Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Diversity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Glycosyltransferase family 47 (GT47) proteins in plants and animals

Glycosyltransferases (GTs) are carbohydrate-active enzymes that are encoded by the genomes of organisms spanning all domains of life. GTs catalyze glycosidic bond formation, transferring a sugar monomer from an activated donor to an acceptor substrate, often another saccharide. GTs from family 47 (GT47, PF03016) are involved in the synthesis of complex glycoproteins in mammals and insects and play a major role in the synthesis of almost every class of polysaccharide in plants, with the exception of cellulose, callose, and mixed linkage β-1,3/1,4-glucan. GT47 enzymes adopt a GT-B fold and catalyze the formation of glycosidic bonds through an inverting mechanism. Unlike animal genomes, which encode few GT47 enzymes, plant genomes contain 30 or more diverse GT47 coding sequences. With our current knowledge of the GT47 family across plant species brings us an interesting view, showcasing how members exhibit a great diversity in both donor and acceptor substrate specificity, even for members that are classified in the same phylogenetic clade. Thus, we discuss how plant GT47 family members represent a great case to study the relationship between substrate specificity, protein structure, and protein evolution. Most of the plant GT47 enzymes that are identified to date are involved in biosynthesis of plant cell wall polysaccharides, including xyloglucan, xylan, mannan, and pectins. This indicates unique and crucial roles of plant GT47 enzymes in cell wall formation. The aim of this review is to summarize findings about GT47 enzymes and highlight new challenges and approaches on the horizon to study this family.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Implications of the correlation between bulge-to-total baryonic mass ratio and the number of satellites for SAGA galaxies

We searched for correlations between the number of satellites and fundamental galactic properties for the Milky Way-like host galaxies in order to better understand their diverse satellite populations. We specifically aim to understand why galaxies that are very similar in stellar mass content, star formation rate, and local environment have very different numbers of satellites. Deep and extensive spectroscopic observations are needed to characterize the complete satellite luminosity function beyond the Local Group. One such endeavor is an ongoing Satellites of Galactic Analogs (SAGA) spectroscopic survey that has completed spectroscopic observations of 36 Milky Way-like galaxies within their virial radii down to the luminosity of Leo I dwarf galaxy. We correlated the number of satellites of SAGA galaxies with several fundamental properties of their hosts – including total specific angular momentum, which is considered to be well preserved throughout galaxy lifetime – in an attempt to identify the main driver of their diverse satellite populations. We aim to reveal some intrinsic galactic property decisive in making more or less satellites irrespective of baryonic mass or the environment in which galaxies reside. We modeled Spitzer Heritage Archive images of SAGA host galaxies at 3.6 and 4.5 microns with GALFIT code to obtain their stellar masses. We also searched the Extragalactic Database for information on their gas content and rotation velocities. Empirical correlations, like the baryonic Tully–Fisher relation and the stellar mass–size relation were used to exclude outliers. All the available galactic properties from the literature along with measured stellar masses were correlated with the number of satellites and no significant correlation was found. However, when we considered the “expected” number of satellites based on the correlation between the baryonic bulge-to-total ratio and the number of satellites confirmed for several nearby galaxies then strong correlations emerge between this number and (1) the mass of the bulge, and (2) the total specific angular momentum. The first correlation is positive, implying that galaxies with more massive bulges have more satellites, as already confirmed. Furthermore, the second correlation with the angular momentum is negative, meaning that, the smaller the angular momentum, the greater the number of expected satellites. This would imply that either satellites cannot form if galaxy angular momentum is too high, or that satellites form inside-out, so that angular momentum is being transferred to the outer parts of the galaxies. However, deeper spectroscopic observations are needed to confirm these findings, because they rely on the expected rather than detected number of satellites. There was a luminosity limit to the SAGA survey equivalent to the luminosity of Leo I dwarf satellite of the Milky Way galaxy (the SAGA limit). In particular, correlations found in this work are very susceptible to the total number of satellites of the NGC 4158 galaxy. This galaxy is predicted to have many more satellites than detected up to the SAGA limit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

High-redshift quasars along the main sequence

The 4D Eigenvector 1 empirical formalism (4DE1) and its main sequence (MS) for quasars has emerged as a powerful tool for organising the diversity among quasar populations, as several key observational measures and physical parameters are systematically changing along it. Trends revealed by 4DE1 are very well established to explain all the diverse characteristics seen in low-redshift quasar samples. Nevertheless, the situation is far less clear when dealing with high-luminosity and high-redshift sources. Here, we aim to evaluate the behaviour of our sample of 22 quasars at high redshift (2.2 ≤ z ≤ 3.7) and high luminosity (47.39 ≤ L bol ≤ 48.36) in the context of the 4DE1. Our approach involves studying quasar physics through a spectroscopic exploration of UV and optical emission line diagnostics. We used new observations from the ISAAC instrument at ESO-VLT and primarily from the SDSS to cover the optical and the UV rest-frames, respectively. The emission lines were characterised both via a quantitative parametrisation of the line profiles and a decomposition of the emission line profiles using multicomponent fitting routines. We provide spectrophotometric properties and line profile measurements for Hβ+[O III]λλ4959,5007, as well as Si IVλ1397+O IV]λ1402, C IVλ1549+He IIλ1640, and the 1900 Å blend (including Al IIIλ1860, Si III]λ1892, and C III]λ1909). For six out of the 22 objects, a significantly blueshifted component on the Hβ profile is present. In 14 out of 22 cases, an Hβ outflowing component associated with [O III] is detected. The majority of [O III]λλ4959,5007 emission line profiles show blueshifted velocities higher than 250 km s -1 . We find extremely broad [O III]λλ4959,5007 emission that is comparable to the width of Hβ broad profile in some highly accreting quasars. The [O III]λλ4959,5007 and C IVλ1549 blueshifts show very high amplitudes and a high degree of correlation. The line widths and shifts are correlated for both [O III]λλ4959,5007 and C IVλ1549, suggesting that emission from outflowing gas is providing a substantial broadening effect to both lines. Otherwise, the links between C IVλ1549 centroid velocity at half intensity (c(1/2)), Eddington ratio (L/L Edd ), and bolometric luminosity are found to be in agreement with previous studies of high-luminosity quasars. Our analysis suggests that the behaviour of quasars of very high luminosity all along the main sequence is strongly affected by powerful outflows involving a broad range of spatial scales. The main sequence correlations remain valid at high redshift and high luminosity even if a systematic increase in line width is observed. Scaling laws based on UV Al IIIλ1860 and Hβ emission lines are equally reliable estimators of M BH .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The dynamical state of eROSITA clusters and its impact on the brightest cluster galaxy luminosity

The first Spectrum-Roentgen-Gamma (SRG) eROSITA public release contains 12 247 clusters and groups from its first 6 months of operation. We used the offset between the brightest cluster galaxy (BCG) and the X-ray peak ( D BCG − X ) to classify the cluster dynamical state of 3946 galaxy clusters and groups. We aim to investigate the evolution of the merger and relaxed cluster distributions with redshift and mass, and the distributions’ impact on the BCG. We used the X-ray peak from the eROSITA survey and the BCG position from the LS DR10 optical data, which includes the DECam eROSITA Survey optical data, to measure the D BCG − X offset. We modelled the distribution of D BCG − X , in units of R 500 , as the sum of two Rayleigh distributions representing the cluster’s relaxed and disturbed populations, and explored their evolution with redshift and mass. To explore the impact of the cluster’s dynamical state on the BCG luminosity, we separated the main sample according to the dynamical state. We defined clusters as relaxed if D BCG − X < 0.25R500, disturbed if D BCG − X > 0.5R500, and ‘diverse’ if 0.25R500 < D BCG − X < 0.5R500. We find no evolution of the merging fraction with redshift or mass. The width of the relaxed distribution increases with redshift, while the width of the two Rayleigh distributions decreases with mass. The analysis reveals that BCGs in relaxed clusters are brighter than BCGs in both the disturbed and diverse cluster populations. The most significant differences are found for high-mass clusters at higher redshifts. The results suggest that BCGs in low-mass clusters are less centrally bound than those in high-mass systems, irrespective of the dynamical state. Over time, BCGs in relaxed clusters progressively align with the potential centre. This alignment correlates with their luminosity growth relative to BCGs in dynamically disturbed clusters, underscoring the critical role of the cluster’s dynamical state in regulating BCG evolution.

galaxy clusters↗
DOE OSTI2025

The R -Process Alliance: Exploring the cosmic scatter among ten r -process sites with stellar abundances

Context. The astrophysical origin of the rapid neutron-capture process (r-process), responsible for producing roughly half of the elements heavier than iron, remains uncertain. Detailed chemical signatures from the oldest, most metal-poor stars, which act as fossil records of the earliest nucleosynthesis events, can be used to identify the dominant r-process sites. Aims. We present a homogeneous chemical abundance analysis of ten r-process element-enhanced stars. These old and metal-poor stars are strongly enriched in r-process elements with minimal contamination from other nucleosynthetic sources. By focusing on this chemically pure sample, we aim to investigate intrinsic variations in the r-process abundance patterns and explore their implications for the nature and potential diversity of r-process sites. Methods. We performed a detailed chemical abundance analysis of high-resolution, high-signal-to-noise spectra. For each star, we inspected over 1400 individual absorption lines using a combination of equivalent width measurements and spectral synthesis. The analysis was conducted under the assumption of 1D local thermodynamic equilibrium and employing the MOOG radiative transfer code. Results. We derived abundances for 54 chemical species, including 29 neutron-capture (n-capture) elements, covering the full mass range of the r-process abundance pattern. A kinematic analysis reveals that stars likely originated from ten kinematically distinct systems. Based on this assumption, we used the sample to probe the maximum variation expected from ten independent r-process nucleosynthesis events and computed the intrinsic dispersion of each element relative to Zr and Eu for the light and heavy r-process elements, respectively. This exercise resulted in a remarkably low cosmic scatter across the ten r-process sites enriching these stars; for the rare earth and third peak elements, for example, we find σ [La/Eu] = 0.08 and σ [Os/Eu] = 0.11 dex, while the scatter between light and heavy elements, σ [Zr/Eu] , is slightly higher at 0.18 dex. Conclusions. The elemental abundance patterns across the ten independent r-process sites show remarkably small cosmic dispersions. This minimal dispersion suggests a high degree of uniformity in r-process yields across diverse astrophysical environments.

Astronomy and AstroPhysics↗
DOE OSTI2020

Rucio beyond ATLAS: experiences from Belle II, CMS, DUNE, EISCAT3D, LIGO/VIRGO, SKA, XENON

For many scientific projects, data management is an increasingly complicated challenge. The number of data-intensive instruments generating unprecedented volumes of data is growing and their accompanying workflows are becoming more complex. Their storage and computing resources are heterogeneous and are distributed at numerous geographical locations belonging to different administrative domains and organisations. These locations do not necessarily coincide with the places where data is produced nor where data is stored, analysed by researchers, or archived for safe long-term storage. To fulfil these needs, the data management system Rucio has been developed to allow the high-energy physics experiment ATLAS at LHC to manage its large volumes of data in an efficient and scalable way. But ATLAS is not alone, and several diverse scientific projects have started evaluating, adopting, and adapting the Rucio system for their own needs. As the Rucio community has grown, many improvements have been introduced, customisations have been added, and many bugs have been fixed. Additionally, new dataflows have been investigated and operational experiences have been documented. In this article we collect and compare the common successes, pitfalls, and oddities that arose in the evaluation efforts of multiple diverse experiments, and compare them with the ATLAS experience. This includes the high-energy physics experiments Belle II and CMS, the neutrino experiment DUNE, the scattering radar experiment EISCAT3D, the gravitational wave observatories LIGO and VIRGO, the SKA radio telescope, and the dark matter search experiment XENON.

Lassnig, Mario↗
DOE OSTI2021

Experience with Rucio in the wider HEP community

Managing the data of scientific projects is an increasingly complicated challenge, which was historically met by developing experiment-specific solutions. However, the ever-growing data rates and requirements of even small experiments make this approach very difficult, if not prohibitive. In recent years, the scientific data management system Rucio has evolved into a successful open-source project that is now being used by many scientific communities and organisations. Rucio is incorporating the contributions and expertise of many scientific projects and is offering common features useful to a diverse re-search community. This article describes the recent experiences in operating Rucio, as well as contributions to the project, by ATLAS, Belle II, CMS, ES-CAPE, IGWN, LDMX, Folding@Home, and the UK's Science and Technology Facilities Council (STFC).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The integration of heterogeneous resources in the CMS Submission Infrastructure for the LHC Run 3 and beyond

While the computing landscape supporting LHC experiments is currently dominated by x86 processors at WLCG sites, this configuration will evolve in the coming years. LHC collaborations will be increasingly employing HPC and Cloud facilities to process the vast amounts of data expected during the LHC Run 3 and the future HL-LHC phase. These facilities often feature diverse compute resources, including alternative CPU architectures like ARM and IBM Power, as well as a variety of GPU specifications. Using these heterogeneous resources efficiently is thus essential for the LHC collaborations reaching their future scientific goals. The Submission Infrastructure (SI) is a central element in CMS Computing, enabling resource acquisition and exploitation by CMS data processing, simulation and analysis tasks. The SI must therefore be adapted to ensure access and optimal utilization of this heterogeneous compute capacity. Some steps in this evolution have been already taken, as CMS is currently using opportunistically a small pool of GPU slots provided mainly at the CMS WLCG sites. Additionally, Power9 processors have been validated for CMS production at the Marconi-100 cluster at CINECA. This note will describe the updated capabilities of the SI to continue ensuring the efficient allocation and use of computing resources by CMS, despite their increasing diversity. The next steps towards a full integration and support of heterogeneous resources according to CMS needs will also be reported.

Pérez-Calero Yzquierdo, Antonio↗
DOE OSTI2022

Employing Technology to Enable Remote Research Charrettes as a Method for Engaging Industry and Uncovering Best Practices: A Novel Approach for a Post-COVID-19 World

Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.

42 ENGINEERING↗
DOE OSTI2020

Proton-conducting oxides for energy conversion and storage

Proton-conducting oxides are a class of solid-state ion-conducting ceramic materials that demonstrate significant hydrogen ion (proton) conductivity at intermediate temperatures (e.g., 300–700 °C). They are garnering significant attention due to several unique characteristics that distinguish them from both higher temperature oxygen ion conducting oxides and lower temperature proton-conducting polymers. By enabling proton-mediated electrochemistry under both dry and wet environments at moderate temperatures, protonic ceramics provide unique opportunities to enhance or synergize a diverse range of complementary electrochemical and thermochemical processes. Because of this potential, significant efforts have been devoted to advancing numerous energy-related applications using these materials. This review aims to comprehensively summarize these applications and analyze the most up-to-date and future developments of proton-conducting oxides. We aim to bring together this diverse subject matter by integrating the fundamentals of proton-conducting oxides with application-oriented insights. We begin with a historical roadmap, followed by a basic overview of the materials, theories and fundamentals, and fabrication and processing technologies underlying the field. The central section of our review summarizes major applications and developments of proton-conducting ceramics, ranging from maturing applications approaching commercialization to embryonic technologies just now emerging from the lab. These include protonic ceramic fuel cells, protonic ceramic electrolysis cells, reversible protonic ceramic electrochemical cells, protonic ceramic membrane reactors, and protonic ceramic electrochemical reactors. For each application, we analyze both the prospects and challenges and offer recommendations for future research directions so that tomorrow's researchers can continue to advance the development and commercialization of these fascinating materials.

Duan, Chuancheng (ORCID:0000000218261415)↗
DOE OSTI2020

An Entropy-Maximization Approach to Automated Training Set Generation for Interatomic Potentials

Machine learning-based interatomic potentials are currently garnering a lot of attention as they strive to achieve the accuracy of electronic structure methods at the computational cost of empirical potentials. Given their generic functional forms, the transferability of these potentials is highly dependent on the quality of the training set, the generation of which can be highly labor-intensive. Good training sets should at once contain a very diverse set of configurations while avoiding redundancies that incur cost without providing benefits. We formalize these requirements in a local entropy-maximization framework and propose an automated sampling scheme to sample from this objective function. We show that this approach generates much more diverse training sets than unbiased sampling and is competitive with hand-crafted training sets.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Self-regulated growth of candidate topological superconducting parkerite by molecular beam epitaxy

Ternary chalcogenides, such as parkerites and shandites, are a broad class of materials exhibiting a rich diversity of transport and magnetic behavior and an array of topological phases, including Weyl and Dirac nodes. However, they remain largely unexplored as high-quality epitaxial thin films. Here, we report the self-regulated growth of thin films of the strong spin–orbit coupled superconductor Pd 3 Bi 2 Se 2 on SrTiO 3 by molecular beam epitaxy. Films are found to grow in a self-regulated fashion, where, in excess Se, the temperature and relative flux ratio of Pd to Bi control the formation of Pd 3 Bi 2 Se 2 due to the combined volatility of Bi, Se, and Bi–Se bonded phases. The resulting films are shown to be of high structural quality, and the stoichiometry is independent of the Pd:Bi and Se flux ratio and exhibits a superconducting transition temperature of 800 mK and a critical field of 17.7 ± 0.5 mT, as probed by transport and magnetometry. Understanding and navigating the growth of the chemically and structurally diverse classes of ternary chalcogenides open a vast space for discovering new phenomena and enabling new applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts

In this work, we present NENCI-2021, a benchmark database of ~8000 Non-Equilibirum Non-Covalent Interaction energies for a large and diverse selection of intermolecular complexes of biological and chemical relevance. To meet the growing demand for large and high-quality quantum mechanical data in the chemical sciences, NENCI-2021 starts with the 101 molecular dimers in the widely used S66 and S101 databases and extends the scope of these works by (i) including 40 cation–π and anion–π complexes, a fundamentally important class of non-covalent interactions that are found throughout nature and pose a substantial challenge to theory, and (ii) systematically sampling all 141 intermolecular potential energy surfaces (PESs) by simultaneously varying the intermolecular distance and intermolecular angle in each dimer. Designed with an emphasis on close contacts, the complexes in NENCI-2021 were generated by sampling seven intermolecular distances along each PES (ranging from 0.7× to 1.1× the equilibrium separation) and nine intermolecular angles per distance (five for each ion–π complex), yielding an extensive database of 7763 benchmark intermolecular interaction energies (E int ) obtained at the coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory. The E int values in NENCI-2021 span a total of 225.3 kcal/mol, ranging from -38.5 to +186.8 kcal/mol, with a mean (median) E int value of -1.06 kcal/mol (-2.39 kcal/mol). In addition, a wide range of intermolecular atom-pair distances are also present in NENCI-2021, where close intermolecular contacts involving atoms that are located within the so-called van der Waals envelope are prevalent—these interactions, in particular, pose an enormous challenge for molecular modeling and are observed in many important chemical and biological systems. A detailed symmetry-adapted perturbation theory (SAPT)- based energy decomposition analysis also confirms the diverse and comprehensive nature of the intermolecular binding motifs present in NENCI-2021, which now includes a significant number of primarily induction-bound dimers (e.g., cation–π complexes). NENCI-2021 thus spans all regions of the SAPT ternary diagram, thereby warranting a new four-category classification scheme that includes complexes primarily bound by electrostatics (3499), induction (700), dispersion (1372), or mixtures thereof (2192). A critical error analysis performed on a representative set of intermolecular complexes in NENCI-2021 demonstrates that the E int values provided herein have an average error of ±0.1 kcal/mol, even for complexes with strongly repulsive E int values, and maximum errors of ±0.2–0.3 kcal/mol (i.e., ~±1.0 kJ/mol) for the most challenging cases. For these reasons, we expect that NENCI-2021 will play an important role in the testing, training, and development of next-generation classical and polarizable force fields, density functional theory approximations, wavefunction theory methods, and machine learning based intra- and inter-molecular potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization

The recent push for the “materials by design” paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (~50 μm) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (~3 μm) and scratched sample surfaces. Here, this work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.

42 ENGINEERING↗
DOE OSTI2022

Observation of conformational dynamics in single light-harvesting proteins from cryptophyte algae

Photosynthetic organisms use pigment–protein complexes to capture the sunlight that powers most life on earth. Within these complexes, the position of the embedded pigments is all optimized for light harvesting. At the same time, the protein scaffold undergoes thermal fluctuations that vary the structure, and, thus, photophysics, of the complexes. While these variations are averaged out in ensemble measurements, single-molecule spectroscopy provides the ability to probe these conformational changes. We used single-molecule fluorescence spectroscopy to identify the photophysical substates reflective of distinct conformations and the associated conformational dynamics in phycoerythrin 545 (PE545), a pigment–protein complex from cryptophyte algae. Rapid switching between photophysical states was observed, indicating that ensemble measurements average over a conformational equilibrium. A highly quenched conformation was also identified, and its population increased under high light. This discovery establishes that PE545 has the characteristics to serve as a photoprotective site. Finally, unlike homologous proteins from the evolutionarily related cyanobacteria and red algae, quenching was not observed upon photobleaching, which may allow for robust photophysics without the need for rapid repair or replacement machinery. Collectively, these observations establish the presence of a rich and robust set of conformational states of PE545. Cryptophytes exhibit particularly diverse energetics owing to the variety of microenvironments in which they survive, and the conformational states and dynamics reported here may provide photophysical flexibility that contributes to their remarkable ability to flourish under diverse conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Universal signal scaling in microwave impedance microscopy

Microwave impedance microscopy (MIM) is an emerging scanning probe technique that measures the local complex dielectric function using near-field microwave. Although it has made significant impacts in diverse fields, a systematic, quantitative understanding of the signal's dependence on various important design parameters is lacking. Here, we show that for a wide range of MIM implementations, given a complex tip-sample admittance change ΔΥ, the MIM signal—the amplified change in the reflected microwave amplitude—is –G · ΔΥ/2Υ 0 · η 2 · V in , where η is the ratio of the microwave voltage at the probe to the incident microwave amplitude, Y o is the system admittance, and G is the total voltage gain. For linear circuits, η is determined by the circuit design and does not depend on V in . We show that the maximum achievable signal for different designs scales with η 2 or η when limited by input power or sample perturbation, respectively. Furthermore, this universal scaling provides guidance on diverse design goals, including maximizing narrow-band signal for imaging and balancing bandwidth and signal strength for spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

ET-AL: Entropy-targeted active learning for bias mitigation in materials data

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Data-driven insights into the fluorescence of asphaltene aggregates using extended Frenkel exciton model

The origin of the fluorescence redshift during asphaltene aggregation remains debated due to the great diversity of asphaltene molecules, while the extended Frenkel exciton model provided a theoretical framework for studying multi-chromophore systems, such as asphaltene aggregates. We investigated the fluorescence energy of hundreds of asphaltene dimers based on 133 experimental revealed asphaltene monomer structures. Our result shows that the dimer's fluorescence energy is always lower than both of its monomers regardless of its intermolecular conformation, with its redshift dominated by superexchange. The dimer oscillator strength predominantly depends on the monomer with the lower fluorescence energy, and the involvement of charge-transfer states and the cancellation between monomer transition dipole moments suppressed the fluorescence especially when two monomers have similar fluorescence energy. The above-mentioned findings hold for all asphaltene dimers despite their diversity, which offers a theoretical interpretation for comprehending the relationship between asphaltene aggregation and its fluorescence variation. Furthermore, this work provides theoretical guidance to other research areas related to organic planar conjugated systems with multiple chromophores.

Chemistry↗