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At least 379 records · Page 21

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗

Chemical Insights into the Formation of Colloidal Iridium Nanoparticles from In Situ X-ray Total Scattering: Influence of Precursors and Cations on the Reaction Pathway

Iridium nanoparticles are important catalysts for several chemical and energy conversion reactions. Studies of iridium nanoparticles have also been a key for the development of kinetic models of nanomaterial formation. However, compared to other metals such as gold or platinum, knowledge on the nature of prenucleation species and structural insights into the resultant nanoparticles are missing, especially for nanoparticles obtained from Ir$_x$Cl$_y$ precursors investigated here. We use in situ X-ray total scattering (TS) experiments with pair distribution function (PDF) analysis to study a simple, surfactant-free synthesis of colloidal iridium nanoparticles. The reaction is performed in methanol at 50 °C with only a base and an iridium salt as precursor. From different precursor salts–IrCl 3 , IrCl 4 , H 2 IrCl 6 , or Na 2 IrCl 6 –colloidal nanoparticles as small as Ir ~55 are obtained as the final product. The nanoparticles do not show the bulk iridium face-centered cubic ($fcc$) structure but show decahedral and icosahedral structures. The formation route is highly dependent on the precursor salt used. Using IrCl 3 or IrCl 4 , metallic iridium nanoparticles form rapidly from Ir$_x$Cl$_y$$^{n–}$ complexes, whereas using H 2 IrCl 6 or Na 2 IrCl 6 , the iridium nanoparticle formation follows a sudden growth after an induction period and the brief appearance of a crystalline phase. With H 2 IrCl 6 , the formation of different Ir$_n$ ($n$ = 55, 55, 85, and 116) nanoparticles depends on the nature of the cation in the base (LiOH, NaOH, KOH, or CsOH, respectively) and larger particles are obtained with larger cations. As the particles grow, the nanoparticle structure changes from partly icosahedral to decahedral. In conclusion, the results show that the synthesis of iridium nanoparticles from Ir$_x$Cl$_y$ is a valuable iridium nanoparticle model system, which can provide new compositional and structural insights into iridium nanoparticle formation and growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structures of methane and ammonia monooxygenases in native membranes

Methane- and ammonia-oxidizing bacteria play key roles in the global carbon and nitrogen cycles, respectively. These bacteria use homologous copper membrane monooxygenases to accomplish the defining chemical transformations of their metabolisms: the oxidations of methane to methanol by particulate methane monooxygenase (pMMO) and ammonia to hydroxylamine by ammonia monooxygenase (AMO), enzymes of prime interest for applications in mitigating climate change. However, investigations of these enzymes have been hindered by the need for disruptive detergent solubilization prior to structure determination, confounding studies of pMMO and precluding studies of AMO. Here, we overcome these challenges by using cryoEM to visualize pMMO and AMO directly in their native membrane arrays at 2.4 to 2.8 Å resolution. These structures reveal details of the copper centers, numerous bound lipids, and previously unobserved components, including identifiable and distinct supernumerary helices interacting with pMMO and AMO, suggesting a widespread role for these helices in copper membrane monooxygenases. Comparisons between these structures, their metallocofactors, and their unexpected protein–protein interactions highlight features that may govern activity or the formation of higher-order arrays in native membranes. The ability to obtain molecular insights within the native membrane will enable further understanding of these environmentally important enzymes.

Science & Technology - Other Topics↗

Detecting Spin-Bath Polarization with Quantum Quench Phase Shifts of Single Spins in Diamond

Single-qubit sensing protocols can be used to measure qubit-bath coupling parameters. However, for sufficiently large coupling, the sensing protocol itself perturbs the bath, which is predicted to result in a characteristic response in the sensing measurements. Here, we observe this bath perturbation, also known as a quantum quench, by preparing the nuclear spin bath of a nitrogen-vacancy (NV) center in polarized initial states and performing phase-resolved spin-echo measurements on the NV electron spin. These measurements reveal a time-dependent phase determined by the initial state of the bath. We derive the relationship between the sensor phase and the Gaussian spin-bath polarization and apply it to reconstruct both the axial and transverse polarization components. Using this insight, we optimize the transfer efficiency of our dynamic nuclear polarization sequence. This technique for directly measuring bath polarization may assist in preparing high-fidelity quantum memory states, improving nanoscale NMR methods, and investigating non-Gaussian quantum baths.

36 MATERIALS SCIENCE↗

Practical Scalability of LuGo: Benchmarking the HHL Algorithm Using an Enhanced QPE Algorithm

The HHL algorithm is a prominent quantum algorithm that offers exponential speedup over its classical counterparts for solving a system of linear equations. However, synthesizing and executing HHL circuits demand significant computational resources from both classical and quantum systems. In this paper, we benchmark the HHL algorithm using the optimized Quantum Phase Estimation (QPE) generation algorithm, LuGo \cite{lu2025lugo}, to enhance its scalability and efficiency. We leverage the National Energy Research Scientific Computing Center's (NERSC) Perlmutter supercomputer to evaluate the scalability of generating HHL circuits and to measure the time to simulate the generated circuits. Additionally, we provide a comprehensive analysis of the algorithm's performance on various state-of-the-art superconducting and trapped-ion quantum devices, including studies on qubit connectivity, fidelity comparisons, and hardware compatibility and robustness. Our results offer preliminary insights into potential practical applications of the HHL algorithm enabled by LuGo and the performance of various types of quantum hardware.

Lu, Chao [ORNL] (ORCID:0000000179346933)↗

Heterogeneous fatigue damage in a nickel-based single-crystal superalloy unraveled using correlative 3D X-ray technology

Nickel-based single-crystal (Ni-SX) superalloys under cyclic stress are susceptible to cracking at stress-concentration sites, eventually leading to low-cycle fatigue (LCF) failure. LCF cracks typically originate from intrinsic defects (e.g., voids and carbides) within solidified dendrites. However, systematic quantitative experimental analyses of defect-mediated local damage remain limited. To thoroughly understand the microscopic origins and evolution of LCF damage, correlated 3D mapping of dendrites across various regions is essential. Here, in this study, macroscale micro-computed tomography (μ-CT) was initially used to capture internal interdendritic secondary cracks within bulk DD413 superalloy after LCF testing at 760 °C. Subsequently, a multimodal methodology combining synchrotron 3D microdiffraction (3D-μXRD), high-resolution μ-CT, and electron microscopy was established. This approach allowed precise localization of internal damage zones near interdendritic secondary cracks and detailed mapping of the 3D correlated distributions of dendrites, defects, and residual stress/strain fields within these zones at submicron spatial resolution. Finally, the same approach was applied to specimens subjected to interrupted loading at approximately 40 % of the fatigue life to uncover the early damage states of dendrites. The dendrite cores (DCs) and interdendritic regions (IDs) exhibit microscale heterogeneous mechanical responses: nearly defect-free DCs accumulate local irreversible slip along specific slip systems to generate slip bands, while the IDs containing various defects accommodate local microplasticity through the activation of multiple slip systems around these defects. The local tensile stress near defects in the IDs exceeds that in the DC slip band regions by more than threefold, leading to the generation of local damage zones within the IDs. Chain-like defect distributions facilitate the interconnection of these local zones into a continuous damage region, further elevating the overall tensile stress in the IDs. Additionally, geometrically necessary dislocations alone are insufficient as indicators of LCF damage; both the internal stress state and its magnitude must be considered. These experimental results provide critical data and insights for the development of multi-physics fatigue models.

Localized deformation↗

Modulating charge transport via 2 MeV He + irradiation in VO 2

Vanadium dioxide (VO 2 ) is of interest for adaptive electronic applications such as neuromorphic neuristor devices and variable emissivity or tunable thermal control materials, thanks to its key property—a metal–insulator transition (MIT) at 68 °C that is accompanied by a dramatic change in electrical and optical properties. To improve performance in these roles, it is critical to develop approaches to engineer transport properties and the MIT behavior. While many documented techniques exist to modulate the MIT and film resistivities via lattice strain and chemical doping, less is known about the effects of ion irradiation on the intrinsic properties of VO 2 , despite the ability to control the spatial distribution of irradiation beams and the prevalence of high energy ion implantation in the semiconductor industry. The impact of irradiation of different acceleration energies on the responses of VO 2 is of specific interest, as charged particle energy generally impacts both the resulting defect profile and corresponding transport behavior. Here, we demonstrate that 2 MeV He ions at equivalent calculated displacements per atom, in two different types of films, can create remarkable changes to the nature of charge transport in VO 2 , especially in the low-temperature insulating phase. Simulation of resulting changes in electrical conductivity reveals that He ion irradiation offers a strategy to increase both oscillation frequency and the signal transmission. These results provide insights into the intentional design of defect populations to modulate transport for neuromorphic VO 2 devices.

Gurrola, Rebeca M. [Texas A & M Univ., College Sta↗

Manipulating the Second Coordination Shell of Single-Atom Fe for Enhanced Fenton Reaction

While current methods use oxidizable metals as electron donors to effectively reduce Fe 3+ , they suffer from the irreversible oxidation of these metals, ultimately compromising the catalyst’s longevity. To address this challenge, we engineered the second coordination shell of a single-atom Fe center by doping boron (B) onto a graphene-based support (Fe 1 /B-graphene) and utilized H 2 O 2 as the electron source for efficient Fe 2+ regeneration. Experimental results, supported by theoretical calculations, revealed that the Fe–O–B motif functions like a micro galvanic cell, with intermediary O atoms facilitating electron transfer between electrodes. Specifically, electrons consumed during H 2 O 2 activation at Fe 1 sites (positive electrode) are replenished by electrons extracted from H 2 O 2 at B atoms (negative electrode), where the activation energy for H 2 O 2 oxidation is significantly lower than that at Fe 1 sites. This study offers inspirational insights into the design of Fenton catalysts through precise regulation of the second coordination shell, demonstrating the potential of tailoring the outer coordination environment of single-atom catalysts to enhance catalytic performance across various reactions.

36 MATERIALS SCIENCE↗

Room temperature XFEL crystallography reveals asymmetry in the vicinity of the two phylloquinones in photosystem I.

Photosystem I (PS I) has a symmetric structure with two highly similar branches of pigments at the center that are involved in electron transfer, but shows very different efficiency along the two branches. We have determined the structure of cyanobacterial PS I at room temperature (RT) using femtosecond X-ray pulses from an X-ray free electron laser (XFEL) that shows a clear expansion of the entire protein complex in the direction of the membrane plane, when compared to previous cryogenic structures. This trend was observed by complementary datasets taken at multiple XFEL beamlines. In the RT structure of PS I, we also observe conformational differences between the two branches in the reaction center around the secondary electron acceptors A 1A and A 1B . The π-stacked Phe residues are rotated with a more parallel orientation in the A-branch and an almost perpendicular confirmation in the B-branch, and the symmetry breaking PsaB-Trp673 is tilted and further away from A 1A . These changes increase the asymmetry between the branches and may provide insights into the preferential directionality of electron transfer.

59 BASIC BIOLOGICAL SCIENCES↗

Detailed Structural and Chemical Analysis of Amorphous Compounds in Superconducting Qubit Systems

With massive improvements in device coherence times and gate fidelity over the past two decades, superconducting quantum devices have emerged as a leading technology platform for next generation quantum computing. While many of these improvements have been driven through optimized device designs and geometries, the presence of defects, impurities, interfaces, and surfaces in the constituent materials continue to limit performance and present a critical barrier in achieving scalable quantum systems with long coherence times. As part of the Superconducting Quantum Materials and Systems (SQMS) center, we have applied state-of-the-art materials characterization techniques, such as scanning/transmission electron microscopy, secondary ion mass spectrometry, and atom probe tomography, to identify structural defects and chemical inhomogeneities in superconducting qubits. In this review, we discuss the findings of these efforts as they relate to the inherent surfaces, interfaces, impurities, and defects in superconducting qubits. Through this comprehensive investigation, we provide insight into possible sources of dissipation in these systems. Further, we supplement these findings with potential strategies for mitigating these undesired features in an effort to systematically and intelligently improve the coherence times of superconducting qubits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pressure-Induced Stacking of Rhodamine 6G Molecules

Extended conjugation of molecular π systems are of great significance for solar cells and organic light-emitting diodes as these can serve as new light absorbing and emitting chromophores. This research demonstrates the potential of using pressure and solvent environment to create larger assemblies of molecular π-conjugated systems. Here, we selected rhodamine 6G (Rh6G) to study the pressure-induced stacking of molecules in three different solvents: methanol (MeOH), isopropanol (IPA), and 16:3:1 mixture of methanol: ethanol: water (MEW). Absorption, emission, and fluorescence lifetime were studied at pressures up to 11.38 GPa. We found that pressure-induced stacking mechanisms can present solvent dependence: high pressures tend to create emissive Haggregates in MeOH and MEW, but excimers in IPA. This work guides and demonstrates routes to stacking of organic molecules using high pressures and provides fundamental insights into the formation of extended conjugation π systems.

Johnson, Kade [Univ. of Texas at San Antonio, TX (↗

Discovering CO Adsorption and Desorption Pathways from Chemical Reaction Neural Network Modeling of Transient Kinetics Spectroscopy

Here, we demonstrate a data-driven approach to interpreting surface reactions by combining time-resolved gas pulsing infrared spectroscopy with chemical reaction neural networks (CRNNs). Using CO adsorption and desorption on Pd(111) at 460–490 K as a model system, we show how transient kinetic data can reveal detailed reaction mechanisms. Starting with a simple one-species model, we systematically evaluate increasingly complex mechanisms involving hollow and bridge site adsorption. Despite the similar goodness of fit to the same experimental absorbance data, our models predict distinct coverage dynamics for different adsorption sites. Through analysis of spectral peak stability and predicted dynamics, we identify a mechanism in which CO primarily adsorbs on bridge sites followed by rapid conversion to hollow sites as being the most physically consistent with experimental observations. This work provides a framework for extracting mechanistic insights from limited experimental data, demonstrating how machine learning can bridge the gap between transient kinetic measurements and a molecular-level understanding of surface reactions.

36 MATERIALS SCIENCE↗

Understanding the Influence of Urban Form on the Spatial Pattern of Precipitation

Urban areas are known to modify the spatial pattern of precipitation climatology. Existing observational evidence suggests that precipitation can be enhanced downwind of a city. Among the proposed mechanisms, the thermodynamic and aerodynamic processes in the urban lower atmosphere interact with the meteorological conditions and can play a key role in determining the resulting precipitation patterns. In addition, these processes are influenced by urban form, such as the impervious surface extent. This study aims to unravel how different urban forms impact the spatial patterns of precipitation climatology under different meteorological conditions. We use the Multi-Radar Multi-Sensor quantitative precipitation estimation data products and analyze the hourly precipitation maps for 27 selected cities across the continental United States from the years 2015–2021 summer months. Results show that about 80% of the studied cities exhibit a statistically significant downwind enhancement of precipitation. Additionally, we find that the precipitation pattern tends to be more spatially clustered in intensity under higher wind speed; the location of radial precipitation maxima is located closer to the city center under low background winds but shifts downwind under high wind conditions. The magnitude of downwind precipitation enhancement is highly dependent on wind directions and is positively correlated with the city size for the south, southwest, and west directions. This study presents observational evidence through a cross-city analysis that the urban precipitation pattern can be influenced by the urban modification of atmospheric processes, providing insight into the mechanistic link between future urban land-use change and hydroclimates.

54 ENVIRONMENTAL SCIENCES↗

A unifying equation for fermentation sustainability across the titer-rate-yield landscape

Industrial fermentation is central to the sustainable production of fuels and chemicals, yet commercial viability of emerging technologies hinges on improving fermentation titer, rate, and yield (TRY). How these metrics shape system cost remains difficult to generalize due to complex interactions among feedstocks, fermentation, separations, catalytic upgrading, waste management, and facility design. Here, we systematically map theoretical fermentation performance spaces (formed by all potential TRY combinations) for 32 representative biomanufacturing facilities—spanning distinct choices for feedstocks, fermentation regimes and products, separations, and catalytic upgrading—by simulating and evaluating them (via techno-economic analysis, TEA) under uncertainty (600,000 Monte Carlo simulations) and across TRY combinations (7500 TRY combinations for each of 32 configurations). Across this wide design and thermodynamic simulation space, we find the relationship between fermentation TRY and system cost is captured by a simple, generalizable mathematical equation (R 2 of 0.992 − 1.000 across our simulations; 0.954 − 1.000 when validated against prior studies that used different tools). We use this equation to elucidate key drivers that shape cost sensitivity to fermentation performance, generating widely applicable insights. By demonstrating a unifying relationship governs the impact of fermentation on biomanufacturing economics, this work establishes a foundation for agile, holistically predictive, resource-efficient strategies to prioritize fermentation research and development needs and accelerate commercialization of emerging biomanufacturing technologies.

applied mathematics↗

Molecular understanding of heteronuclear active sites in heme–copper oxidases, nitric oxide reductases, and sulfite reductases through biomimetic modelling

Heme-copper oxidases (HCO), nitric oxide reductases (NOR), and sulfite reductases (SiR) catalyze the multi-electron and multi-proton reductions of O 2 , NO, and SO 3 2- , respectively. Each of these reactions is important to drive cellular energy production through respiratory metabolism and HCO, NOR, and SiR evolved to contain heteronuclear active sites containing heme/copper, heme/nonheme iron, and heme-[4Fe-4S] centers, respectively. The complexity of the structures and reactions of these native enzymes, along with their large sizes and/or membrane associations, make it challenging to fully understand the crucial structural features responsible for the catalytic properties of these active sites. Here, we summarize progress that has been made to better understand these heteronuclear metalloenzymes at the molecular level though study of the native enzymes along with insights gained from biomimetic models comprising either small molecules or proteins. Further understanding the reaction selectivity of these enzymes is discussed through comparisons of their similar heteronuclear active sites, and we offer outlook for further investigations and areas of ongoing study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Beam-recoil transferred polarization in $K^+Y$ electroproduction in the nucleon resonance region with CLAS12

We report beam-recoil transferred polarizations for the exclusive electroproduction of K + Λ and K + Σ 0 final states from an unpolarized proton target have been measured using the CLAS12 spectrometer at Jefferson Laboratory. The measurements at beam energies of 6.535 and 7.546 GeV span the range of four-momentum transfer Q 2 from 0.3 to 4.5 GeV 2 and invariant energy W from 1.6 to 2.4 GeV, while covering the full center-of-mass angular range of the K + . These new data extend the existing hyperon polarization data from CLAS in a similar kinematic range but from a significantly larger dataset. They represent an important addition to the world data, allowing for better exploration of the reaction mechanism in strangeness production processes, for further understanding of the spectrum and structure of excited nucleon states, and for improved insight into the strong interaction in the regime of nonperturbative dynamics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Technology Integration 2021 Annual Progress Report

VTO's Technology Integration Program supports a broad technology portfolio that includes alternative fuels, energy efficient mobility systems and technologies, and other efficient advanced technologies that can reduce transportation energy costs for businesses and consumers. The program provides objective, unbiased data and real-world lessons learned to inform future research needs and support local decision making. It also includes projects to disseminate data, information, and insight, as well as online tools and technology assistance to cities and regions working to implement alternative fuels and energy efficient mobility technologies and systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design of axion and axion dark matter searches based on ultra high Q SRF cavities

The Superconducting Quantum Materials and Systems center is developing searches for dark photons, axions and ALPs with the goal of improving upon the current state-of-the-art sensitivity. These efforts leverage on Fermi National Accelerator expertise on ultra-high quality factor superconducting radio frequency cavities combined with the center research on quantum technology. Here we focus on multiple axion searches that utilize ~1E10 quality factor superconducting radio frequency cavities and their resonant modes to enhance the production and/or detection of axions in the cavity volume. In addition, we present preliminary results of single-mode and multi-mode nonlinearity measurements that were carried out as part of an experimental feasibility study to gain insight on the behavior of the ultra-high quality factor resonators and the experimental RF system in the regime relevant for axion searches.

43 PARTICLE ACCELERATORS↗