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At least 307 records · Page 17

On-chip spectroscopic sensors with optical fringe suppression

An on-chip spectroscopic sensor includes a tunable diode laser. A laser driver for drives the tunable diode laser. An analyte test cavity receives a chemical sample and exposes the received chemical sample to light from the tunable diode laser. An optical detector detects light emerging from the analyte test cavity as a result of the laser exposure. A spectral analyzer determines a spectrum of the emerging light, matches and removes one or more known optical fringe patterns from the determined spectrum, and determines a composition or concentration of the chemical sample from the optical fringe pattern-removed spectrum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On-chip spectroscopic sensors with optical fringe suppression

An on-chip spectroscopic sensor includes a tunable diode laser. A laser driver for drives the tunable diode laser. An analyte test cavity receives a chemical sample and exposes the received chemical sample to light from the tunable diode laser. An optical detector detects light emerging from the analyte test cavity as a result of the laser exposure. A spectral analyzer determines a spectrum of the emerging light, matches and removes one or more known optical fringe patterns from the determined spectrum, and determines a composition or concentration of the chemical sample from the optical fringe pattern-removed spectrum.

Green, William↗

HARMONY: Large-Scale Architecture Search for Efficient Hybrid Language Models

As large language models scale to trillions of parameters, their computational and memory requirements present critical challenges for efficient training and deployment. While Mixture of Experts (MoE) architectures enable efficient scaling through sparse parameter activation, and state-space models like Mamba offer linear-time complexity, principled methods for combining these paradigms remain undeveloped. We introduce HARMONY (Hybrid Architecture Research for Mamba, Optimized with Neural efficiencY), a multi-objective evolutionary neural architecture search framework for discovering efficient hybrid language models that integrate Transformer attention mechanisms, Mixture-of-Experts routing, and Mamba state-space components. Through large-scale distributed search using 16,384 MI250X GPUs on the Frontier supercomputer, HARMONY explores a comprehensive design space encompassing six attention variants (MHA, MQA, GQA, MLA, SWA, and Mamba-2), variable MoE configurations with both routed and shared experts, and extensive Mamba hyperparameters. Our framework discovers heterogeneous architectures that balance training performance with computational efficiency through multi-objective optimization incorporating latency penalties and fitness-based selection. Analysis of discovered architectures reveals that optimal hybrid designs favor heterogeneous component mixing rather than homogeneous patterns, with Mamba-2 and Multi-Head Latent Attention (MLA) emerging as preferred mechanisms. Discovered architectures demonstrate superior training efficiency: our best configuration achieves a final perplexity of 1.0874 with 2.38B parameters while processing 4,320 tokens/second, outperforming significantly larger manually designed models. Full-scale evaluation shows HARMONY's top architectures achieve better loss trajectories than equivalently-sized models using state-of-the-art configurations including Mixtral, Jamba, and Samba. Additionally, we demonstrate 91% weak scaling efficiency when training discovered 36B-parameter models across 1,024 GPUs. HARMONY is released as an open framework with comprehensive tools for building and training hybrid models using expert-data-pipeline parallelism, democratizing access to automated architecture design for next-generation language models.

Herron, Emily [ORNL] (ORCID:0000000273008172)↗

Achieving performance portability in Gaussian basis set density functional theory on accelerator based architectures in NWChemEx

The numerical integration of the exchange–correlation (XC) potential is one of the primary computational bottlenecks in Gaussian basis set Kohn–Sham density functional theory (KS-DFT). To achieve optimal performance and accuracy, care must be taken in this numerical integration to preserve local sparsity as to allow for near linear weak scaling with system size. This leads to an integration scheme with several performance critical kernels which must be hand optimized for each architecture of interest. As the set of available accelerator hardware goes more diverse, a key challenge for developers of KS-DFT software is to maintain performance portability across a wide range of computational architectures. In this article, we examine a modular software design pattern which decouples the implementation details of performance critical kernels from the expression of high-level algorithmic workflows in a device-agnostic language such as C++; thus allowing for developers to target existing and emerging accelerator hardware within a single code base. We consider the efficacy of such a design pattern in the numerical integration of the XC potential by demonstrating its ability to achieve performance portability across a set of accelerator architectures which are representative of those on current and future U.S. Department of Energy Leadership Computing Facilities.

97 MATHEMATICS AND COMPUTING↗

Absolute Position Encoders With Vertical Image Binning

Improved optoelectronic patternrecognition encoders that measure rotary and linear 1-dimensional positions at conversion rates (numbers of readings per unit time) exceeding 20 kHz have been invented. Heretofore, optoelectronic pattern-recognition absoluteposition encoders have been limited to conversion rates <15 Hz -- too low for emerging industrial applications in which conversion rates ranging from 1 kHz to as much as 100 kHz are required. The high conversion rates of the improved encoders are made possible, in part, by use of vertically compressible or binnable (as described below) scale patterns in combination with modified readout sequences of the image sensors [charge-coupled devices (CCDs)] used to read the scale patterns. The modified readout sequences and the processing of the images thus read out are amenable to implementation by use of modern, high-speed, ultra-compact microprocessors and digital signal processors or field-programmable gate arrays. This combination of improvements makes it possible to greatly increase conversion rates through substantial reductions in all three components of conversion time: exposure time, image-readout time, and image-processing time.

Leviton, Douglas B.↗

3D Time-Lapse Electrical Resistivity Imaging of Rock Damage Patterns and Gas Flow Paths Resulting from Two Underground Chemical Explosions

Abstract Rock damage from underground nuclear explosions (UNEs) has a strong influence on sub-surface gas movement and on seismic waveform characteristics, both of which are used to detect UNEs. Although advanced numerical simulation capabilities exist to predict rock damage patterns and corresponding detection signals, those predictions are dependent on (generally) unknown properties of the host rock. For example, the effects of in-situ mechanical heterogeneities on the explosively generated damage/fractures that provide gas flow pathways to the surface are not well understood, due largely to the difficulty in accessing and characterizing the near-source region. In this paper we demonstrate the emerging use of electrical resistivity tomography (ERT) for imaging rock damage and gas flow patterns resulting from two relatively small-scale underground chemical explosions. Pre-explosion ERT and crosshole seismic imaging revealed a natural fracture zone within the test bed. Post-explosion imaging revealed that the damage zone was non-symmetric and was focused primarily within the pre-existing fracture zone, located 10 m above the first explosion and 5 m above the second explosion. Time-lapse ERT imaging of heated air injected into the detonation borehole revealed the primary gas flow paths to be within the upper margin of the same primary damage zone. These results point to the utility of ERT imaging for understanding rock damage and gas flow patterns under experimental conditions, and to the importance of understanding the effects of geologic heterogeneity on UNE detection signals, particularly gas surface breakthrough times.

58 GEOSCIENCES↗

Morphogenesis of spin cycloids in a noncollinear antiferromagnet

Pattern formation in spin systems with continuous-rotational symmetry (CRS) provides a powerful platform to study emergent complex magnetic phases and topological defects in condensed-matter physics. However, its understanding and correlation with unconventional magnetic order along with high-resolution nanoscale imaging are challenging. Here, we employ scanning nitrogen vacancy (NV) magnetometry to unveil the morphogenesis of spin cycloids at both the local and global scales within a single ferroelectric domain of (111)-oriented BiFeO 3 , which is a noncollinear antiferromagnet, resulting in formation of a glassy labyrinthine pattern. We find that the domains of locally oriented cycloids are interconnected by an array of topological defects and exhibit isotropic energy landscape predicted by first-principles calculations. We propose that the CRS of spin-cycloid propagation directions within the (111) drives the formation of the labyrinthine pattern and the associated topological defects such as antiferromagnetic skyrmions. Unexpectedly, reversing the as-grown ferroelectric polarization from [$\overline{1}$ $\overline{1}$ $\overline{1}$] to [111] produces a noncycloidal NV image contrast which ¯ could be attributed to either the emergence of a uniformly magnetized state or a reversal of the cycloid polarity. These findings highlight that (111)-oriented BiFeO 3 is not only important for studying the fascinating subject of pattern formation but could also be utilized as an ideal platform for integrating novel topological defects in the field of antiferromagnetic spintronics.

magnetoelectric↗

Microstructural pattern formation during liquid metal dealloying: Phase-field simulations and theoretical analyses

In recent years, liquid metal dealloying has emerged as a promising material processing method to generate micro- and nanoscale bicontinuous or porous structures. Most previous studies focused on the experimental characterization of the dealloying process and on the properties of the dealloyed materials, leaving the theoretical study incomplete to fully understand the fundamental mechanisms of the liquid metal dealloying process. In this paper, we use theoretical models and phase-field simulations to clarify the kinetics and pattern formation during liquid metal dealloying. Our investigation starts from a theoretical analysis of the 1D dissolution of a binary precursor alloy, which reveals that the 1D dissolution process involves two regimes. In the first regime, due to the low solubility of one of the elements in the melt, it accumulates at the solid-liquid interface, which reduces the dissolution kinetics. In the second regime, the interface kinetics reaches a stationary regime where both elements of the precursor alloy dissolve into the melt. Previous works revealed that in the early dealloying stage, the dealloying front is destabilized by an interfacial spinodal decomposition, which triggers the formation of interconnected ligaments. Here we extend this line of work by proposing a linear stability analysis able to predict the initial length scale of the ligaments formed in the initial stage of the dealloying. Combining this analysis with the 1D dissolution model proposed here enables us to better understand the initial conditions (composition of the precursor alloy and the melt) leading to a planar dissolution without interface destabilization. Finally, we report a strong influence of solid-state diffusion on dealloying. Although the solid-state diffusivity is four to five orders of magnitude smaller than in the liquid phase, it is found to affect both dissolution kinetics and ligament morphologies.

36 MATERIALS SCIENCE↗

New principles of self‐organization created through the interplay of DNA condensates, microtubules, and motors

Bioinspired design—which holds great promise for a new generation of materials that are robust to defects, scalable under green manufacture, environmentally responsive, and programmably reconfigurable—requires mastery over molecular self-organization. Yet, from its specific mechanisms to most general architectures, the principles governing self-organization remain poorly understood and not even fully enumerated. For living systems, one obvious architectural principle is the modular reuse of a few simple molecular components in myriad combinations to achieve more complex phenomena. For example, the mechanical tasks of a cell are driven by the nonequilibrium dynamics of cytoskeletal filaments and molecular motors—the same filaments and motors, reprogrammed by a variety of modulators, perform tasks ranging from cell movement to division. Similarly, many compartmentalization tasks are performed by liquid-like condensates of simple components, which act as membraneless organelles to localize particular molecules in space and time (e.g. for gene regulation or RNA processing). In a few cases, condensates combine and interact with the cytoskeleton to create still more complex phenomena, e.g. the nucleation of microtubule asters from the centrosome (a protein condensate) to form the mitotic spindle during cell division. Very little is known about the fundamental mechanisms of such filament-plus-condensate phenomena. Despite few examples, the landscape of behaviors that can be achieved through the combination of condensates, filaments, and motors appears vast. However, exploration has been hindered by a lack of systems that have sufficiently programmable and dynamically tunable interactions between component condensates, filaments, and motors. We proposed to combine programmable DNA condensates, filamentous microtubules, and light-controlled motors into self-organizing systems whose principles go beyond those that have been observed in nature. In one limit, our systems will use microtubules and motors to create the molecular analog of a network of roads, which will organize droplets of DNA condensates capable of carrying molecular cargo. DNA condensates coupled to motors will flow from one microtubule aster hub to another, with their direction and timing controlled by DNA circuits. In another limit, microtubules will swim through bulk DNA condensates and exhibit strong interactions with boundaries between different types of condensates. Microtubule swimmers will reflect, get trapped, or refract at boundaries, under a mechanical analog of the classical optical index of refraction. DNA condensates having different mechanical indexes of refraction will be used to construct the analog of optical lenses, so that microtubule swimmers can be manipulated like light—collimated, diffracted, focused, and sorted based on properties analogous to wavelength. These two limits define two new architectures, within which multiple new mechanistic principles for self-organization will be discovered and explored. To explore these architectures, the motor-based coupling between DNA condensates and filaments will be controlled in time and space through the use of opto-proteins that create reversible links between DNA condensates and motors upon illumination. For each principle of interest, patterns of light will create virtual experiments by defining patterns of activity where DNA condensates walk along filaments, or filaments swim through condensates, and patterns of inactivity which will serve either as controls, or as boundary conditions vital to create the desired phenomena. This research serves the goals of Basic Energy Sciences Biomolecular Material Program by elucidating the principles by which the emergent, nonequilibrium behavior of collections of DNA condensates, motors, and microtubules can be programmed by environmental light patterns to create complex motion and materials transport. Because DNA condensates can be readily coupled to virtually any high performance nanomaterial, from carbon nanotubes, to metal nanoparticles, to light harvesting systems, this work provides a path to the construction, self-maintenance and reconfiguration of materials relevant to the Department of Energy.

60 APPLIED LIFE SCIENCES↗

Green microalga Chromochloris zofingiensis conserves substrate uptake pattern but changes their metabolic uses across trophic transition

The terrestrial green alga Chromochloris zofingiensis is an emerging model species with potential applications including production of triacylglycerol or astaxanthin. How C. zofingiensis interacts with the diverse substrates during trophic transitions is unknown. To characterize its substrate utilization and secretion dynamics, we cultivated the alga in a soil-based defined medium in transition between conditions with and without glucose supplementation. Then, we examined its exometabolite and endometabolite profiles. This analysis revealed that regardless of trophic modes, C. zofingiensis preferentially uptakes exogenous lysine, arginine, and purines, while secreting orotic acid. Here, we obtained metabolomic evidences that C. zofingiensis may use arginine for putrescine synthesis when in transition to heterotrophy, and for the TCA cycle during transition to photoautotrophy. We also report that glucose and fructose most effectively inhibited photosynthesis among thirteen different sugars. The utilized or secreted metabolites identified in this study provide important information to improve C. zofingiensis cultivation, and to expand its potential industrial and pharmaceutical applications.

59 BASIC BIOLOGICAL SCIENCES↗

State changes: insights from the U.S. Long Term Ecological Research Network

Understanding the complex and unpredictable ways ecosystems are changing and predicting the state of ecosystems and the services they will provide in the future requires coordinated, long-term research. This paper is a product of a U.S. National Science Foundation funded Long Term Ecological Research (LTER)network synthesis effort that addressed anticipated changes in future populations and communities. Each LTER site described what their site would look like in50 or 100 yr based on long-term patterns and responses to global change drivers in each ecosystem. Common themes emerged and predictions were grouped into state change, connectivity, resilience, time lags, and cascading effects. Here, we report on the “state change” theme, which includes examples from the Georgia Coastal (coastal marsh), Konza Prairie (mesic grassland), Luquillo(tropical forest), Sevilleta (arid grassland), and Virginia Coastal (coastal grassland) sites. Ecological thresholds(the point at which small changes in an environmental driver can produce an abrupt and persistent state change in an ecosystem quality, property, or phenomenon) were most commonly predicted. For example, in coastal ecosystems, sea-level rise and climate change could convert salt marsh to mangroves and coastal barrier dunes to shrub thicket. Reduced fire frequency has converted grassland to shrubland in mesic prairie, whereas overgrazing combined with drought drive shrub encroachment in arid grasslands. Lastly, tropical cloud forests are susceptible to climate-induced changes in cloud base altitude leading to shifts in species distributions. Overall, these examples reveal that state change is a likely outcome of global environmental change across adverse range of ecosystems and highlight the need for long-term studies to sort out the causes and consequences of state change. The diversity of sites within the LTER network facilitates the emergence of overarching concepts about state changes as an important driver of ecosystem structure, function, services, and futures.

54 ENVIRONMENTAL SCIENCES↗

Identification of pressure points in modern power systems using transfer entropy

Power shortages disrupt daily life, economic activity, and essential services. In modern power systems, weather is an increasingly important driver of reliability: high temperatures raise demand and limit transmission capacity, and calm or cloudy periods reduce wind and solar supply. Using a data-driven analysis, this study identifies grid infrastructure whose operating patterns help predict power shortages. The results show that reliability risks often emerge from interacting stresses across generation, transmission, and demand, rather than from single bottlenecks. By clarifying how system stress propagates through the grid, this diagnostic perspective helps explain why shortages occur under specific conditions and can complement traditional planning and operational tools to support adaptive reliability strategies, targeted monitoring, and coordinated infrastructure investments.

power systems↗

Mesoporous Silica Formation Mechanisms Probed Using Combined Spin–Echo Modulated Small-Angle Neutron Scattering (SEMSANS) and Small-Angle Neutron Scattering (SANS)

In this work, the initial formation stages of surfactant-templated silica thin films which grow at the air–water interface were studied using combined spin–echo modulated small-angle neutron scattering (SEMSANS) and small-angle neutron scattering (SANS). The films are formed from either a cationic surfactant or nonionic surfactant (C 16 EO 8 ) in a dilute acidic solution by the addition of tetramethoxysilane. Previous work has suggested a two stage formation mechanism with mesostructured particle formation in the bulk solution driving film formation at the solution surface. From the SEMSANS data, it is possible to pinpoint accurately the time associated with the formation of large particles in solution that go on to form the film and to show their emergence is concomitant with the appearance of Bragg peaks in the SANS pattern, associated with the two-dimensional hexagonal order. The combination of SANS and SEMSANS allows a complete depiction of the steps of the synthesis that occur in the subphase.

36 MATERIALS SCIENCE↗

An Assessment of Nonhydrostatic and Hydrostatic Dynamical Cores at Seasonal Time Scales in the Energy Exascale Earth System Model (E3SM)

Abstract In global atmospheric modeling, the differences between nonhydrostatic (NH) and hydrostatic (H) dynamical cores are negligible in dry simulations when grid spacing is larger than 10 km. However, recent studies suggest that those differences can be significant at far coarser resolution when moisture is included. To better understand how NH and H differences manifest in global fields, we perform and analyze an ensemble of 28 and 13 km seasonal simulations with the NH and H dynamical cores in the Energy Exascale Earth System Model global atmosphere model, where the differences between H and NH configurations are minimized. A set of idealized rising bubble experiments is also conducted to further investigate the differences. Although NH and H differences are not significant in global statistics and zonal averages, significant differences in precipitation amount and patterns are observed in parts of the tropics. The most prominent differences emerge near India and the Western Pacific in the boreal summer, and the central‐southern Indian Ocean and Pacific in the boreal winter. Tropical differences influence surrounding regions through modification of the regional circulation and can propagate to the extratropics, leading to significant temperature and geopotential differences over the middle to high latitudes. While the dry bubble experiments show negligible deviation between H and NH dynamics until grid spacing is below 6.25 km, precipitation amount and vertical velocity are different in the moist case even at 25 km resolution.

58 GEOSCIENCES↗

Videomagnetograph studies of solar magnetic fields. II - Field changes in an active region

Using the Caltech videomagnetograph, we obtained a 6.5-hr movie of the magnetic fields in a young active region. The major contribution to the short term magnetic evolution of the region was provided by many discrete magnetic points which move in apparently random directions with typical velocities of 0.4 - 1.0 km/sec. The majority of these features appear to be footpoints of new EFR's, which emerge at an observed rate of one to two per hour. The pattern of the motions suggests that the magnetic evolution of a growing region cannot be principally due to photospheric convective cells.

Schoolman, S. A.↗

The heavy ion compositional signature in 3He-rich solar particle events

A survey of the approx. 1 MeV/nucleon heavy ion abundances in 66 He3-rich solar particle events was performed using the Max-Planck-Institut/University of Maryland and Goddard Space Flight Center instruments on the ISEE-3 spacecraft. The observations were carried out in interplanetary space over the period 1978 October through 1982 June. Earlier observations were confirmed which show an enrichment of heavy ions in HE3-rich events, relative to the average solar energetic particle composition in large particle events. For the survey near 1.5 MeV/nucleon the enrichments compared to large solar particle events are approximately He4:C:O:Ne:Mg:Si:Fe = 0.44:0.66:1.:3.4:3.5:4.1:9.6. Surprising new results emerging from the present broad survey are that the heavy ion enrichment pattern is the same within a factor of approx. 2 for almost all cases, and the degree of heavy ion enrichment is uncorrelated with the He3 enrichment. Overall, the features established appear to be best explained by an acceleration mechanism in which the He3 enrichment process is not responsible for the heavy ion enrichment, but rather the heavy ion enrichment is a measure of the ambient coronal composition at the sites where the He3-rich events occur.

Mason, G. M.↗

The heavy-ion compositional signature in He-3-rich solar particle events

A survey of the approx. 1 MeV/nucleon heavy ion abundances in 66 He-3-rich solar particle events was performed using the Max-Planck-Institut/University of Maryland and Goddard Space Flight Center instruments on the ISEE-3 spacecraft. The observations were carried out in interplanetary space over the period 1978 October through 1982 June. Earlier observations were confirmed which show an enrichment of heavy ions in He-3-rich events, relative to the average solar energetic particle composition in large particle events. For the survey near 1.5 MeV/nucleon the enrichments compared to large solar particle events are approximately He4:C:O:Ne:Mg:Si:Fe = 0.44:0.66:1.:3.4:3.5:4.1:9.6. Surprising new results emerging from the present broad survey are that the heavy ion enrichment pattern is the same within a factor of approx. 2 for almost all cases, and the degree of heavy ion enrichment is uncorrelated with the He-3 enrichment. Overall, the features established appear to be best explained by an acceleration mechanism in which the He-3 enrichment process is not responsible for the heavy ion enrichment, but rather the heavy ion enrichment is a measure of the ambient coronal composition at the sites where the He-3-rich events occur.

Mason, G. M.↗

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

Michaels, Anthony F.↗