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At least 307 records · Page 17

Photoinduced anisotropic lattice dynamic response and domain formation in thermoelectric SnSe

Identifying and understanding the mechanisms behind strong phonon–phonon scattering in condensed matter systems is critical to maximizing the efficiency of thermoelectric devices. To date, the leading method to address this has been to meticulously survey the full phonon dispersion of the material in order to isolate modes with anomalously large linewidth and temperature-dependence. Here we combine quantitative MeV ultrafast electron diffraction (UED) analysis with Monte Carlo based dynamic diffraction simulation and first-principles calculations to directly unveil the soft, anharmonic lattice distortions of model thermoelectric material SnSe. A small single-crystal sample is photoexcited with ultrafast optical pulses and the soft, anharmonic lattice distortions are isolated using MeV-UED as those associated with long relaxation time and large displacements. We reveal that these modes have interlayer shear strain character, induced mainly by c -axis atomic displacements, resulting in domain formation in the transient state. These findings provide an innovative approach to identify mechanisms for ultralow and anisotropic thermal conductivity and a promising route to optimizing thermoelectric devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Pathways to a net-zero-carbon water sector through energy-extracting wastewater technologies

The energy-consuming and carbon-intensive wastewater treatment plants could become significant energy producers and recycled organic and metallic material generators, thereby contributing to broad sustainable development goals, the circular economy, and the water-energy-sanitation-food-carbon nexus. This review provides an overview of the waste(water)-based energy-extracting technologies, their engineering performance, techno-economic feasibility, and environmental benefits. Here, we propose four crucial strategies to achieve net-zero carbon along with energy sufficiency in the water sector, including (1) improvement in process energy efficiency; (2) maximizing on-site renewable capacities and biogas upgrading; (3) harvesting energy from treated effluent; (4) a new paradigm for decentralized water-energy supply units.

54 ENVIRONMENTAL SCIENCES↗

Additive manufacturing of LiCoO 2 electrodes via vat photopolymerization for lithium ion batteries

Additive manufacturing has the potential to revolutionize the fabrication of lithium-ion batteries for a diversity of applications including in portable, biomedical, aerospace, and the transportation fields. Standard commercial batteries consist of stacked layers of various components (current collectors, cathode, anode, separator and electrolyte) in a two-dimensional manner. By leveraging the latest advances in additive manufacturing and computer-aided design, an improved geometric and electrochemical configuration of these batteries can maximize energy efficiency while allowing design optimization to reduce dead space for a given application. In this work, a composite UV photosensitive resin was prepared and used as feedstock in a vat photopolymerization system. The resin was loaded with LiCoO 2 acting as electrochemically active material for the cathode of a lithium-ion battery, and was further improved with the addition of conductivity-enhancing carbonaceous additives. Challenges to additive manufacturing arise from the opacity and high viscosity of the composite nature of these electrochemically-active resins, which cause light refraction during selective UV curing. Subsequently, items were printed and subjected to a thermal post-processing step to obtain an adequate compromise between electrochemical performance and mechanical integrity. Both sintered and green state 3D printed cathodes were assembled into half-cell lithium-ion batteries using lithium metal as a reference and counter electrode. Electrochemical cycling of these batteries yielded satisfactory results approaching commercial LiCoO 2 cathodes’ performance, with the potential advantages of additive manufacturing – high surface area anode–cathode configurations for power performance as well as shape conformability.

25 ENERGY STORAGE↗

Optimization of distributed compute resources utilization in the CMS Global Pool

The CMS Submission Infrastructure is the primary system for managing computing resources for CMS workflows, including data processing, simulation, and analysis. It integrates geographically distributed resources from Grid, HPC, and cloud providers into federated pools managed by HTCondor and Glidein- WMS, for a total of around 500k CPU cores. This system dynamically manages workloads based on priorities defined by the collaboration. Additionally, CMS scheduling strategies must be flexible to handle multiple concurrent workloads while considering changing processing demands and resource availability from various providers.Efficient utilization of vast amounts of distributed compute resources is a key element for the success of the scientific programs of the LHC experiments. Optimizing the system is essential to maximize resource efficiency and fully utilize the distributed computing power. The CMS Submission Infrastructure team thus systematically investigates sources of inefficiency in workload scheduling to reduce their impact. In addition, a strategy of pilot overloading has been introduced to compensate for other inefficiency sources, thereby optimizing resource utilization and enhancing computational throughput.

Mascheroni, Marco [UC, San Diego (main)]↗

Electronic tuning of the transport properties of off-stoichiometric Pb{sub x}Sn{sub 1−x}Te thermoelectric alloys by Bi{sub 2}Te{sub 3} doping

The recent energy demands affected by the dilution of conventional energy resources and the growing awareness of environmental considerations had motivated many researchers to seek for novel renewable energy conversion methods. Thermoelectric direct conversion of thermal into electrical energies is such a method, in which common compositions include IV-VI semiconducting compounds (e.g., PbTe and SnTe) and their alloys. For approaching practical thermoelectric devices, the current research is focused on electronic optimization of off-stoichiometric p-type Pb{sub x}Sn{sub 1−x}Te alloys by tuning of Bi{sub 2}Te{sub 3} doping and/or SnTe alloying levels, while avoiding the less mechanically favorable Na dopant. It was shown that upon such doping/alloying, higher ZTs, compared to those of previously reported undoped Pb{sub 0.5}Sn{sub 0.5}Te alloy, were obtained at temperatures lower than 210–340 °C, depending of the exact doping/alloying level. It was demonstrated that upon optimal grading of the carrier concentration, a maximal thermoelectric efficiency enhancement of ∼38%, compared to that of an undoped material, is expected.

30 DIRECT ENERGY CONVERSION↗

Axisymmetric electrostatic magnetohydrodynamic oscillations in tokamaks with general cross-sections and toroidal flow

The frequency spectrum and mode structure of axisymmetric electrostatic oscillations [the zonal flow (ZF), sound waves (SW), geodesic acoustic modes (GAM), and electrostatic mean flows (EMF)] in tokamaks with general cross-sections and toroidal flows are studied analytically using the electrostatic approximation for magnetohydrodynamic modes. These modes constitute the “electrostatic continua.” Starting from the energy principle for a tokamak plasma with toroidal rotation, we showed that these modes are completely stable. The ZF, the SW, and the EMF could all be viewed as special cases of the general GAM. The Euler equations for the general GAM are obtained and are solved analytically for both the low and high range of Mach numbers. The solution consists of the usual countable infinite set of eigen-modes with discrete eigen-frequencies, and two modes with lower frequencies. The countable infinite set is identified with the regular GAM. The lower frequency mode, which is also divergence free as the plasma rotation tends to zero, is identified as the ZF. The other lower (zero) frequency mode is a pure geodesic E×B flow and not divergence free is identified as the EMF. The frequency of the EMF is shown to be exactly 0 independent of plasma cross-section or its flow Mach number. We also show that in general, sound waves with no geodesic components are (almost) completely lost in tokamaks with a general cross-sectional shape. The exception is the special case of strict up-down symmetry. In this case, half of the GAMs would have no geodesic displacements. They are identified as the SW. Present day tokamaks, although not strictly up-down symmetric, usually are only slightly up-down asymmetric. They are expected to share the property with the up-down symmetric tokamak in that half of the GAMs would be more sound wave-like, i.e., have much weaker coupling to the geodesic components than the other half of non-sound-wave-like modes with stronger coupling to the geodesic displacements. Based on the general notion that the geodesic component of the GAM is more effective in tearing up the eddies in the electrostatic turbulence, it is important to preferentially excite the GAMs that are non-sound-wave like to maximize the efficiency on turbulence suppression through external means. Finally, approximate formulae for the frequencies of the EMF, ZF, SW, and the GAM for a large aspect ratio circular tokamak rotating at low Mach numbers are also provided.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Shr receptor from Streptococcus pyogenes uses a cap and release mechanism to acquire heme–iron from human hemoglobin

Streptococcus pyogenes (group A Streptococcus ) is a clinically important microbial pathogen that requires iron in order to proliferate. During infections, S. pyogenes uses the surface displayed Shr receptor to capture human hemoglobin (Hb) and acquires its iron-laden heme molecules. Through a poorly understood mechanism, Shr engages Hb via two structurally unique N-terminal Hb-interacting domains (HID1 and HID2) which facilitate heme transfer to proximal NEAr Transporter (NEAT) domains. Based on the results of X-ray crystallography, small angle X-ray scattering, NMR spectroscopy, native mass spectrometry, and heme transfer experiments, we propose that Shr utilizes a “cap and release” mechanism to gather heme from Hb. In the mechanism, Shr uses the HID1 and HID2 modules to preferentially recognize only heme-loaded forms of Hb by contacting the edges of its protoporphyrin rings. Heme transfer is enabled by significant receptor dynamics within the Shr–Hb complex which function to transiently uncap HID1 from the heme bound to Hb’s β subunit, enabling the gated release of its relatively weakly bound heme molecule and subsequent capture by Shr’s NEAT domains. These dynamics may maximize the efficiency of heme scavenging by S. pyogenes , enabling it to preferentially recognize and remove heme from only heme-loaded forms of Hb that contain iron.

59 BASIC BIOLOGICAL SCIENCES↗

Rubisco kinetic acclimation at the holoenzyme level

Kinetic acclimation enables proteins to adjust their activity in response to environmental perturbations. For the CO 2 -fixing enzyme Rubisco, kinetic acclimation may be conferred by its small subunits. Plants express multiple small subunits and vary their expression with temperature. Here, we demonstrate that different small subunits can bind to the same Rubisco to form a heterogeneous holoenzyme. These small subunits had distinct kinetic effects which aligned with changes in holoenzyme structure and stability. Our findings indicate that small subunits enable Rubisco kinetic acclimation via manipulation of flexibility. By assembling a more rigid active site in higher temperatures and a more flexible one in lower temperatures, plants maximize the efficiency of their Rubisco, and thus photosynthesis, over a wide range of temperatures.

CO2 fixation↗

Optimizing multi-modal, non-axisymmetric plasma response metrics with additional coil rows on DIII-D

The expansion of the DIII-D tokamak operational space via the addition of new non-axisymmetric coil rows is investigated using the linear MHD plasma response code MARS-F. The plasma response to magnetic perturbations imposed by five distinct low- and high-field side coil geometries is modeled for toroidal mode numbers up to n = 6. A set of linear (~δB^2: resonant, kink mode amplitude) and quadratic (~δB: core and edge integrated NTV torque) plasma metrics are defined and compared directly for the various coil geometries. Coil size is also scanned as a secondary optimization variable. An in-vessel coil located at the low-field side midplane is identified as the most efficient plasma response actuator across all metrics and toroidal mode numbers. The multi-row combination of this new midplane (M) coil with the existing DIII-D non-axisymmetric coil set is considered in numerical optimization studies to quantify the impact of this new coil on modeled plasma response metrics. The addition of the M coil is shown to significantly increase the actuator efficiency in maximizing individual plasma response metrics as well as maximizing multi-modal ratios of response metrics, e.g. maximizing resonant modes or edge NTV torque while minimizing kink modes or core NTV torque. The ex-vessel midplane (C) coil is also observed to have an outsize effect on multi-modal optimization due to its uniquely narrow poloidal spectra, and the expansion of optimization space due to the combined use of the two existing in-vessel coil rows with both the M and C coils is notably larger than either coil's individual contribution even though both share similar poloidal locations. This four-row system is expected to greatly extend abilities to understand and optimize the control of transients and rotation on the DIII-D tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effects of Inflow Spatiotemporal Discretization on Wake Meandering and Turbine Structural Response using FAST.Farm

FAST.Farm is a newly developed multiphysics, midfidelity engineering tool that can be used to predict turbine power and structural loads of wind turbines in a wind farm with minimal computational expense. Previous studies have shown similarities and differences in wind turbine performance between FAST.Farm and high-fidelity large-eddy simulations (LES) using both LES precursor-generated inflow and TurbSim-generated synthetic inflow. While conservative resolutions have been used to date, no formal spatial or temporal discretization study has been performed for the FAST.Farm model wind domains. This work aims to study the effects of varying the spatial and temporal discretization of the wind domains on wake meandering (low-resolution domain) and turbine structural response (high-resolution domains) and resulting wake and load calculations. The purpose of this study is to establish convergence criteria and recommendations for discretization values in terms of rotor diameter (D, expressed in meters) that will maximize computational efficiency. To ensure a percent error of ≤ 1% in standard deviation of wake center position relative to the finest included resolution, a low-resolution time step of 0.024D s, 0.016D s, and 0.0079D s and a low-resolution spatial discretization of 0.079D m, 0.16D m, and 0.24D m is recommended for 8 m/s, 12 m/s, and 18 m/s mean ambient wind speed at hub height, respectively. These guidelines are likely applicable to other implementations of the dynamic wake meandering model. To ensure a percent error of ≤ 1% in standard deviation of all considered structural response outputs, a high-resolution time step that captures the highest influential excitation and natural frequencies in the system and a high-resolution spatial discretization comparable to the maximum airfoil cord length is recommended. Lastly, these guidelines are likely applicable to any aeroelastic analysis.

17 WIND ENERGY↗

Performance of modern color decompositions for standard candle LHC tree amplitudes

In the last decade, developments of matrix element and phase space generators have focused on providing good efficiency and maximal flexibility and automation for a wide range of physical processes. However, as recent studies have shown, they are a major bottleneck in the established Monte Carlo event generator toolchains. With the advent of the HL-LHC and ever rising precision requirements, future developments will need to focus on computational performance, especially at intermediate to large jet multiplicities. We present the novel BlockGen family of fast matrix element algorithms that are amenable for GPU acceleration, making use of modern, minimal color decompositions. Moreover, we discuss the performance achieved for standard candle processes such as V +jets and tt̄+jets production.

Bothmann, E. [Gottingen U.]↗

Scintillation Light Detection System in LArIAT

The LArIAT experiment is currently taking data at Fermilab using a Liquid Argon TPC, with the aim of studying particle interactions and characterizing detector response for neutrino detectors using argon. In parallel, it serves as a test-bench to develop and evaluate the performance of the simulation, reconstruction, and analysis software used in LAr neutrino experiments. LArIAT also takes advantage of the scintillating capabilities of liquid argon and will evaluate the feasibility of using the light signal to determine calorimetric information and particle identification. To test this possibility, a scintillation light detection system consisting of high Quantum Efficiency (QE) PMT and Silicon Photomultiplier (SiPM) devices is installed in the cryostat, viewing the interior of the TPC. Light collection efficiency is maximized by means of lining the walls with reflector foils covered by a wavelength shifter layer. Collecting the light reflected at the boundaries of the active volume greatly improves also the uniformity of the light yield. Presented here are initial results of the LArIAT light detection system calibration together with the preliminary results of the dedicated simulation and its application in future LAr TPC experiments

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Assessing the design of integrated methane sensing networks

Abstract While methane is the second largest contributor to global warming after carbon dioxide, it has a larger warming effect over a much shorter lifetime. Despite accelerated technological efforts to radically reduce global carbon dioxide emissions, rapid reductions in methane emissions are needed to limit near-term warming. Being primarily emitted as a byproduct from agricultural activities and energy extraction, methane is currently monitored via bottom–up (i.e. activity level) or top–down (via airborne or satellite retrievals) approaches. However, significant methane leaks remain undetected and emission rates are challenging to characterize with current monitoring frameworks. In this paper, we study the design of a layered monitoring approach that combines bottom–up and top–down approaches as an integrated sensing network. By recognizing that varying meteorological conditions and emission rates impact the efficacy of bottom–up monitoring, we develop a probabilistic approach to optimal sensor placement in its bottom–up network. Subsequently, we derive an inverse Bayesian framework to quantify the improvement that a design-optimized integrated framework has on emission-rate quantifications and their uncertainties. We find that under realistic meteorological conditions, the overall error in estimating the true emission rates is approximately 1.3 times higher, with their uncertainties being approximately 2.4 times higher, when using a randomized network over an optimized network, highlighting the importance of optimizing the design of integrated methane sensing networks. Further, we find that optimized networks can improve scenario coverage fractions by more than a factor of 2 over experimentally-studied networks, and identify a budget threshold beyond which the rate of optimized-network coverage improvement exhibits diminishing returns, suggesting that strategic sensor placement is also crucial for maximizing network efficiency.

54 ENVIRONMENTAL SCIENCES↗

Genetic basis of photosynthetic responses to cold in two locally adapted populations of Arabidopsis thaliana

Local adaptation is common, but the traits and genes involved are often unknown. Physiological responses to cold probably contribute to local adaptation in wide-ranging species, but the genetic basis underlying natural variation in these traits has rarely been studied. Using a recombinant inbred (495 lines) mapping population from locally adapted populations of Arabidopsis thaliana from Sweden and Italy, we grew plants at low temperature and mapped quantitative trait loci (QTLs) for traits related to photosynthesis: maximal quantum efficiency (F v /F m ), rapidly reversible photoprotection (NPQ fast ), and photoinhibition of PSII (NPQ slow ) using high-throughput, whole-plant measures of chlorophyll fluorescence. In response to cold, the Swedish line had greater values for all traits, and for every trait, large effect QTLs contributed to parental differences. We found one major QTL affecting all traits, as well as unique major QTLs for each trait. Six trait QTLs overlapped with previously published locally adaptive QTLs based on fitness measured in the native environments over 3 years. Our results demonstrate that photosynthetic responses to cold can vary dramatically within a species, and may predominantly be caused by a few QTLs of large effect. Some photosynthesis traits and QTLs probably contribute to local adaptation in this system.

59 BASIC BIOLOGICAL SCIENCES↗

Adaptive X-ray imaging with reinforcement learning

X-ray imaging is a powerful technique to scan samples in a variety of contexts including biological, environmental and materials science, but commonly requires a synchrotron light source to produce X-rays at sufficient intensity. As these facilities are expensive to operate, the available beam time is limited and always in high demand. Particularly if the illuminated samples are sparse, standard raster scanning methods can be time-consuming, with a majority of that time being spent on areas of the image that carry little information. To increase the efficiency and maximize the information gain for a given time budget, we split the scanning process into a series of steps where previous measurements are used to inform the decision making and adapt the exposure distribution at later stages of the sequence. We formulate this task as a reinforcement learning problem where the goal is to produce a sequence of exposure maps that maximize a predefined scalar metric. We demonstrate the potential of this approach in simulations where the adaptive illumination can accelerate the measurement process by up to an order of magnitude compared with standard raster scanning. Finally, we present the first results from deploying the trained agents on an X-ray fluorescence beamline at the Stanford Synchrotron Radiation Lightsource.

Reinforcement Learning↗

Adaptive Reinforcement Learning (ARL) Control of a Multi-port Resonant Converter in UAV Systems

This study presents an adaptive reinforcement learning (ARL) control framework for a multi-port resonant converter used in hybrid unmanned aerial vehicle (UAV) power systems. The converter integrates high-frequency half-bridge input ports connected to a rectified engine–generator set and a battery energy storage system, along with a semi-bridgeless active rectifier supplying the propulsion load. A deep RL agent is trained to dynamically regulate inter-port phase-shift commands in real time based on flight conditions and load power demand. The ARL controller autonomously identifies phase-shift combinations that maximize conversion efficiency while maintaining stable and coordinated power flow, even under rapidly varying operating scenarios. This data-driven approach eliminates the need for explicit system modeling or extensive manual tuning and enables coordinated control among multiple power ports without inter-port communication. Experimental results validate that the ARL based strategy achieves reliable power sharing and consistently high-efficiency operation across diverse UAV operating conditions.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗