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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A mixed-integer PDE-constrained optimization formulation for constructing electromagnetic cloaks with multiple materials

We study the design of an electromagnetic cloak from multiple materials with an additional constraint on the mass of the cloak. Our problem is an example of a topology optimization problem, and we formulate this problem as a mixed-integer partial-differential equation constrained optimization (MIPDECO) problem, where Maxwell’s equation models the propagation of the wave through the cloak and surrounding medium. We use binary variables to model the assignment of the different materials, and their relevant properties (permittivity and density). The mass constraint adds a nontrivial constraint to this problem. We propose a two-phase strategy to solve this problem. In the first phase, we solve a continuous relaxation, and then propose a new variant of the feasibility pump that exploits the structure of the PDE to obtain an initial integral solution candidate. In the second phase, we use a trust-region approach to improve this incumbent. We also consider a continuation or mesh-sequencing approach to find better solutions faster on consecutively finer meshes. We present detailed numerical results to illustrate the effectiveness of our approaches for constructing multi-material cloaks with a mass constraint.

Calculus of Variations and Optimization↗
DOE OSTI2020

Clumped isotope constraints on changes in latest Pleistocene hydroclimate in the northwestern Great Basin: Lake Surprise, California

Abstract During the Last Glacial Maximum (LGM) and subsequent deglaciation, the Great Basin in the southwestern United States was covered by numerous extensive closed-basin lakes, in stark contrast with the predominately arid climate observed today. This transition from lakes in the Late Pleistocene to modern aridity implies large changes in the regional water balance. Whether these changes were driven by increased precipitation rates due to changes in atmospheric dynamics, decreased evaporation rates resulting from temperature depression and summer insolation changes, or some combination of the two remains uncertain. The factors contributing to these large-scale changes in hydroclimate are critical to resolve, given that this region is poised to undergo future anthropogenic-forced climate changes with large uncertainties in model simulations for the 21st century. Furthermore, there are ambiguous constraints on the magnitude and even the sign of changes in key hydroclimate variables between the Last Glacial Maximum and the present day in both proxy reconstructions and climate model analyses of the region. Here we report thermodynamically derived estimates of changes in temperature, precipitation, and evaporation rates, as well as the isotopic composition of lake water, using clumped isotope data from an ancient lake in the northwestern Great Basin, Lake Surprise (California). Compared to modern climate, mean annual air temperature at Lake Surprise was 4.7 °C lower during the Last Glacial Maximum, with decreased evaporation rates and similar precipitation rates to modern. During the mid-deglacial period, the growth of Lake Surprise implied that the lake hydrologic budget briefly departed from steady state. Our reconstructions indicate that this growth took place rapidly, while the subsequent lake regression took place over several thousand years. Using models for precipitation and evaporation constrained from clumped isotope results, we determine that the disappearance of Lake Surprise coincided with a moderate increase in lake temperature, along with increasing evaporation rates outpacing increasing precipitation rates. Concomitant analysis of proxy data and climate model simulations for the Last Glacial Maximum are used to provide a robust means to understand past climate change, and by extension, predict how current hydroclimates may respond to expected future climate forcings. We suggest that an expansion of this analysis to more basins across a larger spatial scale could provide valuable insight into proposed climate forcings, and aid in climate model process depiction. Ultimately, our analysis highlights the importance of temperature-driven evaporation as a mechanism for lake growth and retreat in this region.

Geology↗
DOE OSTI2025

A unified funnel restoration SQP algorithm

We consider nonlinearly constrained optimization problems and discuss a generic double-loop framework consisting of basic algorithmic ingredients that unifies a broad range of nonlinear optimization solvers. This framework has been implemented in the open-source solver Uno, a Swiss Army knife-like C++ optimization framework that unifies many nonlinearly constrained nonconvex optimization solvers. We illustrate the framework with a sequential quadratic programming (SQP) algorithm that maintains an acceptable upper bound on the constraint violation, called a funnel, that is monotonically decreased to control the feasibility of the iterates. Infeasible quadratic subproblems are handled by a feasibility restoration strategy. Globalization is controlled by a line search or a trust-region method. We prove global convergence of the trust-region funnel SQP method, building on known results from filter methods. We implement the algorithm in Uno, and we provide extensive test results for the trust-region line-search funnel SQP on small CUTEst instances.

Kiessling, David [Katholieke Univ. Leuven, Heverle↗
DOE OSTI2025

Transformation rate maps of dissolved organic carbon in the contiguous US

Riverine dissolved organic carbon (DOC) plays a vital role in regional and global carbon cycles. However, the processes of DOC conversion from soil organic carbon (SOC) and leaching into rivers are insufficiently understood, inconsistently represented, and poorly parameterized, particularly in land surface and Earth system models. As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux (P r ), accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. We then derive high-resolution P r maps over the contiguous US (CONUS) using SOC data from two different sources: the Harmonized World Soil Database v1.2 (HWSD) and SoilGrids 2.0. Both maps are developed following the same five major steps: (1) selecting independent catchments where observed riverine DOC data are available with reasonable quality; (2) estimating catchment-average SOC for the independent catchments; (3) estimating the P r values for these catchments based on the generic formula and catchment-average SOC; (4) developing a predictive model of P r with machine learning (ML) techniques and catchment-scale climate, hydrology, geology, and other attributes; and (5) deriving a national map of P r based on the ML model. For evaluation, we compare the DOC concentration derived using the P r map and the observed DOC concentration values at evaluation catchments. The resulting mean absolute scaled error and coefficient of determination are 0.73 and 0.47 for the HWSD-based model and 0.58 and 0.72 for the SoilGrids-based model, respectively, suggesting the effectiveness of the overall methodology. Efforts to constrain uncertainty and evaluate sensitivity of P r to different factors are discussed. To illustrate the use of such maps, we derive a riverine DOC concentration reanalysis dataset over CONUS. The two P r maps, robustly derived and empirically validated, lay a critical cornerstone for better simulating the terrestrial carbon cycle in land surface and Earth system models. Our findings not only set a foundation for improving our predictive understanding of the terrestrial carbon cycle at the regional and global scales, but also hold promises for informing policy decisions related to decarbonization and climate change mitigation. The data presented in this study are publicly available at https://doi.org/10.5281/zenodo.14563816 (Li et al., 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

R -parity violation axiogenesis

We show that the rotation of the QCD axion field, aided by B–L violation from supersymmetric R-parity violating couplings, can yield the observed baryon abundance. Strong sphaleron processes transfer the angular momentum of the axion field into a quark chiral asymmetry, which R-parity violating couplings convert to the baryon asymmetry of the Universe. We focus on the case of dimensionless R-parity violating couplings with textures motivated by grand unified theories and comment on more general scenarios. The axion decay constant and mass spectrum of supersymmetric particles are constrained by Big Bang nucleosynthesis, proton decay from the R-parity violation, and successful thermalization of the Peccei-Quinn symmetry breaking field. Axion dark matter may be produced by the axion rotation via the kinetic misalignment mechanism for axion decay constants below 10 10 GeV, or by the conventional misalignment mechanism for 10 11-12 GeV. The viable parameter region can be probed by proton decay and axion searches. This scenario may also have connections with collider experiments, including searches for long-lived particles, and observations of gravitational waves.

Beyond Standard Model↗
DOE OSTI2026

Understanding the effect of friction stir processing on electrical steel: Microstructural changes and mechanical transformations

Raising Si beyond 3.5 wt% reduces core loss but embrittles electrical steels, constraining processing and application. Here we assess friction stir processing (FSP) as a solid‑state route to enable Fe–4.0 wt% Si with improved mechanical performance. Temperature‑controlled FSP with a PcBN tool produced a defect‑free processed zone. SEM/EBSD revealed dynamic recrystallization and grain refinement from an average 110 μm in the base material to ∼20 μm in the processed region, with ∼ 80% of grains < 40 μm and a reduction in high‑angle boundary fraction to ∼65% (vs >85% in the base). Comparative mechanical property analysis shows a moderate increase in yield strength in FSP samples relative to the base material, with a significant improvement in ductility (∼35–50%). Post‑fracture EBSD identified 60° twin boundaries in the base while sub-grain formation with elevated KAM in the FSP sample. Fractography revealed a shift from quasi‑cleavage in the Base-faceted planes with river patterns, steps, and occasional secondary cracks—to ductile micro void coalescence after FSP. Following FSP, the material retains soft‑magnetic behavior, with modest shifts in saturation magnetization consistent with grain refinement and stored strain, accompanied by a clear gain in formability. These results indicate that FSP provides a viable route to deploy higher‑Si electrical steels with concurrent gains in strength and ductility.

Electrical steel↗
DOE OSTI2021

Constraints on MeV dark matter and primordial black holes: Inverse Compton signals at the SKA

Here we investigate the possibilities for probing MeV dark matter (DM) particles and primordial black holes (PBHs) (for masses ~ 10 15 –10 17 g) at the upcoming radio telescope SKA, using photon signals from the Inverse Compton (IC) effect within a galactic halo. Pair-annihilation or decay of MeV DM particles (into e + e - pairs) or Hawking radiation from a population of PBHs generates mildly relativistic e ± which can lead to radio signals through the IC scattering on low energy cosmic microwave background (CMB) photons. We study the ability of SKA to detect such signals coming from nearby ultra-faint dwarf galaxies Segue I and Ursa Major II as well as the globular cluster ω-cen and the Coma cluster. We find that with ~ 100 hours of observation, the SKA improves the Planck constraints on the DM annihilation/decay rate and the PBH abundance for masses in the range ~ 1 to few tens of MeV and above 10 15 to 10 17 g, respectively. Importantly, the SKA limits are independent of the assumed magnetic fields within the galaxies. Previously allowed regions of diffusion parameters of MeV electrons inside a dwarf galaxy that give rise to observable signals at the SKA are also excluded. For objects like dwarf galaxies, predicted SKA constraints depend on both the DM and diffusion parameters. Independent observations in different frequency bands, e.g., radio and γ-ray frequencies, may break this degeneracy and thus enable one to constrain the combined parameter space of DM and diffusion. However, the constraints are independent of diffusion parameters for galaxy clusters such as Coma.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

BICEP/ Keck XII: Constraints on axionlike polarization oscillations in the cosmic microwave background

Here, we present a search for axionlike polarization oscillations in the cosmic microwave background (CMB) with observations from the Keck Array . A local axion field induces an all-sky, temporally sinusoidal rotation of CMB polarization. A CMB polarimeter can thus function as a direct-detection experiment for axionlike dark matter. We develop techniques to extract an oscillation signal. Many elements of the method are generic to CMB polarimetry experiments and can be adapted for other datasets. As a first demonstration, we process data from the 2012 observing season to set upper limits on the axion-photon coupling constant in the mass range 10 – 21 – 10 – 18 eV , which corresponds to oscillation periods on the order of hours to months. We find no statistically significant deviations from the background model. For periods larger than 24 hr (mass m < 4.8 × 10 – 20 eV ), the median 95% confidence upper limit is equivalent to a rotation amplitude of 0.68°, which constrains the axion-photon coupling constant to g Φ γ < ( 1.1 × 10 – 11 GeV – 1 ) m / ( 10 – 21 eV ) , if axionlike particles constitute all of the dark matter. The constraints can be improved substantially with data already collected by the BICEP series of experiments. Current and future CMB polarimetry experiments are expected to achieve sufficient sensitivity to rule out unexplored regions of the axion parameter space.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

In situ investigation of phosphonate retarder interaction in oil well cements at elevated temperature and pressure conditions

In this paper, the effect of a high-performance retarding additive in oil well cements was investigated under elevated temperature (165°C) and pressure (1000 psi) conditions via in situ synchrotron-based X-ray diffraction (XRD) and quasielastic neutron scattering (QENS) techniques. Under these temperature and pressure conditions, crystalline calcium silicate hydrates (C–S–H) are formed through the cement hydration process. From in situ XRD experiments, the retardation effect was observed by a change in the rate of the appearance of 11 Å tobermorites as well as a change in the rate of the α-C 2 SH generation and depletion. QENS analysis revealed that the retardation effect was related to the non-conversion of free water to chemical and constrained water components. A high presence of free water components was attributed to a decrease in 11Å tobermorites along with slower consumption of the quartz and portlandite phases. Furthermore, QENS results infer that the water molecules experienced confinement in the restricted pore spaces. The retarder inhibited this initial water confinement by slowing the bulk diffusion of free water in the confined region.

36 MATERIALS SCIENCE↗
DOE OSTI2024

B1-B2 transition in shock-compressed MgO

Magnesium oxide (MgO) is a major component of the Earth’s mantle and is expected to play a similar role in the mantles of large rocky exoplanets. At extreme pressures, MgO transitions from the NaCl B1 crystal structure to a CsCl B2 structure, which may have implications for exoplanetary deep mantle dynamics. In this study, we constrain the phase diagram of MgO with laser-compression along the shock Hugoniot, with simultaneous measurements of crystal structure, density, pressure, and temperature. We identify the B1 to B2 phase transition between 397 and 425 gigapascal (around 9700 kelvin), in agreement with recent theory that accounts for phonon anharmonicity. From 425 to 493 gigapascal, we observe a mixed-phase region of B1 and B2 coexistence. The transformation follows the Watanabe-Tokonami-Morimoto mechanism. Our data are consistent with B2-liquid coexistence above 500 gigapascal and complete melting at 634 gigapascal. This study bridges the gap between previous theoretical and experimental studies, providing insights into the timescale of this phase transition.

58 GEOSCIENCES↗
DOE OSTI2020

Measurements of proton capture in the A=100–110 mass region: Constraints on the In 111 (γ,p)/(γ,n) branching point relevant to the γ process

The γ process is an explosive astrophysical scenario, which is thought to be the primary source of the rare proton-rich stable p nuclei. However, current γ-process models remain insufficient in describing the observed p-nuclei abundances, with disagreements up to two orders of magnitude. A sensitivity study has identified 111 In as a model-sensitive (γ,p)/(γ,n) branching point within the γ process. Constraining the involved reaction rates may have a significant impact on the predicted p-nuclei abundances. Here we report on measurements of the cross sections for 102 Pd (p,γ) 103 Ag, 108 Cd (p,γ) 109 In, and 110 Cd (p,γ) 111 In reactions for proton laboratory energies 3–8 MeV using the high efficiency total absorption spectrometer and the γ-summing technique. These measurements were used to constrain Hauser-Feshbach parameters used in talys 1.9, which constrains the 111 In(γ,p) 110 Cd and 111 In(γ,n) 110 Ag reaction rates. The newly constrained reaction rates indicate that the 111 In(γ,p)/(γ,n) branching point occurs at a temperature of 2.71 ± 0.05 GK, well within the temperature range relevant to the γ process. These findings differ significantly from previous studies and may impact the calculated abundances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign

Numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, are widely used to provide estimates of the offshore wind energy resource owing to their large spatial coverage compared to available observations. Nevertheless, spatiotemporal distribution of model biases is highly dependent on factors including model configuration, location, and the interplay of multi-scale physical processes. Here, in this study, we focus on the characterization of model uncertainties in simulated coast-to-offshore winds over the northeast U.S., by varying sea surface temperature (SST) forcings, surface layer (SL) and planetary boundary layer (PBL) parameterizations, as well as identifying biases that may be directly passed from initial and boundary conditions. Multiple measurements, including aircraft data collected during the U.S. Department of Energy's Two-Column Aerosol Project (TCAP) experiment, are used to constrain the model results and facilitate quantitative comparisons. Our analysis indicates while SST forcing has notable impacts on simulated air temperature and moisture within PBL, the modeled winds are in general more sensitive to the choices of SL and PBL physics than to SST. The model’s forcing data not only controls the vertical dependence of wind speed errors, but also alters regional variability in wind speed’s spatial correlation. Bias comparisons between ERA5 reanalysis and ensemble simulations revealed significant similarity, particularly in wind speed biases during winter, underscoring their dependency on initial and boundary conditions. Coastal and offshore near-surface wind speed biases tend to exhibit much higher similarity in winter than in summer due to the presence of much stronger and more persistent synoptic wind conditions. This study highlights the importance of accurate atmospheric forcing and parameterization choices in improving wind forecasts and suggests the potential for extrapolating coastal wind biases to offshore locations, aiding wind energy forecasting and informing the Wind Forecast Improvement Project-3 (WFIP3).

17 WIND ENERGY↗
DOE OSTI2022

SCONCE : a cosmic web finder for spherical and conic geometries

The latticework structure known as the cosmic web provides a valuable insight into the assembly history of large-scale structures. Despite the variety of methods to identify the cosmic web structures, they mostly rely on the assumption that galaxies are embedded in a Euclidean geometric space. Here, we present a novel cosmic web identifier called SCONCE (Spherical and CONic Cosmic wEb finder) that inherently considers the 2D (RA, DEC) spherical or the 3D (RA, DEC, z) conic geometry. The proposed algorithms in sconce generalize the well-known subspace constrained mean shift (SCMS) method and primarily address the predominant filament detection problem. They are intrinsic to the spherical/conic geometry and invariant to data rotations. We further test the efficacy of our method with an artificial cross-shaped filament example and apply it to the SDSS galaxy catalogue, revealing that the 2D spherical version of our algorithms is robust even in regions of high declination. Finally, using N-body simulations from Illustris, we show that the 3D conic version of our algorithms is more robust in detecting filaments than the standard SCMS method under the redshift distortions caused by the peculiar velocities of haloes. Our cosmic web finder is packaged in python as SCONCE-SCMS and has been made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗
DOE OSTI2023

The transmission ramifications of social and environmental siting considerations on wind energy deployment

Increasing the capacity of wind power is critical to achieving climate goals, however its continued deployment faces environmental and social siting challenges. For example, the United States government is increasingly emphasizing the importance of a just energy transition by considering the social impacts of energy and environmental justice (EEJ). In this study, we investigate the impact of considering available EEJ metrics and environmental impacts into siting wind power and transmission by applying SimWIND PRO . SimWIND PRO is an infrastructure optimization tool that can site wind energy technologies and transmission by concurrently considering wind resource potential, transmission costs, EEJ, and environmental impacts. We demonstrate the impacts of considering EEJ and environmental factors in the context of Midcontinent Independent System Operator’s (MISO) western region, which includes some of the best wind energy potential in the United States. We show that prioritizing EEJ and environmental considerations in wind deployment can result in exponentially more transmission deployment for the same amount of wind power delivered, and results in selecting different wind farm sites. Our results also show that, depending on how it is considered, it is possible that constraining sites based on EEJ and environmental factors can reduce the available capacity of wind energy enough that energy transition capacity targets cannot be met.

17 WIND ENERGY↗
DOE OSTI2022

Searches for Neutrinos from Gamma-Ray Bursts Using the IceCube Neutrino Observatory

Gamma-ray bursts (GRBs) are considered as promising sources of ultra-high-energy cosmic rays (UHECRs) due to their large power output. Observing a neutrino flux from GRBs would offer evidence that GRBs are hadronic accelerators of UHECRs. Previous IceCube analyses, which primarily focused on neutrinos arriving in temporal coincidence with the prompt gamma-rays, found no significant neutrino excess. The four analyses presented in this paper extend the region of interest to 14 days before and after the prompt phase, including generic extended time windows and targeted precursor searches. GRBs were selected between 2011 May and 2018 October to align with the data set of candidate muon-neutrino events observed by IceCube. No evidence of correlation between neutrino events and GRBs was found in these analyses. Limits are set to constrain the contribution of the cosmic GRB population to the diffuse astrophysical neutrino flux observed by IceCube. Prompt neutrino emission from GRBs is limited to ≲1% of the observed diffuse neutrino flux, and emission on timescales up to 10 4 s is constrained to 24% of the total diffuse flux.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Observationally constrained analysis of sulfur cycle in the marine atmosphere with NASA ATom measurements and AeroCom model simulations

The atmospheric sulfur cycle plays a key role in air quality, climate, and ecosystems, such as pollution, radiative forcing, new particle formation, and acid rain. In this study, we compare the spatially and temporally resolved measurements from the NASA Atmospheric Tomography (ATom) mission with simulations from five AeroCom III models for four sulfur species (dimethyl sulfide (DMS), sulfur dioxide (SO 2 ), particulate methanesulfonate (MSA), and particulate sulfate (SO 4 )). We focus on remote regions over the Pacific, Atlantic, and Southern oceans from near the surface to ~12 km altitude range covering all four seasons. In general, the differences among model results can be greater than 1 order of magnitude. Comparing with observations, model-simulated SO 2 is generally low, whereas SO 4 is generally high. Simulated DMS concentrations near the sea surface exceed observed levels by a factor of 5 in most cases, suggesting potential overestimation of DMS emissions in all models. With GEOS model simulations of tagging emission from anthropogenic, biomass burning, volcanic, and oceanic sources, we find that anthropogenic emissions are the dominant source of sulfate aerosol (40 %–60 % of the total amount) in the ATom measurements at almost all altitudes, followed by volcanic emissions (18 %–32 %) and oceanic sources (16 %–32 %). Similar source contributions can also be derived at broad ocean basins and on monthly scales, indicating the representativeness of ATom measurements for global ocean. Our work presents the first assessment of AeroCom sulfur study using ATom measurements, providing directions for improving sulfate simulations, which remain the largest uncertainty in radiative forcing estimates in aerosol climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multimodal characterization of Te inclusions in Cd 1−x Zn x Te and Cd 1−x Zn x Te 1−y Se y for gamma and X-ray detectors

While CdZnTe (CZT) and CdZnTeSe (CZTS) semiconductors have emerged as compounds for room-temperature gamma and X-ray detection materials, they continue to be constrained by the formation of Te-inclusion defects generated during the growth and post-growth phases of the material, which adversely affect the detector performance. We demonstrate the utility of multimodal microscopic imaging and analysis for the characterization of the optical and electronic properties of Te inclusions in CZT and CZTS crystals at both micron and nanometer length scales. Having first identified regions with micron-scale Te inclusions using confocal Raman microscopy techniques, optically coupled infrared scattering near-field optical microscopic mapping was performed to map the distribution of these inclusions with nanometer spatial resolution and correlate the presence of Te inclusions in the matrix with other properties. Kelvin probe force microscopy was then utilized to characterize the variations of the work function associated with the presence of Te inclusions. Here, we observe an increase of ~ 240 mV in the work function associated with Te inclusions compared to the bulk CZT/CZTS crystals. Additionally, we observe that individual bulk grains in CZT can exhibit slight potential variations. Our findings develop a portrait of the charge trapping mechanisms in CZT and CZTS that act to degrade detector performance, while the demonstration of these combined microscopy techniques provides a new analytical tool that can be utilized for further optimization of the detector performance for these semiconducting compounds.

36 MATERIALS SCIENCE↗