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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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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structure Sensitivity and Catalyst Restructuring for CO2 Electro-reduction on Copper

Abstract Cu is the most promising metal catalyst for CO 2 electroreduction (CO 2 RR) to multi-carbon products, yet the structure sensitivity of the reaction and the stability versus restructuring of the catalyst surface under reaction conditions remain controversial. Here, atomic scale simulations of surface energies and reaction pathway kinetics supported by experimental evidence unveil that CO 2 RR does not take place on perfect planar Cu(111) and Cu(100) surfaces but rather on steps or kinks. These planar surfaces tend to restructure in reaction conditions to the active stepped surfaces, with the strong binding of CO on defective sites acting as a thermodynamic driving force. Notably, we identify that the square motifs adjacent to defects, not the defects themselves, as the active sites for CO 2 RR via synergistic effect. We evaluate these mechanisms against experiments of CO 2 RR on ultra-high vacuum-prepared ultraclean Cu surfaces, uncovering the crucial role of step-edge orientation in steering selectivity. Overall, our study refines the structural sensitivity of CO 2 RR on Cu at the atomic level, highlights the self-activation mechanism and elucidates the origin of in situ restructuring of Cu surfaces during the reaction.

Science & Technology - Other Topics↗
DOE OSTI2024

Unveiling Highly Sensitive Active Site in Atomically Dispersed Gold Catalysts for Enhanced Ethanol Dehydrogenation

Developing a desirable ethanol dehydrogenation process necessitates a highly efficient and selective catalyst with low cost. Herein, we show that the “complex active site” consisting of atomically dispersed Au atoms with the neighboring oxygen vacancies (Vo) and undercoordinated cation on oxide supports can be prepared and display unique catalytic properties for ethanol dehydrogenation. The “complex active site” Au–Vo–Zr 3+ on Au 1 /ZrO 2 exhibits the highest H 2 production rate, with above 37,964 mol H 2 per mol Au per hour (385 g H 2 $\text{g}^{-1}_{\text{Au}} \text{h}^{–1}$) at 350 °C, which is 3.32, 2.94 and 15.0 times higher than Au 1 /CeO 2 , Au 1 /TiO 2 , and Au 1 /Al 2 O 3 , respectively. Combining experimental and theoretical studies, we demonstrate the structural sensitivity of these complex sites by assessing their selectivity and activity in ethanol dehydrogenation. Our study sheds new light on the design and development of cost-effective and highly efficient catalysts for ethanol dehydrogenation. Fundamentally, atomic-level catalyst design by colocalizing catalytically active metal atoms forming a structure-sensitive “complex site”, is a crucial way to advance from heterogeneous catalysis to molecular catalysis. Finally, our study advanced the understanding of the structure sensitivity of the active site in atomically dispersed catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unveiling Highly Sensitive Active Site in Atomically Dispersed Gold Catalysts for Enhanced Ethanol Dehydrogenation

Developing a desirable ethanol dehydrogenation process necessitates a highly efficient and selective catalyst with low cost. Herein, we show that the “complex active site” consisting of atomically dispersed Au atoms with the neighboring oxygen vacancies (Vo) and undercoordinated cation on oxide supports can be prepared and display unique catalytic properties for ethanol dehydrogenation. The “complex active site” Au-Vo-Zr 3+ on Au 1 /ZrO 2 exhibits the highest H 2 production rate, with above 37,964 mol H 2 per mol Au per hour (385 g H 2 $g^{-1}_{Au}$ h -1 ) at 350 °C, which is 3.32, 2.94 and 15.0 times higher than Au 1 /CeO 2 , Au 1 /TiO 2 , and Au 1 /Al 2 O 3 , respectively. Combining experimental and theoretical studies, we demonstrate the structural sensitivity of these complex sites by assessing their selectivity and activity in ethanol dehydrogenation. Our study sheds new light on the design and development of cost-effective and highly efficient catalysts for ethanol dehydrogenation. Fundamentally, atomic-level catalyst design by colocalizing catalytically active metal atoms forming a structure-sensitive “complex site”, is a crucial way to advance from heterogeneous catalysis to molecular catalysis. In conclusion, our study advanced the understanding of the structure sensitivity of the active site in atomically dispersed catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis of Non-Nuclear Advanced Controls Testbed Reactor Mockup

The research presented in this report describes our progress in applying stochastic methods and uncertainty quantification, parametric study, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated with Griffin, with the goal of developing a reduced order (surrogate) model which can be rapidly sampled while perturbing multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums, which are controlled by a hybrid proportional, integral and derivative (PID) controller, actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time and $\beta$ from a transient Griffin simulation executed with the improved quasi-static method to provide the kinetic parameters) as inputs to functions which control the CD rotation angle. Using a number of stochastic method approaches, we developed a dual purpose training-surrogate model of the NTP system using polynomial regression. The trained model can be rapidly sampled while simultaneously perturbing various input parameters of the model, such as coefficients on the PID control, or temperature (directly affect the neutron cross section). The surrogate model delivers accurate results orders-of-magnitude faster (minutes, not days) than the base model. Once the base model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs and their effect on the output. For example, coefficients used in the PID control system may vary due to some physical interference, or there may be uncertainty in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters and operational boundaries can be determined. The goal of this work is to support development of an advanced control system to operate CDs in a functioning NTP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

A preliminary investigation into the feasibility of laser ablation U–Pb isotope ratio measurement via all‐faraday cup detection with 10 11 ‐ and 10 13 ‐Ω amplifiers on the Neoma multicollector‐inductively coupled plasma‐mass spectrometer

Rationale Signal detection for uranium–lead (U–Pb) dating of zircon is typically performed via ion counters. Here, we develop a preliminary understanding of the strengths and limitations of faraday‐cup‐based detection. Methods A suite of zircon reference materials and the NIST‐610 glass were sampled using laser ablation followed by U–Pb isotope ratio measurement on a Neoma multicollector‐inductively coupled plasma‐mass spectrometer. Results We were able to produce geologically accurate 207 Pb/ 206 Pb, 206 Pb/ 238 U, and 207 Pb/ 235 U ratios for the NIST‐610 glass and the zircon standards, with ages ranging from ~2.5 Ga to ~337 Ma (TanBrown A, Oracle, 91550, Mud Tank, Temora, and Plešovice). Two of the younger zircon standards examined (94‐35, ~55.6 Ma, and Fish Canyon, 28.6 Ma) yielded accurate 206 Pb/ 238 U but not 207 Pb/ 235 U or 207 Pb/ 206 Pb ratios, whereas the youngest zircon standard (Penglai, ~4.4 Ma) failed for all three ratios of interest. The accuracy and precision of the all‐faraday method are directly tied to signal intensity, with reliable data capable of being produced even when both isotopes in a ratio have signals below ~0.001 V (equivalent to ~62 500 cps on an ion counter). Conclusion The all‐faraday cup multicollection method provides sufficient sensitivity to obtain geologically meaningful U–Pb data, with possible advantages being that laser pit depth‐dependent changes in the observed interelemental fractionation behavior may be easier to correct using a static collector configuration compared to when the ion beam is swept across a single detector while also removing the need for an interdetector‐type calibration. Further work is needed to refine the all‐faraday cup method (e.g., application of background subtraction and common Pb corrections, outlier removal, and interelement as well as down‐hole fractionation corrections), but our initial results demonstrate that the faraday detector method has sufficient sensitivity to warrant further study.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Searching for neutrino polarizability at DUNE

We perform an initial study of DUNE’s sensitivity to enhanced neutrino polarizability within models of light scalar mediators. We identify two possible signatures of polarizability due to neutrino scattering on electrons and due to coherent scattering on argon nuclei. These result in either one or two separated electromagnetic showers, respectively, with no associated hadronic activity. For each signature we compute the signal rates and the relevant backgrounds, obtaining the projected reach of the DUNE near detector. We then compare this with the current astrophysical and terrestrial bounds on light scalar models coupling to neutrinos and/or photons.

Carey, Sam [Wayne State U.] (ORCID:000900029607531↗
DOE OSTI2025

Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening

This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Depth-Resolved X-Ray Nanoimaging of Coherent and Incoherent Energy Transport in Silicon Carbide

Understanding lattice dynamics is crucial for optimizing the process of creating functional structures, such as laser writing of color-center defects. However, existing structural probes have difficulty measuring structural dynamics with submicrometer depth sensitivity. Here, in this study, a depth-resolved ultrafast X-ray nanodiffraction technique is developed to track the lattice dynamics of silicon carbide (SiC) in three dimensions. Upon laser excitation of an aluminum layer that acts as a heat and strain transducer, a specular Bragg peak of SiC shows an overall increase in the X-ray diffraction intensity rather than a peak shift. The relaxation dynamics of the increased intensity are significantly different when probed on and off the Bragg peak. The fast subnanosecond relaxation probed at the maximum of the Bragg peak is a result of the propagation of a coherent strain wave along the depth direction, while a slow relaxation probed at the wings of the Bragg peak reflects a localized incoherent lattice heating. To further visualize these processes, spatiotemporal maps were obtained by scanning the relative position and delay between the laser pump and X-ray probe beams, which capture the propagation of the strain wave, as well as a stationary structural distortion close to the aluminum/SiC interface. These depth-resolved structural measurements disentangle energy dissipation mechanisms in laser-excited SiC, and they open opportunities for finer control of, for example, the formation of optically addressable defect complexes central to quantum information applications.

X-ray nanodiffraction↗
DOE OSTI2024

4D Electrical Resistivity Imaging of Stress Perturbations Induced During High–Pressure Shear Stimulation Tests

Fluid flow through fractured media is typically governed by the distribution of fracture apertures, which are in turn governed by stress. Consequently, understanding subsurface stress is critical for understanding and predicting subsurface fluid flow. Although laboratory–scale studies have established a sensitive relationship between effective stress and bulk electrical conductivity in crystalline rock, that relationship has not been extensively leveraged to monitor stress evolution at the field scale using electrical or electromagnetic geophysical monitoring approaches. In this paper we demonstrate the use time–lapse 3–dimensional (4D) electrical resistivity tomography to image perturbations in the stress field generated by pressurized borehole packers deployed during shear–stimulation attempts in a 1.25 km deep metamorphic crystalline rock formation.

58 GEOSCIENCES↗
DOE OSTI2025

Revealing the loss mechanisms of a 3D superconducting microwave cavity for use in a dark matter search

Superconducting microwave cavities have found applications in many areas including quantum computing, particle accelerators, and dark matter searches. Their extremely high quality factors translate to very narrow bandwidth, which makes them key components of sensitive detectors. In this study, we aim to understand the loss mechanisms of an aluminium cavity, with a fundamental mode frequency of about 2.5123 GHz, and how they change as the cavity material transitions from the superconducting to normal state. We found that at temperatures not much lower than the transition temperature $T_c$, losses are dominated by quasiparticle excitations and are well described by the Bardeen–Cooper–Schrieffer theory. The exponential decrease of the quasiparticle density below $T_c$ results in a 1000-fold increase of the quality factor, as well as a shift of the resonance frequency due to the change of the kinetic inductance of the superconductor. At very low temperatures, losses due to two-level systems begin to dominate giving a peak in the quality factor of about 2.76 x 10 7 at 130 mK. Understanding the loss mechanisms is invaluable, as the working temperature of the cavity may vary during operation regardless of its application.

Physics - Physics of elementary particles and fiel↗
DOE OSTI2026

Jet charge with global event shapes: Probing quark flavor dynamics

We propose measuring the jet electric charge of jet regions, defined within the framework of global event shapes, as a probe of quark flavor dynamics within the nucleon and the hadronization process. In particular, we consider a measurement of the jet region charge while simultaneously keeping track of the energy flow throughout the event, as characterized by the global event shape. As a concrete example, we focus on the measurement of the (Q), the jet charge of the jet region (𝐽) defined within the framework of the 1-Jettiness global event shape (𝜏 1 ) for the Deep Inelastic Scattering (DIS) process, 𝑒 − +𝑝→𝑒 − +𝐽+𝑋, with unpolarized or longitudinally polarized protons. The 1-Jettiness distribution, binned according to jet charge, allows for enhanced quark flavor separation of the initial state unpolarized or polarized PDFs. On the other hand, the jet charge distribution binned by 1-Jettiness can serve as a probe of quark flavor dynamics in the final state hadronization process. We derive a factorization theorem for simultaneous measurements of 𝜏 1 and Q in the resummation region, 𝜏 1 ≪𝑃 𝐽 𝑇 , where 𝑃 𝐽 𝑇 denotes the transverse momentum of the jet region. The correlation between the jet region charge and the charge of the struck quark is expected to be the strongest in the resummation region. The factorization theorem contains a new universal , generalizing the standard jet function to include a jet charge measurement. Therefore these universal functions can be extracted from a global analysis of N-jettiness and thrust at 𝑒 + ⁢𝑒 − colliders. We provide simulation studies to demonstrate the sensitivity of the 1-Jettiness jet charge observable to quark flavor dynamics in nucleon structure and explore the possibility of probing the final state hadronization process. This observable is well-suited for applications with existing HERA data and the future Electron-Ion Collider (EIC).

Mantry, Sonny [University of North Georgia, Dahlon↗
DOE OSTI2026

Charm quark evolution in the early stages of heavy-ion collisions

Heavy quarks are predominantly generated at the initial stage of relativistic heavy-ion collisions such that heavy flavor observables have the potential to provide information on the pre-equilibrium medium dynamics. In this study, we investigate the sensitivity of D-meson $R_{AA}$ and $v_2$ to early-time charm quark dynamics in Pb+Pb collisions at $\sqrt{s_{NN}}$=5.02 TeV. We employ the IP-Glasma+MUSIC+UrQMD framework to model the evolution of the bulk medium. Charm quarks are generated using PYTHIA with nuclear parton distribution functions and evolved using Langevin dynamics within MARTINI. We observe that even though there is significant momentum broadening in the earliest stage, D-meson $R_{AA}$ and $v_2$ are only weakly sensitive to pre-equilibrium interactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

4D Multimodal Co-attention Fusion Network with Latent Contrastive Alignment for Alzheimer’s Diagnosis

Multimodal neuroimaging provides complementary structural and functional insights into both human brain organization and disease-related dynamics. Recent studies demonstrate enhanced diagnostic sensitivity for Alzheimer’s disease (AD) through synergistic integration of neuroimaging data (e.g., sMRI, fMRI) with tabular data (e.g., behavioral and cognitive tests). However, the intrinsic heterogeneity across modalities (e.g., 4D spatiotemporal fMRI dynamics vs. 3D anatomical sMRI structure) presents critical challenges for discriminative feature fusion, often leading to information loss or biased fusion. To bridge this gap, we propose M2M-AlignNet: a multimodal co-attention network with latent alignment for early AD diagnosis using sMRI and fMRI. At the core of our approach is a multi-patch-to-multi-patch (M2M) contrastive loss function that quantifies and reduces representational discrepancies via weighted patch correspondence, explicitly aligning fMRI components across brain regions with their sMRI structural substrates without one-to-one constraints. Additionally, we propose a latent-as-query co-attention module to autonomously discover fusion patterns, circumventing modality prioritization biases while minimizing feature redundancy. We conduct extensive experiments to confirm the effectiveness of our method and highlight the correspondence between fMRI and sMRI as AD biomarkers.

Wei, Yuxiang [Georgia Institute of Technology]↗
DOE OSTI2024

Influence of Local Water Vapor Analysis Uncertainty on Ensemble Forecasts of Tropical Cyclogenesis Using Hurricane Irma (2017) as a Testbed

Abstract Tropical cyclone formation is known to require abundant water vapor in the lower to middle troposphere within the incipient disturbance. In this study, we assess the impacts of local water vapor analysis uncertainty on the predictability of the formation of Hurricane Irma (2017). To this end, we reduce the magnitude of the incipient disturbance’s water vapor perturbations obtained from an ensemble-based data assimilation system that constrained moisture by assimilating all-sky infrared and microwave radiances. Five-day ensemble forecasts are initialized two days before genesis using each set of modified analysis perturbations. Growth of convective differences and intensity uncertainty are evaluated for each ensemble forecast. We observe that when initializing an ensemble forecast with only moisture uncertainty within the incipient disturbance, the resulting intensity uncertainty at every lead time exceeds half that of an ensemble containing initial perturbations to all variables throughout the domain. Although ensembles with different initial moisture uncertainty amplitudes reveal a similar pathway to genesis, uncertainty in genesis timing varies substantially across ensembles since moister members exhibit earlier spinup of the low-level vortex. These differences in genesis timing are traced back to the first 6–12 h of integration, when differences in the position and intensity of mesoscale convective systems across ensemble members develop more quickly with greater initial moisture uncertainty. In addition, the rapid growth of intensity uncertainty may be greatly modulated by the diurnal cycle. Ultimately, this study underscores the importance of targeting the incipient disturbance with high spatiotemporal water vapor observations for ingestion into data assimilation systems. Significance Statement Hurricanes form from clusters of thunderstorms that organize into a coherent system. One of the key ingredients for the formation process is an abundance of moisture. In this study, we test the sensitivity of hurricane formation to the initial moisture content in the vicinity of the cluster of thunderstorms that would become Hurricane Irma (2017). To do so, we initialize sets of forecasts each having a different variability of initial moisture content within the embryonic disturbance. Our results show that the predictability of hurricane formation is highly dependent on the uncertainty of the moisture content within the initial disturbance. Consequently, more high-quality observations of the moisture within the precursor disturbances to hurricanes are expected to improve forecasts of their formation.

Hartman, Christopher M.↗
DOE OSTI2026

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Multibody for Everybody (M4E): A Symbolic Dynamics Modeling Tool with Applications in Simulation, Control, and Optimization

Developing the analytical model of a multibody system is often the initial step in control and optimization. The analytical model (equations of motion) describes a system’s time evolution under specified forcing conditions. Although developing these equations is easy for simple systems, this process becomes more complex for systems composed of multiple bodies. Deriving equations of motion for complex multibody systems requires specialized expertise in multibody dynamics, is time-consuming, and is susceptible to error. To address this issue, this paper presents an open-source, easy-to-use, systematic framework to derive symbolic equations of motion in both Python and MATLAB using the joint coordinate formulation. This formulation results in a set of ordinary differential equations that use the minimum set of coordinates needed to model a system. The symbolic representation provides better insight into the influence of design parameters on system performance, facilitates sensitivity analysis and parameter studies, and supports direct implementation of control and optimization routines. The tool enables numerical simulation for specified parameter sets, is modular for straightforward integration with other tools and libraries, and allows incorporation of hydrodynamics, mooring, and other external forces. The result is a reproducible, extensible pipeline for modeling, simulation, and design of complex multibody systems. The proposed tool is versatile and can be applied to domains such as robotics, control, and design. In addition, we integrated external libraries that provide capabilities for modeling offshore systems such as underwater robots and marine energy converters.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Optimization of the light detection system of the ICARUS detector

The Short Baseline Neutrino (SBN) Program at Fermilab is designed to investigate short-baseline neutrino oscillations and test the hypothesis of sterile neutrinos, motivated by several experimental anomalies observed over the past decades. Within this program, the ICARUS experiment plays a key role. It employs the world’s largest Liquid Argon Time Projection Chamber (LArTPC) and serves as the farthest and most sensitive SBN detector for studying muon and electron neutrino oscillations. A crucial subsystem of the ICARUS detector is the Light Detection System (LDS), which captures the prompt scintillation light produced by neutrino interactions in the 600-ton active liquid Argon volume. This system provides precise timing information that is essential for event reconstruction, the trigger system, and cosmic background rejection. The LDS is composed of 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), operating under cryogenic conditions ($\sim 87 \ K$) inside the detector’s cryostats. During the detector’s operation at FNAL, a degradation in PMT gain has been observed, attributed to aging under low-temperature conditions. In collaboration with ICARUS teams from INFN Pavia and Catania, I developed an experimental setup to study the temperature-dependent behavior of the PMTs, performing gain measurements both at room temperature and down to $-70°C$ using a climatic chamber at INFN Catania. The results indicate that while the PMTs maintain stable gain at room temperature, a significant and permanent gain reduction occurs at low temperatures. Although $-70°C$ is still warmer than liquid Argon temperatures, the findings clearly demonstrate a gain-dependent performance degradation. The thesis also discusses mitigation strategies implemented in the ICARUS detector to address this issue and presents a simplified model to describe and simulate the observed behavior.

Saia, Clara [Catania U.] (ORCID:0009000464102417)↗
DOE OSTI2024

Future projections of storm surge in Hurricane Katrina and sensitivity to meteorological forcing resolution

In this study, we investigated whether and how the storm surge induced by Hurricane Katrina could change if it occurs in a future warmer climate, and the sensitivity of the changes to atmospheric forcing resolution. Climate model simulations of Hurricane Katrina at 27 km, 4.5 km, and 3 km resolutions were used to drive storm surge simulations in historical and future climates using the ADvanced CIRCulation (ADCIRC) model. We found that peak surge height increased significantly in the future with all forcing resolutions. However, the future projection is 22% greater in the 3 km forcing, typical of regional climate models, compared to the 27 km forcing, typical of state-of-the-art global climate models. Additionally, the spatial extent of the future change is highly sensitive to forcing resolution, extending most broadly under the 27 km forcing. Furthermore, we found that storm surge duration decreases in the future with all forcing resolutions due to increasing TC translation speed and decreasing ocean lifetime. However, the future change in the surge duration is sensitive to the forcing resolution, decreasing by 31% in the 27 km forcing and 6% in the 3 km forcing.

54 ENVIRONMENTAL SCIENCES↗