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DOE OSTI2026

Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)

This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Robust Heat-Flux Sensors for Coal-Fired Boiler Extreme Environments

In this project, robust heat-flux measurement systems were developed. The heat-flux sensors utilize thermoelectric effects to directly transduce the heat-flux inputs to analog electrical voltage signals. They were constructed from dedicated materials that can withstand temperatures of at least 1000°C and maintain adequate performance at these conditions for prolonged periods of time. The proposed approaches took into account numerous considerations, including system cost, sensor head resilience, sensor footprint, data accuracy, response time, and maintenance requirements. Through modern thermoelectric materials design, methodical materials selection and rigorous testing in materials characterization labs and medium-scale fire research facilities, we have demonstrated functioning laboratory prototypes, upon which one could base industrial heat-flux sensing platforms capable of operating in the challenging high-temperature, corrosive environments of the boilers of coal-fired power plants. A distributed sensor array for heat-flux measurements throughout the furnace water-wall, the superheater area and the economizer coils can provide critical data for the power plant control systems to increase efficiency, improve safety and reduce down times. For example, the combined heat-flux sensor/control systems can contribute to the optimization of burner and boiler operations under flexible loads, the optimization of heat-exchange conditions and overall reduction of heat rate and emissions, the prediction of imminent overheating conditions, and the optimization of the soot-blowing protocols.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2010

Inverse Method for Estimating the Spatial Variability of Soil Particle Size Distribution from Observed Soil Moisture

Soil particle size distribution (PSD) (i.e., clay, silt, sand, and rock contents) information is one of critical factors for understanding water cycle since it affects almost all of water cycle processes, e.g., drainage, runoff, soil moisture, evaporation, and evapotranspiration. With information about soil PSD, we can estimate almost all soil hydraulic properties (e.g., saturated soil moisture, field capacity, wilting point, residual soil moisture, saturated hydraulic conductivity, pore-size distribution index, and bubbling capillary pressure) based on published empirical relationships. Therefore, a regional or global soil PSD database is essential for studying water cycle regionally or globally. At the present stage, three soil geographic databases are commonly used, i.e., the Soil Survey Geographic database, the State Soil Geographic database, and the National Soil Geographic database. Those soil data are map unit based and associated with great uncertainty. Ground soil surveys are a way to reduce this uncertainty. However, ground surveys are time consuming and labor intensive. In this study, an inverse method for estimating mean and standard deviation of soil PSD from observed soil moisture is proposed and applied to Throughfall Displacement Experiment sites in Walker Branch Watershed in eastern Tennessee. This method is based on the relationship between spatial mean and standard deviation of soil moisture. The results indicate that the suggested method is feasible and has potential for retrieving soil PSD information globally from remotely sensed soil moisture data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Constraining the Multiscale Structure of Geophysical Fields in Machine Learning: The Case of Precipitation

The use of deep-learning algorithms for estimating the value of geophysical variables from remotely sensed information is rapidly expanding. The typical objective function minimized in such algorithms is the mean square error (MSE), which is known to lead to smooth estimates with compressed dynamical range as compared to the true distribution of the variable of interest. Here, we introduce and evaluate alternative objective functions, focusing on the retrieval of precipitation rates from satellite passive microwave radiometric measurements using a deep convolutional neural network. For this testbed application, the results show that explicitly imposing the preservation of the statistical distribution and spatial wavelet power spectrum of the target variable allows to accurately reproduce extreme values and sharp gradients across multiple scales in this study.

58 GEOSCIENCES↗

DOE OSTI2018

Superior signal persistence of circularly polarized light in polydisperse, real-world fog environments

Here, we present simulation results quantitatively showing that circularly polarized light persists in transmission through several real-world and model fog environments better than linearly polarized light over broad wavelength ranges from the visible through the infrared. We present results for polydisperse particle distributions from realistic and measured fog environments, comparing the polarization persistence of linear and circular polarization. Using a polarization-tracking Monte Carlo program, we simulate polarized light propagation through four MODTRAN fog models (moderate and heavy radiation fog and moderate and heavy advection fog) and four real-world measured fog particle distributions (Garland measured radiation and advection fogs, Kunkel measured advection fog, and Sandia National Laboratories’ Fog Facility’s fog). Simulations were performed for each fog environment with wavelengths ranging from 0.4 to 12 µm for increasing optical thicknesses of 5, 10, and 15 (increasing fog density or sensing range). Circular polarization persists superiorly for all optical wavelength bands from the visible to the long-wave infrared in nearly all fog types for all optical thicknesses. Throughout our analysis, we show that if even a small percentage of a fog’s particle size distribution is made up of large particles, those particles dominate the scattering process. In nearly all real-world fog situations, these large particles and their dominant scattering characteristics are present. Larger particles are predominantly forward-scattering and contribute to circular polarization’s persistence superiority over broad wavelength ranges and optical thicknesses/range. Circularly polarized light can transmit over 30% more signal in its intended state compared to linearly polarized light through real-world fog environments. This work broadens the understanding of how circular polarization persists through natural fog particle distributions with natural variations in mode particle radius and single or bimodal characteristics.

47 OTHER INSTRUMENTATION↗

DOE OSTI2011

Catalytic Consequences of Acid Strength in the Conversion of Methanol to Dimethyl Ether

The effects of acid identity on CH{sub 3}OH dehydration are examined here using density functional theory (DFT) estimates of acid strength (as deprotonation energies, DPE) and reaction energies, combined with rate data on Keggin polyoxometalate (POM) clusters and zeolite H-BEA. Measured first-order (k{sub mono}) and zero-order (k{sub dimer}) CH3OH dehydration rate constants depend exponentially on DPE for POM clusters; the value of k{sub mono} depends more strongly on DPE than k{sub dimer} does. The chemical significance of these rate parameters and the basis for their dependences on acid strength were established by using DFT to estimate the energies of intermediates and transition states involved in elementary steps that are consistent with measured rate equations. We conclude from this treatment that CH{sub 3}OH dehydration proceeds via direct reactions of co-adsorbed CH{sub 3}OH molecules for relevant solid acids and reaction conditions. Methyl cations formed at ion-pair transition states in these direct routes are solvated by H{sub 2}O and CH{sub 3}OH more effectively than those in alternate sequential routes involving methoxide formation and subsequent reaction with CH{sub 3}OH. The stability of ion-pairs, prevalent as intermediates and transition states on solid acids, depends sensitively on DPE because of concomitant correlations between the stability of the conjugate anionic cluster and DPE. The chemical interpretation of k{sub mono} and k{sub dimer} from mechanism-based rate equations, together with thermochemical cycles of their respective transition state formations, show that similar charge distributions in the intermediate and transition state involved in k{sub dimer} cause its weaker dependence on DPE. Values of k{sub mono} involve uncharged reactants and the same ion-pair transition state as k{sub dimer}; these species sense acid strength differently and cause the larger effects of DPE on k{sub mono}. Confinement effects in H-BEA affect the value of k{sub mono} because the different sizes and number of molecules in reactants and transition states selectively stabilize the latter; however, they do not influence k{sub dimer}, for which reactants and transition states of similar size sense spatial constraints to the same extent. This combination of theory and experiment for solid acids of known structure sheds considerable light on the relative contributions from solvation, electrostatic and van der Waals interactions in stabilizing cationic transition states and provides predictive insights into the relative contributions of parallel routes based on the size and charge distributions of their relevant intermediates and transition states. These findings also demonstrate how the consequences of acid strength on measured turnover rates depend on reaction conditions and their concomitant changes in the chemical significance of the rate parameters measured. Moreover, the complementary use of experiment and theory in resolving mechanistic controversies has given predictive guidance about how rate and equilibrium constants, often inextricably combined as measured rate parameters, individually depend on acid strength based on the magnitude and spatial distributions of charges in reactants, products and transition states involved in relevant elementary steps. The unique relations between k{sub mono}, k{sub dimer} and DPE developed here for CH{sub 3}OH dehydration can be applied in practice to assess the acid strength of any solid acid, many of which have unknown structures, preventing reliable calculations of their DPE by theory.

10 SYNTHETIC FUELS↗

DOE OSTI2016

Mapping Arctic plant functional type distributions in the Barrow Environmental Observatory using WorldView-2 and LiDAR datasets

Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landscape in and around the Barrow Environmental Observatory (BEO), a 3021-hectare research reserve located at the northern edge of the Alaskan Arctic Coastal Plain. Vegetation surveys were conducted during the growing season (June August) of 2012 from 48 1 m 1 m plots in the study region for estimating the percent cover of PFTs (i.e., sedges, grasses, forbs, shrubs, lichens and mosses). Statistical relationships were developed between spectral and topographic remote sensing characteristics and PFT fractions at the vegetation plots from field surveys. These derived relationships were employed to statistically upscale PFT fractions for our study region of 586 hectares at 0.25-m resolution around the sampling areas within the BEO, which was bounded by the LiDAR footprint. We employed an unsupervised clustering for stratification of this polygonal tundra landscape and used the clusters for segregating the field data for our upscaling algorithm over our study region, which was an inverse distance weighted (IDW) interpolation. We describe two versions of PFT distribution maps upscaled by IDW from WorldView-2 imagery and LiDAR: (1) a version computed from a single image in the middle of the growing season; and (2) a version computed from multiple images through the growing season. This approach allowed us to quantify the value of phenology for improving PFT distribution estimates. We also evaluated the representativeness of the field surveys by measuring the Euclidean distance between every pixel. This guided the ground-truthing campaign in late July of 2014 for addressing uncertainty based on representativeness analysis by selecting 24 1 m 1 m plots that were well and poorly represented. Ground-truthing indicated that including phenology had a better accuracy (R 2 =0.75, RMSE=9.94) than the single image upscaling (R 2 =0.63 , RMSE=12.05) predicted from IDW. We also updated our upscaling approach to include the 24 ground-truthing plots, and a second ground-truthing campaign in late August of 2014 indicated a better accuracy for the phenology model (R 2 =0.61 , RMSE=13.78 ) than only using the original 48 plots for the phenology model (R 2 =0.23 , RMSE=17.49). After all, we believe that the cluster-based IDW upscaling approach and the representativeness analysis offer new insights for upscaling high-resolution data in fragmented landscapes. This analysis and approach provides PFT maps needed to inform land surface models in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Using spectral methods to obtain particle size information from optical data: applications to measurements from CARES 2010

Abstract. Multi-wavelength in situ aerosol extinction, absorption and scattering measurements made at two ground sites during the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are analyzed using a spectral deconvolution method that allows extraction of particle-size-related information, including the fraction of extinction produced by the fine-mode particles and the effective radius of the fine mode. The spectral deconvolution method is typically applied to analysis of remote sensing measurements. Here, its application to in situ measurements allows for comparison with more direct measurement methods and validation of the retrieval approach. Overall, the retrieved fine-mode fraction and effective radius compare well with other in situ measurements, including size distribution measurements and scattering and absorption measurements made separately for PM1 and PM10, although there were some periods during which the different methods yielded different results. One key contributor to differences between the results obtained is the alternative, spectrally based definitions of fine and coarse modes from the optical methods, relative to instruments that use a physically defined cut point. These results indicate that for campaigns where size, composition and multi-wavelength optical property measurements are made, comparison of the results can result in closure or can identify unusual circumstances. The comparison here also demonstrates that in situ multi-wavelength optical property measurements can be used to determine information about particle size distributions in situations where direct size distribution measurements are not available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Quantum optical memory for entanglement distribution

Optical photons are powerful carriers of quantum information, which can be delivered in free space by satellites or in fibers on the ground over long distances. Entanglement of quantum states over long distances can empower quantum computing, quantum communications, and quantum sensing. Quantum optical memories are devices designed to store quantum information in the form of stationary excitations, such as atomic coherence, and are capable of coherently mapping these excitations to flying qubits. Quantum memories can effectively store and manipulate quantum states, making them indispensable elements in future long-distance quantum networks. Over the past two decades, quantum optical memories with high fidelities, high efficiencies, long storage times, and promising multiplexing capabilities have been developed, especially at the single-photon level. In this review, we introduce the working principles of commonly used quantum memory protocols and summarize the recent advances in quantum memory demonstrations. We also offer a vision for future quantum optical memory devices that may enable entanglement distribution over long distances.

Lei, Yisheng↗

DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

The Midlatitude Continental Convective Clouds Experiment (MC3E)

The Midlatitude Continental Convective Clouds Experiment (MC3E), a field program jointly led by the U.S. Department of Energy’s Atmospheric Radiation Measurement program and the NASA Global Precipitation Measurement (GPM) Mission, was conducted in south-central Oklahoma during April – May 2011. MC3E science objectives were motivated by the need to improve understanding of midlatitude continental convective cloud system lifecycles, microphysics, and GPM precipitation retrieval algorithms. To achieve these objectives a multi-scale surface- and aircraft-based in situ and remote sensing observing strategy was employed. A variety of cloud and precipitation events were sampled during the MC3E, of which results from three deep convective events are highlighted. Vertical structure, air motions, precipitation drop-size distributions and ice properties were retrieved from multi-wavelength radar, profiler, and aircraft observations for an MCS on 11 May. Aircraft observations for another MCS observed on 20 May were used to test agreement between observed radar reflectivities and those calculated with forward-modeled reflectivity and microwave brightness temperatures using in situ particle size distributions and ice water content. Multi-platform observations of a supercell that occurred on 23 May allowed for an integrated analysis of kinematic and microphysical interactions. A core updraft of 25 ms-1 supported growth of hail and large rain drops. Data collected during the MC3E campaign is being used in a number of current and ongoing research projects and is available through the DOE ARM and NASA data archives.

Jensen, Mark P.↗

DOE OSTI2014

CaCO 3 Precipitation, Transport and Sensing in Porous Media with In Situ Generation of Reactants

Ureolytically driven calcite precipitation is a promising approach for inducing subsurface mineral precipitation, but engineered application requires the ability to control and predict precipitate distribution. To study the coupling between reactant transport and precipitate distribution, columns with defined zones of immobilized urease were used to examine the distribution of calcium carbonate precipitation along the flow path, at two different initial flow rates. As expected, with slower flow precipitate was concentrated toward the upstream end of the enzyme zone and with higher flow the solid was more uniformly distributed over the enzyme zone. Under constant hydraulic head conditions the flow rate decreased as precipitates decreased porosity and permeability. The hydrolysis/precipitation zone was expected to become compressed in the upstream direction. However, apparent reductions in the urea hydrolysis rate and changes in the distribution of enzyme activity, possibly due to CaCO 3 precipitate hindering urea transport to the enzyme, or enzyme mobilization, mitigated reaction zone compression. Co-injected strontium was expected to be sequestered by coprecipitation with CaCO 3 , but the results suggested that coprecipitation was not an effective sequestration mechanism in this system. In addition, spectral induced polarization (SIP) was used to monitor the spatial and temporal evolution of the reaction zone.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A Complex Interplay between Nitric Oxide, Quorum Sensing, and the Unique Secondary Metabolite Tundrenone Constitutes the Hypoxia Response in Methylobacter

Methylobacter species, members of the Methylococcales, have recently emerged as some of the globally widespread, cosmopolitan species that play a key role in the environmental consumption of methane across gradients of dioxygen tensions. In this work, we approached the question of howMethylobacter copes with hypoxia, via laboratory manipulation. Through comparative transcriptomics of cultures grown under high dioxygen partial pressure versus cultures exposed to hypoxia, we identified a gene cluster encoding a hybrid cluster protein along with sensing and regulatory functions. Through mutant analysis, we demonstrated that this gene cluster is involved in the hypoxia stress response. Through additional transcriptomic analyses, we uncovered a complex interconnection between the NO-mediated stress response, quorum sensing, the secondary metabolite tundrenone, and methanol dehydrogenase functions. This novel and complex hypoxia stress response system is so far unique to Methylobacter species, and it may play a role in the environmental fitness of these organisms and in their cosmopolitan environmental distribution.Here, we describe a novel and complex hypoxia response system in a methanotrophic bacterium that involves modules of central carbon metabolism, denitrification, quorum sensing, and a secondary metabolite, tundrenone. This intricate stress response system, so far unique to Methylobacter species, may be responsible for the persistence and activity of these species across gradients of dioxygen tensions and for the cosmopolitan distribution of these organisms in freshwater and soil environments in the Northern Hemisphere, including the fast-melting permafrosts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

A Bayesian Machine Learning Model for Estimating Building Occupancy from Open Source Data

Understanding building occupancy is critical to a wide array of applications including natural hazards loss analysis, green building technologies, and population distribution modeling. Due to the expense of directly monitoring buildings, scientists rely in addition on a wide and disparate array of ancillary and open source information including subject matter expertise, survey data, and remote sensing information. These data are fused using data harmonization methods which refer to a loose collection of formal and informal techniques for fusing data together to create viable content for building occupancy estimation. In this paper, we add to the current state of the art by introducing the Population Data Tables (PDT), a Bayesian based informatics system for systematically arranging data and harmonization techniques into a consistent, transparent, knowledge learning framework that retains in the final estimation uncertainty emerging from data, expert judgment, and model parameterization. PDT probabilistically estimates ambient occupancy in units of people/1000ft2 for over 50 building types at the national and sub-national level with the goal of providing global coverage. The challenge of global coverage led to the development of an interdisciplinary geospatial informatics system tool that provides the framework for capturing, storing, and managing open source data, handling subject matter expertise, carrying out Bayesian analytics as well as visualizing and exporting occupancy estimation results. We present the PDT project, situate the work within the larger community, and report on the progress of this multi-year project.Understanding building occupancy is critical to a wide array of applications including natural hazards loss analysis, green building technologies, and population distribution modeling. Due to the expense of directly monitoring buildings, scientists rely in addition on a wide and disparate array of ancillary and open source information including subject matter expertise, survey data, and remote sensing information. These data are fused using data harmonization methods which refer to a loose collection of formal and informal techniques for fusing data together to create viable content for building occupancy estimation. In this paper, we add to the current state of the art by introducing the Population Data Tables (PDT), a Bayesian model and informatics system for systematically arranging data and harmonization techniques into a consistent, transparent, knowledge learning framework that retains in the final estimation uncertainty emerging from data, expert judgment, and model parameterization. PDT probabilistically estimates ambient occupancy in units of people/1000 ft 2 for over 50 building types at the national and sub-national level with the goal of providing global coverage. The challenge of global coverage led to the development of an interdisciplinary geospatial informatics system tool that provides the framework for capturing, storing, and managing open source data, handling subject matter expertise, carrying out Bayesian analytics as well as visualizing and exporting occupancy estimation results. We present the PDT project, situate the work within the larger community, and report on the progress of this multi-year project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Uncertain role of clouds in shaping summertime atmosphere-sea ice connections in reanalyses and CMIP6 models

Downwelling longwave radiation (DLR) driven by the atmospheric and cloud conditions in the troposphere is suggested to be a dominant factor to determine the summertime net surface energy budget over the Arctic Ocean and thus plays a key role to shape the September sea ice. We use reanalyses and the self-organizing map (SOM) method to distinguish CMIP6 model performance in replicating the observed strong atmosphere-DLR connection. We find all models can reasonably simulate the linkage between key atmosphere variables and the clear sky DLR but behave differently in replicating the atmosphere-DLR connection due to cloud forcing. In ERA5 and strongly coupled models, tropospheric high pressure is associated with decreased clouds in the mid- and high-levels and increased clouds near the surface. This out-of-phase structure indicates that DLR cloud forcing is nearly neutral, making the clear sky DLR more important to bridge JJA circulation to late-summer sea ice. In MERRA-2 and weakly coupled models, tropospheric clouds display a vertically homogeneous reduction; the cloud DLR is thus strongly reduced due to the cooling effect, which partially cancels out the clear sky DLR and makes the total DLR less efficient to translate circulation forcing to sea ice. The differences of cloud vertical distribution in CMIP6 appear to be differentiated by circulation related relative humidity. Therefore, a better understanding of the discrepancy of different reanalyses and remote sensing products is critical to comprehensively evaluate simulated interactions among circulation, clouds, sea ice and energy budget at the surface in summer.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Enhanced Tunability of Gold Nanoparticle Size, Spacing, and Shape for Large-Scale Plasmonic Arrays

Gold nanoparticles are important constituents in plasmonic arrays, lending themselves to electronic, optical, biomedical, sensing, and catalytic applications, among numerous others. Process variables that must be controlled when engineering plasmonic nanoparticle ensembles include nanoparticle size, shape, and spatial distribution on surfaces. The challenge in generating arrays of nanoparticles with control over these three parameters increases dramatically as spatial requirements for uniformity extend to larger processing areas. In this paper, we present a procedure that exploits thermally driven solid-state diffusional dewetting to yield considerable flexibility in generating ensembles of gold nanoparticles. Such submelting dewetting introduces fine control over particle spatial features that are currently difficult to achieve through conventional methods of generating nanoparticle arrays. Because of the simplicity of the process and its area-scalability, solid-state diffusional dewetting is shown here to be a method that could be easily scaled up to apply to large-area plasmonic fabrication processes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Geophysical Monitoring Shows that Spatial Heterogeneity in Thermohydrological Dynamics Reshapes a Transitional Permafrost System

Climate change is causing rapid changes of Arctic ecosystems. Yet, data needed to unravel complex subsurface processes are very rare. Using geophysical and in-situ sensing, this study closes an observational gap associated with thermohydrological dynamics in discontinuous permafrost systems. It highlights the impact of vegetation and snow thickness distribution on subsurface thermohydrological properties and processes. Large snow accumulation near tall shrubs insulates the ground and allows for rapid and downward heat flow. Thinner snowpack above graminoid results in surficial freezing and prevents water from infiltrating into the subsurface. Analyzing short term disturbances, we found that lateral flow could be a driving factor in talik formation. Inter-annual measurements show that deep permafrost temperatures increased by about 0.2°C over two years. The results, which suggest that snow-vegetation-subsurface processes are tightly coupled, will be useful for improving predictions of Arctic feedback to climate change, including how subsurface thermohydrology influences CO 2 and CH 4 fluxes.

58 GEOSCIENCES↗

DOE OSTI2024

THz Radar Observations of Hydrometeors in a Spray Chamber

Abstract A THz radar, with its wide bandwidth, is capable of high‐resolution imaging down to the centimeter scale. In this study, a THz radar is applied to detect hydrometeors generated in a spray chamber. The observed backscattering signals show fluctuations at centimeter scales, indicating various hydrometeor distribution patterns along the radar beam. A co‐located High‐Speed Imaging (HSI) sensor is used to measure the Drop Size Distributions (DSD) in the spray chamber. The radar sampling beam is well aligned with the HSI probes, allowing an objective comparison between the remote sensing and in situ observations. In this study, the observed radar power is compared with the power estimated from the HSI measurements. Results show great consistency, with power difference smaller than 0.5 dB. This study demonstrates the feasibility and great potential of using a THz radar for ultra‐high‐resolution observations of clouds in a laboratory facility, and in the real atmosphere.

54 ENVIRONMENTAL SCIENCES↗