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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Performance of the CMS Zero Degree Calorimeters in pPb collisions at the LHC

The two Zero Degree Calorimeters (ZDCs) of the CMS experiment are located at ± 140 m from the collision point and detect neutral particles in the |η| > 8.3 pseudorapidity region. This paper presents a study on the performance of the ZDC in the 2016 pPb run. The response of the detectors to ultrarelativistic neutrons is studied using in-depth Monte Carlo simulations. A method of signal extraction based on template fits is presented, along with a dedicated calibration procedure. A deconvolution technique for the correction of overlapping collision events is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Electronics for the far-forward CMS muon detector upgrade, ME0

Abstract With the High Luminosity upgrade of the Large Hadron Collider (LHC) we expect increased instantaneous luminosities up to 7.5 × 10 34 cm −2 s −1 , or five times more than the original values. In order to maintain performance of the Compact Muon Solenoid (CMS) experiment under these conditions, ME0 is one of three new muon sub-detectors being added, along with GE1/1 and GE2/1, which use the triple Gas Electron Multiplier (GEM) technology. ME0 is designed to cover the forward region of 2.0 < | η | < 2.8, thus improving muon reconstruction at high background rates by supplementing other overlapping muon subsystems up to | η | = 2.4, while also extending the acceptance for the first time to | η | = 2.8. The readout electronics for ME0 must be designed to accommodate high data rates and be sufficiently radiation hard to operate close to the beamline. The Optohybrid (OH) board for ME0, which reads out data from the front-end VFAT3b ASICs, has therefore been designed to operate without an FPGA (unlike GE1/1 and GE2/1) to ensure radiation hardness. The ME0 OH uses the radiation-hard CERN-designed lpGBT ASIC and VTRx+ optical transceiver module for high bandwidth optical links up to 10.24 Gb/s. The backend system is based on the ATCA standard. The design and development status of the readout electronics for ME0 is presented, along with recent results from integration tests performed using the first prototypes.

Instruments & Instrumentation↗
DOE OSTI2023

Performance of the local reconstruction algorithms for the CMS hadron calorimeter with Run 2 data

A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015–2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A method to observe field-region oxide charge and inter-electrode isolation from CV-characteristics of n-on-p devices

Abstract N-on-psilicon sensors will be utilized in the Compact Muon Solenoid (CMS) detector's tracker and High Granularity Calorimeter (HGCAL) in the High Luminosity upgrade of the Large Hadron Collider (HL-LHC). Among their several advantages in terms of radiation hardness over the traditionalp-on-nsensors in the extreme radiation environment of the HL-LHC are electron collection instead of holes and overlapping maxima of weighting and electric fields at the charge-collecting electrodes. The disadvantage of the multi-channel SiO 2 -passivatedn-on-psensors is the generation of an inversion layer under the Si/SiO 2 -interface by a positive interface-oxide-charge (N ox ) that at high densities can compromise the position resolution by creating a conduction channel between the electrodes. This issue is typically addressed by including additional isolnts (p-stp,p-spray) between n + -electrodes. Focusing on the guard-ring regions ofn-on-psensors where no isolation implants are applied between the electrodes, a capacitance-voltage (CV) characterization study of both 6-inch wafer test diodes and 8-inch HGCAL prototype and pre-series sensors showed a distinct threshold voltage (V th,iso ) in theCV-characteristics of a biased n + -electrode when its enclosing guard-ring was left floating. When reproduced by simulations, the measuredV th,iso was found to contain information on the field-regionN ox and indicate the threshold where the two electrodes become electrically isolated by the influence of the reverse bias voltage. Together with previous studies on the inter-electrode isolation of irradiatedn-on-psensors, the results indicate that position sensitiven-on-psensors without isolation implants may be feasible in future HEP experiments.

Instruments & Instrumentation↗
DOE OSTI2022

Boosting climate change mitigation potential of perennial lignocellulosic crops grown on marginal lands

Nitrogen fertilizer (N F ) is a major uncertainty surrounding the greenhouse gas (GHG) emissions of lignocellulosic biofuels. NF enhances agronomic yields and soil C inputs via plant litters, but results in soil organic carbon (SOC) decomposition, soil N 2 O fluxes, and a large fossil energy footprint. Thus, whether NF is beneficial or detrimental to the GHG mitigation of biofuels is unknown. Here, we show the potential GHG mitigation of fertilizing switchgrass (Panicum virgatum) at the NF rate that minimizes net GHG emissions across 7.1 million ha of marginal lands in the Midwest US, with long-term production advantages surpassing emitted GHG by 0.66 Mg CO 2 e ha –1 yr –1 on the aggregate. Marginal lands limited by poor N fertility could see a much greater benefit, but not SOC-rich lands, limited by low precipitation, or short growing seasons. The objectives of maximizing yield and minimizing GHG overlap only in a few environments, suggesting that maximum yield will reduce the climate benefit of cellulosic biofuels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions

Wetlands are the single largest natural source of atmospheric methane (CH 4 ), contributing approximately 30% of total surface CH 4 emissions, and they have been identified as the largest source of uncertainty in the global CH 4 budget based on the most recent Global Carbon Project CH 4 report. High uncertainties in the bottom–up estimates of wetland CH 4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH 4 emissions from space. In fact, there are large disagreements between bottom–up estimates versus top–down estimates inferred from inversion of atmospheric CH 4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom–up estimates of global wetland CH 4 emissions, as well as how they are used in top–down inversions. These bottom–up estimates, using (1) empirical biogeochemical modeling (e.g. WetCHARTs: 125–208 TgCH 4 yr -1 ); (2) process-based biogeochemical modeling (e.g. WETCHIMP: 190 ± 39 TgCH 4 yr -1 ); and (3) data-driven machine learning approach (e.g. UpCH4: 146 ± 43 TgCH 4 yr -1 ). Bottom–up estimates are subject to significant uncertainties (~80 Tg CH 4 yr -1 ), and the ranges of different estimates do not overlap, further amplifying the overall uncertainty when combining multiple data products. These substantial uncertainties highlight gaps in our understanding of wetland CH 4 biogeochemistry and wetland inundation dynamics. Major tropical and arctic wetland complexes are regional hotspots of CH 4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top–down inversions to improve bottom–up estimates. Recent advances in surface measurements of CH 4 fluxes (e.g. FLUXNET-CH 4 ) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom–up estimates of wetland CH 4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH 4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH 4 observations directed at wetlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Heat metrics and thresholds reshape population exposure and inequality signals

Extreme heat is intensifying worldwide, yet estimates of heat hazard and exposure inequality depend on both the heat metric and how extreme days are defined. Using summer 2022 across the Mediterranean, we quantify population heat exposure with four metrics—land surface temperature (LST), air temperature (Ta), heat index (HI), and wet-bulb globe temperature (WBGT)—under absolute (fixed-value) and relative (anomaly-based) thresholds. Under absolute thresholds, total heat exposure differs by more than two orders of magnitude across metrics (31.3 billion person-days for Ta vs 0.3 billion for HI). Geographic hotspots also diverge: WBGT concentrates in humid coastal North Africa (e.g. the Nile Delta), whereas Ta and LST are more widespread. Under relative thresholds, exposure totals converge and cross-metric hotspot agreement increases (e.g. Ta–WBGT top-tercile overlap increases from 10.7% to 29.0%), shifting hotspots toward densely populated southern Europe. Crucially, the exposure–deprivation relationship also reverses across threshold frameworks: absolute thresholds concentrate exposure in more deprived North Africa and the Middle East, whereas relative thresholds shift the burden toward less-deprived European cities. This sensitivity is decision-relevant: city rankings based on WBGT exposure duration are almost completely reordered when switching threshold frameworks. Threshold choice therefore systematically reshapes hotspot patterns and inequality signals. Reporting both absolute and relative exposures can reveal hidden hotspots and support more targeted heat-risk monitoring and intervention planning.

Mediterranean↗
DOE OSTI2022

High harmonic generation in mixed XUV and NIR fields at a free-electron laser

Abstract We present the results of an experiment investigating the generation of high-order harmonics by a femtosecond near-infrared (NIR) laser pulse in the presence of an extreme ultraviolet (XUV) field provided by a free-electron laser (FEL), a process referred to as XUV-assisted high-order harmonic generation (HHG). Our experimental findings show that the XUV field can lead to a small enhancement in the harmonic yield when the XUV and NIR pulses overlap in time, while a strong decrease of the HHG yield and a red shift of the HHG spectrum is observed when the XUV precedes the NIR pulse. The latter observations are in qualitative agreement with model calculations that consider the effect of a decreased number of neutral emitters but are at odds with the predicted effect of the correspondingly increased ionization fraction on the phase matching. Our study demonstrates the technical feasibility of XUV-assisted HHG experiments at FELs, which may provide new avenues to investigate correlation-driven electron dynamics as well as novel ways to study and control propagation effects and phase matching in HHG.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Proximity-enhanced valley Zeeman splitting at the WS 2 /graphene interface

The valley Zeeman physics of excitons in monolayer transition metal dichalcogenides provides valuable insight into the spin and orbital degrees of freedom inherent to these materials. Being atomically-thin materials, these degrees of freedom can be influenced by the presence of adjacent layers, due to proximity interactions that arise from wave function overlap across the 2D interface. Here, we report 60 T magnetoreflection spectroscopy of the A- and B- excitons in monolayer WS 2 , systematically encapsulated in monolayer graphene. While the observed variations of the valley Zeeman effect for the A- exciton are qualitatively in accord with expectations from the bandgap reduction and modification of the exciton binding energy due to the graphene-induced dielectric screening, the valley Zeeman effect for the B- exciton behaves markedly different. We investigate prototypical WS 2 /graphene stacks employing first-principles calculations and find that the lower conduction band of WS 2 at the <?CDATA $K/K^{^{\prime}}$?> K / K ′ valleys (the <:tex-math><?CDATA $\mathrm{CB}^-$?> C B − band) is strongly influenced by the graphene layer on the orbital level. Specifically, our detailed microscopic analysis reveals that the conduction band at the Q point of WS 2 mediates the coupling between <?CDATA $\mathrm{CB}^-$?> C B − and graphene due to resonant energy conditions and strong coupling to the Dirac cone. This leads to variations in the valley Zeeman physics of the B- exciton, consistent with the experimental observations. Our results therefore expand the consequences of proximity effects in multilayer semiconductor stacks, showing that wave function hybridization can be a multi-step energetically resonant process, with different bands mediating the interlayer interactions. Such effects can be further exploited to resonantly engineer the spin-valley degrees of freedom in van der Waals and moiré heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Giant resistance switch in twisted transition metal dichalcogenide tunnel junctions

Resistance switching in multilayer structures are typically based on materials possessing ferroic orders. Here, in this work, we predict an extremely large resistance switching based on the relative spin–orbit splitting in twisted transition metal dichalcogenide (TMD) monolayers tunnel junctions. Because of the valence band spin splitting which depends on the valley index in the Brillouin zone, the perpendicular electronic transport through the junction depends on the relative reciprocal space overlap of the spin-dependent Fermi surfaces of both layers, which can be tuned by twisting one layer. Our quantum transport calculations reveal a switching resistance larger than 10 6 % when the relative alignment of TMDs goes from 0° to 60° and when the angle is kept fixed at 60° and the Fermi level is varied. By creating vacancies, we evaluate how inter-valley scattering affects the efficiency and find that the resistance switching remains large (10 4 %) for typical values of vacancy concentration. Not only should this resistance switching be observed at room temperature due to the large spin splitting, but our results also show how twist angle engineering and control of van der Waals heterostructures could be used for next-generation memory and electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Linear gyrokinetic simulations of reversed shear Alfvén eigenmodes and ion temperature gradient modes in DIII-D tokamak

Abstract Global linear gyrokinetic simulations using realistic DIII-D tokamak geometry and plasma profiles find co-existence of unstable reversed shear Alfvén eigenmodes (RSAE) with low toroidal mode number n and electromagnetic ion temperature gradient (ITG) instabilities with higher toroidal mode number n . For intermediate n = [10, 12], RSAE and ITG co-exist and overlap weakly in the radial domain with similar growth rates but different real frequencies. Both RSAE and ITG growth rates decrease less than 5% when compressible magnetic perturbations are neglected in the simulations. The ITG growth rates increase less than 7% when fast ions are not included in the simulations. Finally, the effects of trapped electrons on the RSAE are negligible.

Physics↗
DOE OSTI2022

Layered complex networks as fluctuation amplifiers

Abstract In complex networked systems theory, an important question is how to evaluate the system robustness to external perturbations. With this task in mind, I investigate the propagation of noise in multi-layer networked systems. I find that, for a two layer network, noise originally injected in one layer can be strongly amplified in the other layer, depending on how well-connected are the complex networks in each layer and on how much the eigenmodes of their Laplacian matrices overlap. These results allow to predict potentially harmful conditions for the system and its sub-networks, where the level of fluctuations is important, and how to avoid them. The analytical results are illustrated numerically on various synthetic networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Joint ptycho-tomography with deep generative priors

Abstract Joint ptycho-tomography is a powerful computational imaging framework to recover the refractive properties of a 3D object while relaxing the requirements for probe overlap that is common in conventional phase retrieval. We use an augmented Lagrangian scheme for formulating the constrained optimization problem and employ an alternating direction method of multipliers (ADMM) for the joint solution. ADMM allows the problem to be split into smaller and computationally more efficient subproblems: ptychographic phase retrieval, tomographic reconstruction, and regularization of the solution. We extend our ADMM framework with plug-and-play (PnP) denoisers by replacing the regularization subproblem with a general denoising operator based on machine learning. While the PnP framework enables integrating such learned priors as denoising operators, tuning of the denoiser prior remains challenging. To overcome this challenge, we propose a denoiser parameter to control the effect of the denoiser and to accelerate the solution. In our simulations, we demonstrate that our proposed framework with parameter tuning and learned priors generates high-quality reconstructions under limited and noisy measurement data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DiffLense: a conditional diffusion model for super-resolution of gravitational lensing data

Abstract Gravitational lensing data is frequently collected at low resolution due to instrumental limitations and observing conditions. Machine learning-based super-resolution techniques offer a method to enhance the resolution of these images, enabling more precise measurements of lensing effects and a better understanding of the matter distribution in the lensing system. This enhancement can significantly improve our knowledge of the distribution of mass within the lensing galaxy and its environment, as well as the properties of the background source being lensed. Traditional super-resolution techniques typically learn a mapping function from lower-resolution to higher-resolution samples. However, these methods are often constrained by their dependence on optimizing a fixed distance function, which can result in the loss of intricate details crucial for astrophysical analysis. In this work, we introduce DiffLense , a novel super-resolution pipeline based on a conditional diffusion model specifically designed to enhance the resolution of gravitational lensing images obtained from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Our approach adopts a generative model, leveraging the detailed structural information present in Hubble space telescope (HST) counterparts. The diffusion model, trained to generate HST data, is conditioned on HSC data pre-processed with denoising techniques and thresholding to significantly reduce noise and background interference. This process leads to a more distinct and less overlapping conditional distribution during the model’s training phase. We demonstrate that DiffLense outperforms existing state-of-the-art single-image super-resolution techniques, particularly in retaining the fine details necessary for astrophysical analyses.

Computer Science↗
DOE OSTI2025

Comparing multi-source urban flood indicators: satellite, simulation, and citizen-reported data

Urban flooding arises from complex mechanisms, making it challenging to capture accurately with a single detection method. This study evaluates three complementary approaches to detect flooding across three Chicago neighborhoods: (i) Sentinel-1 synthetic aperture radar (SAR), offering weather-independent, high-resolution (10 m) imagery of surface inundation; (ii) the storm water management model (SWMM), simulating combined sewer overflow and drainage performance; and (iii) citizen-generated 311 service requests, capturing observed flooding impacts. By analyzing six storms ranging from severe to mild, we examine how each source uniquely contributes to identifying urban flood events. SAR imagery effectively identifies standing water but can miss brief flooding due to satellite revisit constraints. SWMM provides detailed insights into system-wide drainage behavior yet may underestimate localized street-level flooding. Meanwhile, 311 calls reflect real-world flooding impacts but are vulnerable to underreporting. Statistical overlap analysis highlights chronic flood hotspots repeatedly identified across multiple detection methods, indicating persistent infrastructure and topographic vulnerabilities. Temporal analysis further reveals that while SWMM flooding aligns closely with rainfall peaks, 311 calls typically precede or persist beyond these peaks. Our findings emphasize the value of using satellite observations, hydrological modeling, and resident-reported data in a complementary manner to better interpret patterns in flood timing, severity, and spatial distribution—providing insights that can inform targeted infrastructure improvements and contribute to urban flood resilience planning.

311↗
DOE OSTI2023

Divergent selection and climate adaptation fuel genomic differentiation between sister species of Sphagnum (peat moss)

Abstract Background and Aims New plant species can evolve through the reinforcement of reproductive isolation via local adaptation along habitat gradients. Peat mosses (Sphagnaceae) are an emerging model system for the study of evolutionary genomics and have well-documented niche differentiation among species. Recent molecular studies have demonstrated that the globally distributed species Sphagnum magellanicum is a complex of morphologically cryptic lineages that are phylogenetically and ecologically distinct. Here, we describe the architecture of genomic differentiation between two sister species in this complex known from eastern North America: the northern S. diabolicum and the largely southern S. magniae. Methods We sampled plant populations from across a latitudinal gradient in eastern North America and performed whole genome and restriction-site associated DNA sequencing. These sequencing data were then analyzed computationally. Key Results Using sliding-window population genetic analyses we find that differentiation is concentrated within ‘islands’ of the genome spanning up to 400 kb that are characterized by elevated genetic divergence, suppressed recombination, reduced nucleotide diversity and increased rates of non-synonymous substitution. Sequence variants that are significantly associated with genetic structure and bioclimatic variables occur within genes that have functional enrichment for biological processes including abiotic stress response, photoperiodism and hormone-mediated signalling. Demographic modelling demonstrates that these two species diverged no more than 225 000 generations ago with secondary contact occurring where their ranges overlap. Conclusions We suggest that this heterogeneity of genomic differentiation is a result of linked selection and reflects the role of local adaptation to contrasting climatic zones in driving speciation. This research provides insight into the process of speciation in a group of ecologically important plants and strengthens our predictive understanding of how plant populations will respond as Earth’s climate rapidly changes.

58 GEOSCIENCES↗
DOE OSTI2023

White-tailed deer responses to acoustic predator cues are contingent upon past land use and contemporary fire regime

Prey can assess the immediate risk of predation by detecting cues of predator presence, and it is expected that prey should invest in costly antipredator behaviors when a cue of predator presence is detected. Features of the habitat in which the cue is detected, such as vegetative concealment, serve as indirect cues of risk and can mediate how prey respond to direct cues of predator presence. Past agricultural land use and contemporary fire regimes are common disturbances that may modify prey perceptions of risk and could, therefore, alter prey responses to direct cues of predator presence. Here we examined whether the overlap of these two disturbances affected white-tailed deer (Odocoileus virginianus) responses to cues of predator presence by measuring deer vigilance and foraging bout duration in response to coyote (Canis latrans) vocalizations across 20 woodlands that varied in past land use and contemporary fire regime. Frequent fire regimes consistently increased deer visibility to predators across both land-use history contexts. Deer exhibited no behavioral response to the predator cue in habitats containing infrequent fire regimes or agricultural legacies. Deer responded to the cue in frequently burned woodlands without agricultural legacies through increased vigilance and time spent at a foraging location. These findings reveal that land-use legacies and contemporary fire regimes can mediate how prey respond to direct cues of risk. They also suggest that prey may balance the uncertainty associated with cues of predation risk with the urgency of responding to a potential attack by being vigilant and remaining in place.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Integrating functional scoring and regulatory data to predict the effect of non-coding SNPs in a complex neurological disease

Abstract Most SNPs associated with complex diseases seem to lie in non-coding regions of the genome; however, their contribution to gene expression and disease phenotype remains poorly understood. Here, we established a workflow to provide assistance in prioritising the functional relevance of non-coding SNPs of candidate genes as susceptibility loci in polygenic neurological disorders. To illustrate the applicability of our workflow, we considered the multifactorial disorder migraine as a model to follow our step-by-step approach. We annotated the overlap of selected SNPs with regulatory elements and assessed their potential impact on gene expression based on publicly available prediction algorithms and functional genomics information. Some migraine risk loci have been hypothesised to reside in non-coding regions and to be implicated in the neurotransmission pathway. In this study, we used a set of 22 non-coding SNPs from neurotransmission and synaptic machinery-related genes previously suggested to be involved in migraine susceptibility based on our candidate gene association studies. After prioritising these SNPs, we focused on non-reported ones that demonstrated high regulatory potential: (1) VAMP2_rs1150 (3′ UTR) was predicted as a target of hsa-mir-5010-3p miRNA, possibly disrupting its own gene expression; (2) STX1A_rs6951030 (proximal enhancer) may affect the binding affinity of zinc-finger transcription factors (namely ZNF423) and disturb TBL2 gene expression; and (3) SNAP25_rs2327264 (distal enhancer) expected to be in a binding site of ONECUT2 transcription factor. This study demonstrated the applicability of our practical workflow to facilitate the prioritisation of potentially relevant non-coding SNPs and predict their functional impact in multifactorial neurological diseases.

Felício, Daniela↗