicle should be relocated from location i to location j at any given time. The matrix itself is high-dimensional and therefore challenging to obtain accurate estimation with traditional machine learning approach. Our model proposes the low-rank approximation of the relocation matrix, and introduces the deep convolution-LSTM network which extracts low-level spatial and temporal features from past demand observations for best restoration of the actual low rank approximation vector. The model is trained by deriving the optimal matching strategies from one year of real-world trip data. The results show that our model is able to predict the low-rank approximation of the relocation matrix with 4% of mean absolute error, may reduce the relocation cost by 20%-45% as compared to the real-world observations and is 50% optimal as compared to the global optimal matching with perfect information.
Lei, Zengxiang↗
A Multiagent Deep Reinforcement Learning-Enabled Dual-Branch Damping Controller for Multimode Oscillation
Here, this study develops a multiagent deep reinforcement learning (MADRL)-enabled framework for the decentralized cooperative control of a novel dual-branch (DB) damping controller for both low-frequency oscillation (LFO) and ultralow-frequency oscillation (ULFO). It has two branches, each of which consists of a proportional resonance (PR) and a second-order polynomial that is designed to handle target oscillation modes. To improve the robustness of the controller to system uncertainties, MADRL is developed, where multiagents are centrally trained to obtain the coordinated adaptive control policy while being executed in a decentralized manner to provide the optimal parameter setting for each controller with only local states. Comparisons with the IEEE 10-machine 39-bus system demonstrate that the proposed method achieves better robustness to uncertainties, lower communication delay, and single-point failure, as well as damping control performances for both LFO and ULFO.
97 MATHEMATICS AND COMPUTING↗
Network-Level Traffic Signal Cooperation: A Higher-Order Conflict Graph Approach
Traffic signal control and cooperation are extremely important to alleviate traffic congestion in a large traffic network. This study develops a higher-order conflict graph approach for network-wide traffic signal control and cooperation. A conflict graph is applied to model the traffic signal configurations, which identifies the conflict and unconflicted movements for each intersection. In conflict graph, the node represents each movement. The weight of each node can be defined as traffic volume, queue length, fuel consumption, or any weighted combinations of these measurements. The calculation of the optimal green light duration and green light sequence (for different movements) is equivalent to sequentially finding the maximum weight independent set (MWIS) in the conflict graph. The conflict graph also provides a uniform and efficient way to connect traffic signal operations among nearby intersections spatially. Then, we introduced the concept of the k -th order neighborhood to model the degree of connectivity between each movement to the movements at upstream or downstream intersections. The weight of each node in the higher-order conflict graph not only represents its own congestion level, but also relates to the traffic conditions of nearby intersections. Through this approach, the cooperation of multiple intersections can be realized by incorporating their spatial connectivity into conflict graph and solving the MWIS problem. A simulation network is built in SUMO to test the effectiveness of the proposed method. Results suggested that the proposed model outperformed other state-of-the-art signal control methods. Also, the scheme maintains good performance under varying traffic demands.
42 ENGINEERING↗
What Is the Best Use of Biomass? A Harmonized LCA-TEA Framework Quantifying Economic and Environmental Metrics for Bioenergy Pathways
Bioresource utilization is expected to play a pivotal role in complementing existing energy pathways and enhancing energy resilience. This study develops a harmonized life cycle assessment (LCA) and techno-economic analysis (TEA) framework to evaluate the greenhouse gas (GHG) reduction potential, minimum fuel selling price (MFSP), and marginal abatement cost (MAC) of bioenergy pathways. We analyze 19 pathways, including liquid biofuels (via catalytic fast pyrolysis, Fischer–Tropsch synthesis, and gasification), bioelectricity, and biomass-to-hydrogen, with and without carbon capture and storage (CCS). The GHG impacts are assessed using the GREET 2022 model, while U.S. Billion-Ton 2016 biomass availability projections are used to estimate scale-up potential. Additionally, we evaluate the influence of a low-carbon electricity grid on pathway performance. Our results show that CCS implementation reduces carbon intensities (CI) to net-negative values for several pathways, with MAC ranging from $\$$32 to $\$$600 per metric ton (MT) CO2e avoided. Bioelectricity pathways with CCS achieve the lowest MAC ($\$$32–$\$$68/tCO2e), while liquid biofuels and hydrogen pathways remain critical for hard-to-abate sectors like aviation and heavy industry. Pathways with net-positive electricity demand benefit from a low-carbon grid, whereas those co-producing electricity experience increased MAC under lower electricity grid CI scenarios. This open-source framework provides a robust tool for harmonized evaluation of bioenergy pathways, enabling policymakers and stakeholders to identify cost-effective strategies for biomass utilization and carbon abatement at scale. The findings underscore the importance of CCS, co-product credits, and feedstock availability in optimizing bioenergy deployment for a low-carbon economy.
09 BIOMASS FUELS↗
Hanford low-activity waste glass composition-temperature-melt viscosity relationships
This study developed a model for predicting viscosity of alkali-alumino-borosilicate glass melts as functions of composition and temperature. The model is based on a total of 3935 viscosity-temperature data from 574 glasses with viscosity values ranging from 2.53 to 7260 Poise (P) in the temperature range of 900–1260°C. Several different model forms were surveyed, including those based on Arrhenius, Vogel-Fulcher-Tammann, Avramov-Milchev, and Mauro-Yue-Ellison-Gupta-Allen. For each of these models, combinations of the temperature-independent parameters were fitted to composition. It was found that generally fitting more than one temperature-independent parameter as functions of composition resulted in overfitting. The Avramov-Milchev-based model was found to best represent the Hanford low-activity waste glass melt viscosity data based on model fit and validation statistics. A 21-term partial quadratic mixture model was recommended for use. This model predicts melt viscosity with a root-mean square error of .1736 ln(P), which is similar to the error in viscosity measurements from replicate glass analyses of .1383 ln(P). Viscosity was found to be most increased by SiO 2 > Al 2 O 3 > ZrO 2 > SnO 2 and most decreased by Li 2 O > Na 2 O > B 2 O 3 > CaO > K 2 O > MgO, at temperatures from 900 to 1260°C.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Performance of a CO 2 sorbent for indoor air cleaning applications: Effects of environmental conditions, sorbent aging, and adsorption of co-occurring formaldehyde
Indoor air cleaning systems that incorporate CO 2 sorbent materials enable HVAC load shifting and efficiency improvements. This study developed a bench-scale experimental system to evaluate the performance of a sorbent under controlled operation conditions. A thermostatic holder containing 3.15 g sorbent was connected to a manifold that delivered CO 2 -enriched air at a known temperature and relative humidity (RH). The air stream was also enriched with 0.8-2.1 ppm formaldehyde. The CO 2 concentration was monitored in real-time upstream and downstream of the sorbent, and integrated formaldehyde samples were collected at different times using DNPH-coated silica cartridges. Sorbent regeneration was carried out by circulating clean air in countercurrent. Almost 200 loading/regeneration cycles were performed in the span of 17 months, from which 104 were carried out at reference test conditions defined by loading with air at 25°C, 38% RH, and 1000 ppm CO 2 , and regenerating with air at 80°C, 3% RH and 400 ppm CO 2 . The working capacity decreased slightly from 43-44 mg CO 2 per g sorbent to 39-40 mg per g over the 17 months. The capacity increased with lower loading temperature (in the range 15-35°C) and higher regeneration temperature, between 40 and 80°C. The CO 2 capacity was not sensitive to the moisture content in the range 6-9 g/m 3 , and decreased slightly when dry air was used. Loading isothermal breakthrough curves were fitted to three simple adsorption models, verifying that pseudo-first-order kinetics appropriately describes the adsorption process. The model predicted that equilibrium capacities decreased with increasing temperature from 15 to 35°C, while adsorption rate constants slightly increased. The formaldehyde adsorption efficiency was 80%-99% in different cycles, corresponding to an average capacity of 86 ± 36 µg/g. Formaldehyde was not quantitatively released during regeneration, but its accumulation on the sorbent did not affect CO 2 adsorption.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Dynamic QTL mapping for plant height in the hybrid population of Agropyron Gaertn.
Abstract Plant height (PH) plays a very important role for plant breeding and also serves as a model trait to dynamic development study. The dynamic quantitative trait locus (QTL) analysis for PH of Agropyron Gaertn. was carried out in a cross‐pollination (CP) hybrid population of A. Gaertn. based on the phenotypic data of PH at different developmental stages in four year‐sites and the constructed single‐nucleotide polymorphism (SNP) genetic map. The results showed that 69 QTL and nine major QTL were detected by unconditional QTL mapping. A total of 107 QTL and 13 major QTL were found using conditional QTL mapping. Forty‐seven QTL were detected by two methods. Two unconditional QTL, Qph2‐5 and Qph3‐4, were expressed as major and stable QTL for PH. Four major stable conditional QTL for PH, cQph4‐1 , cQph4‐8, cQph6‐2 and cQph6‐7 , were detected. Two conditional PH QTL, cQph3‐5 and cQPh3‐7 , were identified in four environments over multiple stages. The gene/QTL controlling PH was expressed in a certain spatiotemporal manner. These results could also provide a reference for genetic and breeding research of related plant.
Che, Yonghe↗
Poster - 34: Clinical Implementation of Prone Breast Treatment
Purpose: Prone breast treatment is used to reduce acute and late toxicities for large or pendulous breast patients. This study developed and implemented the clinical workflow of prone breast radiotherapy treatment. Methods: Varian kVue Access360™ Prone Breast Couchtop was used as prone breast board. The treatment planning (TP)is performed in Eclipse TP system. TP comparisons between supine deep inspiration breathing hold (DIBH) and prone breast; prone forward field-in-field (FinF) planning and inverse IMRT planning were performed and discussed. For the daily setup, breast coverage was assessed in the room using light field and MV imaging was used at day 1 and weekly. Results: The first ten patients are CT scanned and planned both supine and prone. The coverage was all excellent for supine DIBH plan and prone breast plan. The plan in the prone position demonstrated improvements in lung sparing comparing to the DIBH plan. Both forward FinF plan and inverse IMRT plan achieved acceptable coverage of the breast, and heart dose is comparable. Considering the daily setup variations and MLC leakage, forward FinF plan was recommended for routine clinical use. The procedure has been tested in phantom and patients were treated clinically. Conclusions: Prone breast irradiation has been advocated for women with large pendulous breasts in order to decrease acute and late toxicities. The workflow for prone breast radiation therapy has been developed and the technique is ready to treat patients.
60 APPLIED LIFE SCIENCES↗
In-process volumetric sensing of defects in multiple parts during powder bed fusion using ultrasound
This letter reports on the integration of eight ultrasonic transducers into a build substrate for individual in-process monitoring of eight parts fabricated using powder bed fusion additive manufacturing. Ultrasound is shown to be able to sense poor fusion of parts to the substrate and also sensitivity to porosity. This technique demonstrates the utility of ultrasound as one of a few techniques able to interrogate the volume of additively manufactured parts during the process. Additionally, the ability to measure several parts during a single build can be used for efficient process parameter development studies, as the ultrasonic measurements can offer rapid information about part quality and integrity.
Kizer, Nathan J.↗