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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 289 records · Page 16

Using Molecular Structure to Tune Intrachain and Interchain Charge Transport in Indacenodithiophene-Based Copolymers

Here, in this work, we compare two structurally near-amorphous rigid-rod polymers-poly(indacenodithiophene-co-benzothiadiazole), p(IDT-BT), and poly(indacenodithiophene-co-benzopyrollodione), p(IDT-BPD)-with orders of magnitude different mobilities to understand the effect charge carrier intrachain delocalization has on electronic transport. Quantum chemical calculations show that p(IDT-BPD) has a barrier to torsion that is significantly lower than that of p(IDT-BT) and is thus more likely to have reduced conjugation lengths. We utilize absorption and photoluminescence spectroscopy to characterize energetic disorder and show that p(IDT-BPD) has higher energetic disorder. Charge modulation spectroscopy (CMS) and model calculations are used to show that charge carriers are substantially delocalized in p(IDT-BT) and occupy near-uniform energetic environments. We find that mobility activated hopping barriers are similar in these two materials. Electronic structure calculations show that both intrachain and interchain couplings of monomer units are poor enough in p(IDT-BPD) that charge carriers collapse to single IDT units and transport via a through-space tunneling mechanism. This work highlights the remarkable charge transport properties of p(IDT-BT) by showing that high mobilities are achievable on device-relevant length scales with only 1D carrier delocalization.

36 MATERIALS SCIENCE↗

Experiments and Simulations of the Dusty Properties of Hypervelocity Impact Plasmas

Hypervelocity impacts, referring to impacts occurring at several times the speed of sound in the target, result in inertial stresses greatly exceeding the material strength and produce behavior that is not fully understood. These impact phenomena are seen in space through impacts of orbital debris and meteoroids on spacecraft and airless natural bodies but can also be produced in laboratory environments using light-gas guns and electrostatic dust accelerators. When a hypervelocity impact occurs, plasma is generated both from thermal ionization and from pressure ionization, producing a wide range of plasma densities depending on the impactor’s velocity. This plasma is initially formed in the warm dense matter (WDM) regime and governed by high energy density (HED) hydrodynamics before it rapidly expands and dissipates, spanning many orders of magnitude in density and length scale. The plasma can also contain a dust component, which is particularly relevant for the lower-velocity range of hypervelocity impacts with parameters that are particularly relevant to Tokamak plasmas. Therefore, the properties and dynamics of these plasmas cannot be fully characterized without considering dusty plasma effects, which are ubiquitous but poorly understood.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimizing Ventilation Using Low-Cost Sensors to Improve Health, Safety, and Energy Efficiency

Air is the primary carrier of hazards within a space, whether it be hazardous bi-products of research activities or airborne pathogens. As a result, building ventilation is the primary defense against unseen airborne hazards. Critical laboratory facilities already demand the need for effective mitigation of exposure to research-related, airborne hazards, providing a proving ground for effective ventilation strategies that optimize safety of occupants and reduce energy use. The heart of smart laboratory building operation is dynamic, analytics-based ventilation, which requires an intimate knowledge of building environmental conditions achieved through contaminant-detection systems. Unfortunately, currently available contaminant-detection solutions are expensive, elaborate systems that raise barriers for building managers on a limited budget. Through the successful deployment of a novel low-cost, modular sensor technology, we have developed a demand-control ventilation protocol effective in improving safety and reducing energy in the critical laboratory environment. In this session, we will highlight best practices and lessons learned through this deployment that can be applied beyond laboratories without breaking the bank. This paper describes a low-cost solution for providing a safe, healthy building environment and reducing energy use through effective, efficient ventilation.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance

Bacterial adaptation to antibiotic combinations depends on the joint inhibitory effects of the two drugs (drug interaction [DI]) and how resistance to one drug impacts resistance to the other (collateral effects [CE]). Here we model these evolutionary dynamics on two-dimensional phenotype spaces that leverage scaling relations between the drug-response surfaces of drug-sensitive (ancestral) and drug-resistant (mutant) populations. We show that evolved resistance to the component drugs – and in turn, the adaptation of growth rate – is governed by a Price equation whose covariance terms encode geometric features of both the two-drug-response surface (DI) in ancestral cells and the correlations between resistance levels to those drugs (CE). Within this framework, mean evolutionary trajectories reduce to a type of weighted gradient dynamics, with the drug interaction dictating the shape of the underlying landscape and the collateral effects constraining the motion on those landscapes. We also demonstrate how constraints on available mutational pathways can be incorporated into the framework, adding a third key driver of evolution. Our results clarify the complex relationship between drug interactions and collateral effects in multidrug environments and illustrate how specific dosage combinations can shift the weighting of these two effects, leading to different and temporally explicit selective outcomes.

Gjini, Erida↗

Rotor blade imbalance fault detection for variable-speed marine current turbines via generator power signal analysis

Marine hydrokinetic (MHK) turbines extract renewable energy from oceanic environments. However, due to the harsh conditions that these turbines operate in, system performance naturally degrades over time. Thus, ensuring efficient condition-based maintenance is imperative towards guaranteeing reliable operation and reduced costs for marine hydrokinetic power. This work proposes a novel framework aimed at identifying and classifying the severity of rotor blade pitch imbalance faults experienced by marine current turbines (MCTs). In the framework, a Continuous Morlet Wavelet Transform (CMWT) is first utilized to acquire the wavelet coefficients encompassed within the 1P frequency range of the turbine's rotor shaft. From these coefficients, several statistical indices are tabulated into a six-dimensional feature space. Next, Principle Component Analysis (PCA) is employed on the resulting feature space for dimensionality reduction, and then the application of a K-Nearest Neighbor (KNN) machine learning algorithm is utilized for fault detection and severity classification. The effectiveness of the proposed framework is validated using a high-fidelity MCT numerical simulation platform, where results demonstrate that the presence of a pitch imbalance fault can be accurately detected 100% of the time and correctly classified based upon severity more than 97% of the time.

42 ENGINEERING↗

Eu 5 Al 3 Sb 6 : Al 4 Tetrahedra Embedded in a Rock-Salt-Like Structure

The new Eu 5 Al 3 Sb 6 phase has been successfully synthesized as a pure phase through Sn flux methods yielding large, high-quality crystals. This structure type features disordered Al clusters that appear in the form of dual tetrahedra. It crystallizes in the monoclinic C2/m space group exhibiting a rock-salt-like Eu–Sb framework with [Al 4 ] tetrahedra replacing some of the cationic Eu atoms (space group: C2/m, a = 8.151(1) Å, b = 14.181(2) Å, c = 8.145(1) Å, β = 109.577(2)°). The structure models the [Al 4 ] as dual tetrahedra with the Al atom sites 37.5% occupied along with Eu present on the central site at 8% occupancy and the remainder of the site being vacant. The presence of the [Al 4 ] cluster is further supported by HRTEM. Electronic structure calculations show that this material is a semimetal with observed band crossings close to the Fermi level. Strong Al–Sb antibonding interactions were found from COHP calculations close to the Fermi level and provide the rationale for the deficiency of the Al cluster. Mössbauer spectroscopy on Eu-151 and Sb-121 provides oxidation states of 2+ and 3– along with the local environment. Magnetic susceptibility measurements can be described well with a Curie–Weiss law where an effective moment of 7.80 μB/mol Eu is obtained, consistent with Eu 2+ , and show canted antiferromagnetic behavior below 10 K. Temperature dependent resistivity shows a Kondo-like low-temperature upturn caused by enhanced scattering of the itinerant electrons with the 4f orbitals of Eu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗

Nearly Identical but Not Isotypic: Influence of Lanthanide Contraction on Cs 2 NaLn(PS 4 ) 2 (Ln = La–Nd, Sm, and Gd–Ho)

The effect of the lanthanide contraction often results in topological and symmetry changes in compounds with the same compositions as a function of lanthanide cation size. Here we report on the first example of a lanthanide thiophosphate exhibiting a change in the lanthanide cation environment without any topological or symmetry change. A series of new lanthanide thiophosphates with mixed alkali cations was obtained via a flux crystal growth technique using a CsI flux. The obtained compounds Cs 2 NaLn(PS 4 ) 2 (Ln = La–Nd, Sm, Gd–Ho) were grown as large single crystals (~0.1–1 mm 3 ) and characterized using single crystal X-ray diffraction and magnetic susceptibility measurements. Moving across the series, the structural studies revealed a change in the lanthanide coordination environment dependent upon the identity of the lanthanide. Although all compounds in the Cs 2 NaLn(PS 4 ) 2 series crystallize in the same space group and have the same Wyckoff positions of the atoms, a slight size change between Sm 3+ and Gd 3+ causes a subtle change in coordination number from 9 (for Ln = La–Sm) to 8 (for Ln = Gd–Ho), resulting in two distinct but virtually identical structure types. Ab initio calculations were performed, and the observed experimental trend was corroborated computationally. Finally, magnetic measurements performed on the Cs 2 NaLn(PS 4 ) 2 (Ln = Ce, Pr, Nd, Gd, and Tb) compounds revealed paramagnetic behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Oxygen and Proton Transport in Flooded Graphene Pores with N-Dopants and Defects

Reactant transport is an important consideration in the design of ideal electrode structures. For the oxygen reduction reaction catalyzed by Pt/C in proton exchange membrane fuel cell cathodes, O 2 and H + delivery to Pt surfaces and H 2 O transport away are required. Some Pt nanoparticles may only be accessible via micropores that are too small for ionomer molecules to enter, possibly requiring flooding for H + transport. Here, to test if these “buried” Pt particles can play a role in activity through this proposed transport mechanism, we have performed atomic-scale simulations based on reactive force field molecular dynamics with an emphasis on confinement below 20 Å. Diffusion coefficients as a function of the molar concentration and local environment have been evaluated in water domains confined in two-dimensional graphene nanochannels of various channel heights representing a morphological model for micropores in proton exchange fuel cell cathodes. Our study shows that local atomic-scale structures can strongly modify H + , O 2 , and H 2 O transport rates in flooded micropores less than 20 Å in size. We find that there is a critical crossover in diffusion behavior around the 20 Å spacing with larger pores having bulk-like diffusion properties and confinement below 20 Å monotonically decreases diffusion rates. As pore size decreases, we observe locally dispersed water regions that ultimately strand reactants from long-distance transport. These findings suggest that flooded micropores may in fact be viable transport pathways for relevant reactants and products if the pore walls on opposite sides remain separated by ≥10 Å separation. Furthermore, the confinement effect is so strong that N-doping and C-vacancy defects in the C pore wall have only a minimal impact on diffusion rates and their effects are counterintuitively more apparent at larger spacings. These findings provide valuable insight regarding cathode performance and the role “stranded” catalyst particles may play in fuel cell cathodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designed and biologically active protein lattices

Versatile methods to organize proteins in space are required to enable complex biomaterials, engineered biomolecular scaffolds, cell-free biology, and hybrid nanoscale systems. Here, we demonstrate how the tailored encapsulation of proteins in DNA-based voxels can be combined with programmable assembly that directs these voxels into biologically functional protein arrays with prescribed and ordered two-dimensional (2D) and three-dimensional (3D) organizations. We apply the presented concept to ferritin, an iron storage protein, and its iron-free analog, apoferritin, in order to form single-layers, double-layers, as well as several types of 3D protein lattices. Our study demonstrates that internal voxel design and inter-voxel encoding can be effectively employed to create protein lattices with designed organization, as confirmed by in situ X-ray scattering and cryo-electron microscopy 3D imaging. The assembled protein arrays maintain structural stability and biological activity in environments relevant for protein functionality. The framework design of the arrays then allows small molecules to access the ferritins and their iron cores and convert them into apoferritin arrays through the release of iron ions. The presented study introduces a platform approach for creating bio-active protein-containing ordered nanomaterials with desired 2D and 3D organizations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Anisotropic 2D excitons unveiled in organic-inorganic quantum wells

Here we report that two-dimensional (2D) excitons arise from electron-hole confinement along one spatial dimension. Such excitations are often described in terms of Frenkel or Wannier limits according to the degree of exciton spatial localization and the surrounding dielectric environment. In hybrid material systems, such as the 2D perovskites, the complex underlying interactions lead to excitons of an intermediate nature, whose description lies somewhere between the two limits, and a better physical description is needed. Here, we explore the photophysics of a tuneable materials platform where covalently bonded metal-chalcogenide layers are spaced by organic ligands that provide confinement barriers for charge carriers in the inorganic layer. We consider self-assembled, layered bulk silver benzeneselenolate, [AgSePh] ∞ , and use a combination of transient absorption spectroscopy and ab initio GW plus Bethe-Salpeter equation calculations. We demonstrate that in this non-polar dielectric environment, strongly anisotropic excitons dominate the optical transitions of [AgSePh] ∞ . We find that the transient absorption measurements at room temperature can be understood in terms of low-lying excitons confined to the AgSe planes with in-plane anisotropy, featuring anisotropic absorption and emission. Finally, we present a pathway to control the exciton behaviour by changing the chalcogen in the material lattice. Our studies unveil unexpected excitonic anisotropies in an unexplored class of tuneable, yet air-stable, hybrid quantum wells, offering design principles for the engineering of an ordered, yet complex dielectric environment and its effect on the excitonic phenomena in such emerging materials.

36 MATERIALS SCIENCE↗

Magnetohydrodynamic simulations preliminarily predict the habitability and radio emission of TRAPPIST-1e

TRAPPIST-1e, an Earth-sized exoplanet in the habitable zone of the nearby M dwarf TRAPPIST-1, may experience magnetospheric responses that vary with stellar space weather, which could potentially influence both its habitability and radio emissions. Our objective is to investigate how different Earth-like magnetospheric configurations of TRAPPIST-1e – specifically variations in dipolar magnetic field strength and axial tilt – respond to diverse stellar space weather conditions, including events analogous to coronal mass ejections (CMEs), and to assess their implications for potential habitability and expected radio emissions. We conducted 3D magnetohydrodynamic simulations of the TRAPPIST-1e system using the PLUTO code in spherical coordinates. The planetary magnetic field was modelled as dipolar, with equatorial strengths from Earth-like to several times stronger. The dipole axis spans a representative range of axial tilts. We investigate four stellar wind environments, from sub-Alfvénic flow to CME-like disturbances. Planetary shielding was quantified based on the magnetopause standoff distance, and radio powers were estimated via empirical scaling laws. Our simulations show that both shielding and radio power depend strongly on the magnetic configuration. Stronger fields increase protection, while larger tilts reduce it. Radio power increases with both field strength and tilt across all wind regimes. An Earth-like magnetic field can provide effective shielding even under intense CMEs, whereas high tilts require stronger fields. Predicted radio powers reach ~10 20 erg s −1 during CMEs, making bursts from close-in, magnetised planets more detectable. However, for TRAPPIST-1e, the maximum cyclotron frequency lies below the Earth’s ionospheric cutoff (~10 MHz), making ground-based detection currently infeasible.

Sun: magnetic fields↗

Moment preserving constrained resampling with applications to particle-in-cell methods

The Moment Preserving Constrained Resampling (MPCR) algorithm for particle resampling is introduced and applied to particle-in-cell (PIC) methods to increase simulation accuracy, reduce compute cost, and/or avoid numerical instabilities. The general algorithm partitions the system space into smaller subsets and resamples the distribution within each subset. Further, the algorithm is designed to conserve any number of particle and grid moments with a high degree of accuracy (i.e. machine accuracy). The effectiveness of MPCR is demonstrated with several numerical tests, including a use-case study in gyrokinetic fusion plasma simulations. Finally, the computational cost of MPCR is negligible compared to the cost of particle evolution in PIC methods, and the tests demonstrate that periodic particle resampling yields a significant improvement in the accuracy and stability of the results.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Chlorophyll- a dynamics in the lower Amazon River: insights from in situ and hyperspectral remote sensing using OCI-PACE

Chlorophyll-a concentration (Chla) is a key indicator of phytoplankton biomass and aquatic trophic status. However, satellite-derived Chla in sediment-rich waters, such as those found in the Lower Amazon River, remains challenging. The present study characterizes in situ Chla levels and their relationships with geographic, physical, and biogeochemical parameters in the Lower Amazon. Data collected between 2014 and 2017 across four hydrological seasons included measurements of Chla, remote sensing reflectance, and water quality parameters such as total suspended sediment, conductivity, water surface temperature, dissolved oxygen, pH, dissolved organic carbon and coloured dissolved organic matter. An empirical model was developed to estimate Chla using simulated hyperspectral bands from NASA’s PACE mission, achieving high performance (R 2 = 0.76; RMSE = 0.11 μg·L −1 ). Red bands proved particularly effective for Chla retrieval, while the addition of ultraviolet bands further enhanced model accuracy. The application of the developed model to satellite imagery yielded results consistent with in situ observations for the same hydrologic season. Seasonal variation and geographic location were major factors influencing Chla dynamics. This study provides a novel contribution to Chla estimation in optically complex, highly turbid waters and highlights the potential of the PACE mission to enhance global aquatic ecosystem monitoring. In conclusion, by offering freely available hyperspectral data with high radiometric resolution, PACE represents a significant advancement in the realm of remote sensing of aquatic environments.

Amazon River↗

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗

The AUREX cell: a versatile operando electrochemical cell for studying catalytic materials using X-ray diffraction, total scattering and X-ray absorption spectroscopy under working conditions

Understanding the structure–property relationship in electrocatalysts under working conditions is crucial for the rational design of novel and improved catalytic materials. This paper presents the Aarhus University reactor for electrochemical studies using X-rays (AUREX) operando electrocatalytic flow cell, designed as an easy-to-use versatile setup with a minimal background contribution and a uniform flow field to limit concentration polarization and handle gas formation. The cell has been employed to measure operando total scattering, diffraction and absorption spectroscopy as well as simultaneous combinations thereof on a commercial silver electrocatalyst for proof of concept. This combination of operando techniques allows for monitoring of the short-, medium- and long-range structure under working conditions, including an applied potential, liquid electrolyte and local reaction environment. The structural transformations of the Ag electrocatalyst are monitored with non-negative matrix factorization, linear combination analysis, the Pearson correlation coefficient matrix, and refinements in both real and reciprocal space. Upon application of an oxidative potential in an Ar-saturated aqueous 0.1 M KHCO 3 /K 2 CO 3 electrolyte, the face-centered cubic (f.c.c.) Ag gradually transforms first to a trigonal Ag 2 CO 3 phase, followed by the formation of a monoclinic Ag 2 CO 3 phase. A reducing potential immediately reverts the structure to the Ag (f.c.c.) phase. Following the electrochemical-reaction-induced phase transitions is of fundamental interest and necessary for understanding and improving the stability of electrocatalysts, and the operando cell proves a versatile setup for probing this. In addition, it is demonstrated that, when studying electrochemical reactions, a high energy or short exposure time is needed to circumvent beam-induced effects.

Frank, Sara (ORCID:0000000163218363)↗

Programming Abstractions for Managing Workflows on Tiered Storage Systems

Scientific workflows in High Performance Computing (HPC) environments are processing large amounts of data. The storage hierarchy on HPC systems is getting deeper, driven by new technologies (NVRAMs, SSDs, etc.) There is a need for new programming abstractions that allow users to seamlessly manage data at the workflow level on multi-tiered storage systems, and provide optimal workflow performance and use of storage resources. In previous work, we introduced a software architecture Managing Data on Tiered Storage for Scientific Workflows (MaDaTS) that used a Virtual Data Space (VDS) abstraction to hide the complexities of the underlying storage system while allowing users to control data management strategies. In this article, we detail the data-centric programming abstractions that allow users to manage a workflow around its data on the storage layer. The programming abstractions simplify data management for scientific workflows on multi-tiered storage systems, without affecting workflow performance or storage capacity. We measure the overheads and effectiveness introduced by the programming abstractions of MaDaTS. Our results show that these abstractions can optimally use the storage capacity in lesser capacity storage tiers, and simplify data management without adding any performance overheads.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Effect of Dipole Interactions on Blocking Temperature and Relaxation Dynamics of Superparamagnetic Iron-Oxide (Fe 3 O 4 ) Nanoparticle Systems

The effects of dipole interactions on magnetic nanoparticle magnetization and relaxation dynamics were investigated using five nanoparticle (NP) systems with different surfactants, carrier liquids, size distributions, inter-particle spacing, and NP confinement. Dipole interactions were found to play a crucial role in modifying the blocking temperature behavior of the superparamagnetic nanoparticles, where stronger interactions were found to increase the blocking temperatures. Consequently, the blocking temperature of a densely packed nanoparticle system with stronger dipolar interactions was found to be substantially higher than those of the discrete nanoparticle systems. The frequencies of the dominant relaxation mechanisms were determined by magnetic susceptibility measurements in the frequency range of 100 Hz–7 GHz. The loss mechanisms were identified in terms of Brownian relaxation (1 kHz–10 kHz) and gyromagnetic resonance of Fe 3 O 4 (~1.12 GHz). It was observed that the microwave absorption of the Fe 3 O 4 nanoparticles depend on the local environment surrounding the NPs, as well as the long-range dipole–dipole interactions. These significant findings will be profoundly important in magnetic hyperthermia medical therapeutics and energy applications.

36 MATERIALS SCIENCE↗