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DOE OSTI2025

Advancing the Understanding of Snow Accumulation, Melting, and Associated Thermal Insulation Using Spatially Dense Snow Depth and Temperature Time Series

Snow thermal insulation is a critical factor influencing ground thermal dynamics and associated biogeochemical processes. We analyzed the spatiotemporal variability of snow accumulation, melting, and thermal insulation dynamics using spatially dense, collocated snow depth and ground interface temperature time series over two consecutive years. We demonstrated that considering late‐winter snow depth alone was insufficient to fully capture the complexity in snow and insulation dynamics. The influence of vegetation and topography on snow depth distribution varied over the season, across sites and years. We found that deep snow with a long melting period had a substantial impact on thawing n‐factors. To better predict snow insulation effects, we proposed a new weighted snow depth metric that integrates mean daily snow depth and air temperature throughout the cold season. Our results provide insights for developing space‐time remote sensing products and evaluating the representation of snow and permafrost processes in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

THE BALLOON-BORNE LARGE APERTURE SUBMILLIMETER TELESCOPE (BLAST) 2005: A 10 deg{sup 2} SURVEY OF STAR FORMATION IN CYGNUS X

We present Cygnus X in a new multi-wavelength perspective based on an unbiased BLAST survey at 250, 350, and 500 {mu}m, combined with rich data sets for this well-studied region. Our primary goal is to investigate the early stages of high-mass star formation. We have detected 184 compact sources in various stages of evolution across all three BLAST bands. From their well-constrained spectral energy distributions, we obtain the physical properties mass, surface density, bolometric luminosity, and dust temperature. Some of the bright sources reaching 40 K contain well-known compact H II regions. We relate these to other sources at earlier stages of evolution via the energetics as deduced from their position in the luminosity-mass (L-M) diagram. The BLAST spectral coverage, near the peak of the spectral energy distribution of the dust, reveals fainter sources too cool ({approx}10 K) to be seen by earlier shorter-wavelength surveys like IRAS. We detect thermal emission from infrared dark clouds and investigate the phenomenon of cold 'starless cores' more generally. Spitzer images of these cold sources often show stellar nurseries, but these potential sites for massive star formation are 'starless' in the sense that to date there is no massive protostar in a vigorous accretion phase. We discuss evolution in the context of the L-M diagram. Theory raises some interesting possibilities: some cold massive compact sources might never form a cluster containing massive stars, and clusters with massive stars might not have an identifiable compact cold massive precursor.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Embedding of Fiber Optic Sensors in Stainless Steel for Sensing in Harsh Environments

Structural health monitoring is critical for components working in harsh environments to assess their safety and integrity. This can be realized with advanced sensors, such as fiber optic sensors, embedded in these components. Recent studies have used ultrasonic consolidation (UC) and laser-based additive manufacturing (AM) techniques to embed fiber optic sensors in metals. However, sensor embedding using these techniques has been challenging, with gaps and voids around the embedded fiber. Successful embedding of fiber optic sensors requires good contact between the fiber and the matrix to eliminate potential gas/liquid leaks in critical systems such as in nuclear and aerospace services. Defect-free fiber/matrix bond is also essential for accurate measurement of parameters of interest, such as temperature and strain. This study developed a novel fiber embedding technique based on electric field-assisted sintering (EFAS). Sapphire optical fibers with diameters of 125 µm and 250 µm were embedded in stainless steel (SS) 316L using EFAS. The embedding was completed by sintering SS 316L powders at a pressure of 50MPa, hold time of 5 min, and temperatures of 1000°C, 1100°C, and 1200°C. Joule heating mechanism during EFAS enabled rapid sintering of the SS 316L powder with resulting sample densities over 99%. Microscopy analysis performed on the cross-sections revealed a defect-free bond between the embedded fiber and SS 316L. The good integrity of the embedded fiber was evidenced by optical transmittance measurement. Optical attenuation of the fiber before and after embedment was examined in the near-infrared region. Scanning electron microscopy was employed to investigate the grain morphology of SS 316L near the embedded fiber. Hardness distribution in the sintered part was also investigated to study the effect of the embedded fiber on the mechanical properties of the as-fabricated component. The results indicated that EFAS was able to embed fiber in SS with good fiber functionality and part quality.

36 - MATERIALS SCIENCE↗

DOE OSTI2023

An Incremental Gradient Method for Optimization Problems With Variational Inequality Constraints

We consider minimizing a sum of agent-specific nondifferentiable merely convex functions over the solution set of a variational inequality (VI) problem in that each agent is associated with a local monotone mapping. This problem finds an application in computation of the best equilibrium in nonlinear complementarity problems arising in transportation networks. We develop an iteratively regularized incremental gradient method where at each iteration, agents communicate over a directed cycle graph to update their solution iterates using their local information about the objective and the mapping. The proposed method is single-timescale in the sense that it does not involve any excessive hard-to-project computation per iteration. We derive nonasymptotic agent-wise convergence rates for the suboptimality of the global objective function and infeasibility of the VI constraints measured by a suitably defined dual gap function. Finally, the proposed method appears to be the first fully iterative scheme equipped with iteration complexity that can address distributed optimization problems with VI constraints over cycle graphs.

convergence↗

DOE OSTI2022

Secure mmWave Spectrum Sharing with Autonomous Beam Scheduling for 5G and Beyond

Spectrum Sharing (SS) has seen a renewed set of initiatives in 5G with the availability of shared and unlicensed spectrum bands that can be used by multiple cellular service providers and private cellular networks. Beam based transmission, instead of the traditional sector based transmission in conjunction with the spectrum agility of the 5G New Radio (NR) has brought new opportunities to optimized sharing of spectrum. Currently in the U.S., a centralized Spectrum Access Server (SAS) is used to co-ordinate spectrum sharing among networks sharing the same spectrum band. However, SAS becomes a focal point for security attacks and a performance bottleneck. In addition, SAS relies on an Environmental Sensor Network (ESN), separate from the 5G network. Without trusted spectral occupancy information, false reporting of spectrum sensing data can create sub-optimal and unfair spectrum usage. This paper summarizes our recent research findings in using a decentralized scheme for multiple networks to securely share spectrum with autonomous beam scheduling : 1) A new stochastic network framework based on Lyapunov Optimization approach is developed to optimize scheduling at the base stations; 2) Game theoretic (GT) approach is used to formulate the distributed scheduler; 3) Another distributed scheduler with Q-learning is presented that utilizes the Reinforcement Learning (RL) approach; 4) The performance and convergence rate of these distributed solutions to use shared and unlicensed spectrum are compared with existing solutions. Conditions under which the performance of these schedulers approach the theoretical upper bound, which is the performance possible with no interference among the operators sharing the spectrum, are presented; 5) The ability of a base station to use its own user equipment as sensors, for optimal spectrum sharing with base stations in other operator networks, is demonstrated to be an effective approach.

5G↗

DOE OSTI2013

Intelligent Software Agents: Sensor Integration and Response

Abstract In a post Macondo world the buzzwords are Integrity Management and Incident Response Management. The twin processes are not new but the opportunity to link the two is novel. Intelligent software agents can be used with sensor networks in distributed and centralized computing systems to enhance real-time monitoring of system integrity as well as manage the follow-on incident response to changing, and potentially hazardous, environmental conditions. The software components are embedded at the sensor network nodes in surveillance systems used for monitoring unusual events. When an event occurs, the software agents establish a new concept of operation at the sensing node, post the event status to a blackboard for software agents at other nodes to see , and then react quickly and efficiently to monitor the scale of the event. The technology addresses a current challenge in sensor networks that prevents a rapid and efficient response when a sensor measurement indicates that an event has occurred. By using intelligent software agents - which can be stationary or mobile, interact socially, and adapt to changing situations - the technology offers features that are particularly important when systems need to adapt to active circumstances. For example, when a release is detected, the local software agent collaborates with other agents at the node to exercise the appropriate operation, such as: targeted detection, increased detection frequency, decreased detection frequency for other non-alarming sensors, and determination of environmental conditions so that adjacent nodes can be informed that an event is occurring and when it will arrive. The software agents at the nodes can also post the data in a targeted manner, so that agents at other nodes and the command center can exercise appropriate operations to recalibrate the overall sensor network and associated intelligence systems. The paper describes the concepts and provides examples of real-world implementations including the Threat Detection and Analysis System (TDAS) at the International Port of Memphis and the Biological Warning and Incident Characterization System (BWIC) Environmental Monitoring (EM) Component. Technologies developed for these 24/7 operational systems have applications for improved real-time system integrity awareness as well as provide incident response (as needed) for production and field applications.

emergency response↗

DOE OSTI2020

Ultra-Low SWaP CO 2 Sensing for Demand Control Ventilation (Final Report)

In this project PARC and Energy ETC aimed to develop an ultra-low cost, size, weight, and power (SWaP) printed CO 2 sensor system for occupancy detection to enable Demand Control Ventilation (DCV) on a per-room basis. The CO 2 sensor technology is based on the temperature variation when CO 2 reversibly physisorbs to a highly conductive and high surface area sorbent surface, and is compatible with integration with PARC innovations in printed sensors and flexible electronics, for which PARC is a globally leading research center. The printed CO 2 sensor itself is designed to be compatible with PARC’s “peel-and-stick” platform of ultra-low power, low-cost, distributed sensors, and to facilitate real-time DCV based on overall indoor air quality (IAQ). Previously, PARC has developed flexible hybrid electronics (FHE) compatible materials to measure humidity, temperature, light, strain, and gases such as carbon monoxide, methane, ammonia, and hydrogen sulfide. Through this project, PARC developed FHE-compatible materials to measure CO 2 . Thus, with one <$15 FHE “peel-and-stick” based sensor node, a building management system (BMS) will be able to capture a complete picture of the indoor environment. This includes IAQ, light, temperature, and other comfort factors that impact building operations. Combined with optimized DCV, this low-cost sensor capability can be a key enabler of annual primary energy savings of ~ 0.3-0.4 Quad in commercial buildings while ensuring healthy IAQ. Energy ETC is a leader in supplier-agnostic BMS deployments and will design the commissioning and deployment procedures to maximize system interoperability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Molecular Sensing Using Hyperpolarized Xenon NMR Spectroscopy

Molecular imaging is defined as the determination of the spatial location and concentration of specific molecules in a sample of interest. Sophisticated modern magnetic resonance imaging machines can collect NMR spectra from small-volume elements within a sample, enabling local chemical analysis. However, abundant water and fat signals limit detection of metabolites to near mm concentrations. Alternatively, targeted relaxation contrast agents enhance the relaxation of the strong water signal where they bind. A comparison of images with and without a contrast agent shows the target distribution, but high mm concentrations are needed. We have developed an approach that exploits the strong signals of hyperpolarized 129 Xe (an inert reporter introduced for imaging). The imaging contrast agents are composed of a biological recognition motif to localize the agent (antibodies or aptamers) and covalently tethered cryptophane cages. Xenon binds to the cryptophane and though chemical exchange saturation transfer creates contrast in a xenon image. Imaging agents can deliver many cages per target, giving detection limits in the pm concentration range. The evolution and principles of this approach are described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Imaging Photonic Resonances within an All‐Dielectric Metasurface via Photoelectron Emission Microscopy

Dielectric metasurfaces, through volume‐type photonic resonances, enable precise control of light‐matter interactions for applications including imaging, holography, and sensing. The application space of dielectric metasurfaces has extended from infrared to visible wavelengths by incorporating high refractive index materials, such as titanium dioxide (TiO 2 ). Understanding the fundamental and fabrication limits for these applications requires metrology with nanoscale resolution, sensitivity to electromagnetic fields within the meta‐atom volume, and far‐field excitation. In this work, photoelectron emission microscopy (PEEM) is used to image field distributions of photonic resonances in a TiO 2 metasurface excited with far‐field, visible‐wavelength illumination. The local volumetric field variations within the meta‐atoms are analyzed as a function of illumination angle and polarization by comparing photoelectron images to finite‐difference time‐domain simulations. This study determines the inelastic mean free path of very low‐energy (<1 eV) photoelectrons to be 35 ± 10 nm, which is comparable to the meta‐atom height thereby highlighting PEEM sensitivity to resonances within the volume. Additionally, the simulations reveal high sensitivity of PEEM images to an in‐plane component of the illumination k ‐vector. These results demonstrate that photoelectron imaging with subwavelength resolution offers unique advantages for examining light‐matter interactions in volume‐type (as opposed to surface) photonic modes within dielectric nanophotonic structures.

electron inelastic mean free path↗

DOE OSTI2010

Effect of Kerr nonlinearity on an Airy beam

The effect of Kerr nonlinearity on an Airy beam is investigated by using the nonlinear Schroedinger equation. Based on the moments method, the evolution of the Airy beam width in the rms sense is analytically described. Numerical simulations indicate that the central parts of the major lobe of the Airy beam initially give rise to radial compression during propagation in a focusing medium, even though the rms beam width broadens. The partial collapse of the center parts of the major lobe of the beam appear below the threshold for a global collapse. The evolutions of the field distributions of the Airy beams are different during propagation in different Kerr media while the beams still travel along the parabolic trajectory just as the beam propagates in free space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Satellite remote sensing data can be used to model marine microbial metabolite turnover

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10-6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Multicolor Inks of Black Phosphorus for Midwave‐Infrared Optoelectronics

Abstract Black phosphorus (bP) based ink with a bulk bandgap of 0.33 eV ( λ = 3.7 µm) has recently been shown to be promising for large‐area, high performance mid‐wave infrared (MWIR) optoelectronics. However, the development of multicolor bP inks expanding across the MWIR wavelength range has been challenging. Here a multicolor ink process based on bP with spectral emission tuned from 0.28 eV ( λ = 4.4 µm) to 0.8 eV ( λ = 1.5 µm) is demonstrated. Specifically, through the reduction of bP particle size distribution (i.e., lateral dimension and thickness), the optical bandgap systematically blueshifts, reaching up to 0.8 eV. Conversely, alloying bP with arsenic (bP 1− x As x ) induces a redshift in the bandgap to 0.28 eV. The ink processed films are passivated with an infrared‐transparent epoxy for stable infrared emission in ambient air. Utilizing these multicolor bP‐based inks as an infrared light source, a gas sensing system is demonstrated that selectively detects gases, such as CO 2 and CH 4 whose absorption band varies around 4.3 and 3.3 µm, respectively. The presented ink formulation sets the stage for the advancement of multiplex MWIR optoelectronics, including spectrometers and spectral imaging using a low‐cost material processing platform.

Kim, Jae Ik↗

DOE OSTI2020

Efficient Control of Atom Arrangement in Ternary Metal Chalcogenide Nanoparticles Using Precursor Oxidation State

Controlling both the concentration and the distribution of elements in a given material is often crucial to extracting and optimizing synergistic properties of the various constituents. An interesting class of such multielement materials is metal chalcogenide nanoparticles, which exhibit a wide range of composition-dependent optoelectronic properties including both bandgap-mediated processes and localized surface plasmon resonance properties, each of which is useful in applications ranging from energy conversion to sensing. Because metal chalcogenide nanoparticles can support several different metal elements in a variety of chalcogen lattices, this material class has particularly benefited from the ability to control both atom concentration and atom arrangement to tailor final particle properties. The primary method to access complex, multimetallic chalcogenide particles is via a postsynthetic cation exchange strategy. One-pot syntheses have been less explored to access these complex particles, although this route is desirable for economy and scalability. In this work, we compare the composition and morphology outcomes from cation exchange and one-pot preparation approaches using a Cu/Ag/Se system, which is already known to exhibit both binary and ternary metal chalcogenide phases. We show that at similar concentrations of the two metal cations, initial reaction conditions for the one-pot method yield multicomponent nanoparticles, whereas cation exchange yields homogeneous ternary metal chalcogenide structures. We then show that by tuning the precursor oxidation state for the one-pot method, this approach can be used to access homogeneous ternary metal chalcogenide particles that are similar in atom arrangement to the particles obtained using cation exchange. Taken together, our results demonstrate reliable synthetic methods that yield a variety of controlled compositions and composition morphologies in the Cu/Ag/Se system. Importantly, we demonstrate that this entire collection of architectures can all be accessed via a one-pot method simply by modifying metal precursor chemistry. The mechanistic insights gained and the resulting streamlined syntheses outlined indicate pathways to easily scaled, highly tailorable syntheses for rapid translation into downstream technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

A united event grand canonical Monte Carlo study of partially doped polyaniline

A Grand Canonical Monte Carlo scheme, based on united events combining protonation/deprotonation and insertion/deletion of HCl molecules is proposed for the generation of polyaniline structures at intermediate doping levels between 0% (PANI EB) and 100% (PANI ES). A procedure based on this scheme and subsequent structure relaxations using molecular dynamics is described and validated. Using the proposed scheme and the corresponding procedure, atomistic models of amorphous PANI-HCl structures were generated and studied at different doping levels. Density, structure factors, and solubility parameters were calculated. Their values agree well with available experimental data. The interactions of HCl with PANI have been studied and distribution of their energies has been analyzed. The procedure has also been extended to the generation of PANI models including adsorbed water and the effect of inclusion of water molecules on PANI properties has also been modeled and discussed. The protocol described here is general and the proposed United Event Grand Canonical Monte Carlo scheme can be easily extended to similar polymeric materials used in gas sensing and to other systems involving adsorption and chemical reactions steps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Hawaii Utility Integration Initiatives to Enable Wind (Wind HUI) (Final Technical Report)

To advance the state and nation toward clean energy, Hawaii is pursuing an aggressive Renewable Portfolio Standard (RPS), 40% renewable generation and 30% energy efficiency and transportation initiatives by 2030. Additionally, with support from federal, state and industry leadership, the Hawaii Clean Energy Initiative (HCEI) is focused on reducing Hawaii's carbon footprint and global warming impacts. To keep pace with the policy momentum and changing industry technologies, the Hawaiian Electric Companies are proactively pursuing a number of potential system upgrade initiatives to better manage variable resources like wind, solar and demand-side and distributed generation alternatives (i.e. DSM, DG).

17 WIND ENERGY↗

DOE OSTI2010

Filamentation of Beam-Shaped Femtosecond Laser Pulses

When ultra-intense and ultra-short optical pulses propagate in transparent dielectrics, the dynamic balance between multiple linear and nonlinear effects results in the generation of laser filaments. These peculiar objects have numerous interesting properties and can be potentially used in a variety of applications from remote sensing to the optical pulse compression down to few optical cycles to guiding lightning discharges away from sensitive sites. Materializing this practical potential is not straightforward owing to the complexity of the physical picture of filamentation. In this paper, we discuss recent experiments on using beam shaping as a means of control over the filament formation and dynamics. Two particular beam shapes that we have investigated so far are Bessel and Airy beams. The diffraction-free propagation of femtosecond Bessel beams allows for the creation of extended plasma channels in air. These extended filaments can be used for the generation of energetic optical pulses with the duration in the few-cycle range. In the case of filamentation of femtosecond Airy beams, the self-bending property of these beams allows for the creation of curved filaments. This is a new regime of the intense laser-pulse propagation in which the linear self-bending property of the beam competes against the nonlinear self-channeling. The bent filaments generated by ultra-intense Airy beams emit forward-propagating broadband radiation. Analysis of the spatial and spectral distribution of this emission provides for a valuable tool for analyzing the evolution of the ultra-intense optical pulse along the optical path.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Modelling of radiative transfer by the Monte Carlo method and solving the inverse problem based on a genetic algorithm according to experimental results of aerosol sensing on short paths using a femtosecond laser source

We consider the algorithms that implement a broadband ('multiwave') radiative transfer with allowance for multiple (aerosol) scattering and absorption by main atmospheric gases. In the spectral range of 0.6 – 1 μm, a closed numerical simulation of modifications of the supercontinuum component of a probing femtosecond pulse is performed. In the framework of the algorithms for solving the inverse atmospheric-optics problems with the help of a genetic algorithm, we give an interpretation of the experimental backscattered spectrum of the supercontinuum. An adequate reconstruction of the distribution mode for the particles of artificial aerosol with the narrow-modal distributions in a size range of 0.5 – 2 mm and a step of 0.5 mm is obtained. (light scattering)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks

Gigapixel images are prevalent in scientific domains ranging from remote sensing, and satellite imagery to microscopy, etc. However, training a deep learning model at the natural resolution of those images has been a challenge in terms of both, overcoming the resource limit (e.g. HBM memory constraints), as well as scaling up to a large number of GPUs. In this paper, we trained Residual neural Networks (ResNet) on 22,528 x 22,528-pixel size images using a distributed spatial decomposition method on 2,304 GPUs on the Summit Supercomputer. We applied our method on a Whole Slide Imaging (WSI) dataset from The Cancer Genome Atlas (TCGA) database. WSI images can be in the size of 100,000 x 100,000 pixels or even larger, and in this work we studied the effect of image resolution on a classification task, while achieving state-of-the-art AUC scores. Moreover, our approach doesn't need pixel-level labels, since we're avoiding patching from the WSI images completely, while adding the capability of training arbitrary large-size images. This is achieved through a distributed spatial decomposition method, by leveraging the non-block fat-tree interconnect network of the Summit architecture, which enabled GPU-to-GPU direct communication. Finally, detailed performance analysis results are shown, as well as a comparison with a data-parallel approach when possible.

Tsaris, Aristeidis (aris)↗