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At least 181 records · Page 10

Elevations in Tumor Necrosis Factor Alpha and Interleukin 6 From Neuronal-Derived Extracellular Vesicles in Repeated Low-Level Blast Exposed Personnel

The purpose of this pilot study was to determine if military service members with histories of hundreds to thousands of low-level blast exposures (i. e., experienced breachers) had different levels of serum and neuronal-derived extracellular vesicle (EV) concentrations of interleukin (IL)-6, IL-10, and tumor necrosis factor alpha (TNFα), compared to matched controls, and if these biomarkers related to neurobehavioral symptoms. Participants were experienced breachers (n = 20) and matched controls without blast exposures (n = 14). Neuronal-derived EVs were isolated from serum and identified with mouse anti-human CD171. Serum and neuronal-derived EVs were analyzed for IL-6, IL-10, and TNFα using an ultra-sensitive assay. Serum TNFα concentrations were decreased in breachers when compared to control concentrations (p < 0.01). There were no differences in serum concentrations of IL-6, IL-10, or the IL-6/IL-10 ratio between breachers and controls (p's > 0.01). In neuronal-derived EVs, TNFα and IL-6 levels were increased in breachers compared to controls (p's < 0.01), and IL-10 levels were decreased in the breacher group compared to controls (p < 0.01). In breachers the IL-6/IL-10 ratio in neuronal-derived EVs was higher compared to controls, which correlated with higher total Rivermead Post-concussion Questionnaire (RPQ) scores (p's < 0.05). These findings suggest that exposure of personnel to high numbers of low-level blast over a career may result in enduring central inflammation that is associated with chronic neurological symptoms. The data also suggest that peripheral markers of inflammation are not necessarily adequate surrogates for central neuroinflammation.

59 BASIC BIOLOGICAL SCIENCES↗

Measurement report: Comparison of wintertime individual particles at ground level and above the mixed layer in urban Beijing

Beijing has been suffering from frequent severe air pollution events, with concentrations affected significantly by the mixed-layer height. Major efforts have been made to study the physico-chemical properties, compositions, and sources of aerosol particles at ground level. However, little is known about the morphology, elemental composition, and mixing state of aerosol particles above the mixed layer. In this work, we collected individual aerosol particles simultaneously at ground level (2 m above ground) and above the mixed layer in urban Beijing (within the Atmospheric Pollution and Human Health in a Chinese Megacity, APHH-Beijing, 2016 winter campaign). The particles were analyzed offline by transmission electron microscopy coupled with energy dispersive X-ray spectroscopy. Our results showed that the relative number contribution of mineral particles to all measured particles was much higher during non-haze periods (42.5 %) than haze periods (18.1 %); in contrast, internally mixed particles contributed more during haze periods (21.9 %) than non-haze periods (7.2 %) at ground level. In addition, more mineral particles were found at ground level than above the mixed-layer height. Around 20 % of individual particles showed core–shell structures during haze periods, whereas only a few core–shell particles were observed during non-haze periods (2 %). The results showed that the particles above the mixed layer were more aged, with a larger proportion of organic particles originating from coal combustion. Our results indicate that a large fraction of the airborne particles above the mixed layer come from surrounding areas influenced by coal combustion activities. This source contributes to the surface particle concentrations in Beijing when polluted air is mixed down to the ground level.

54 ENVIRONMENTAL SCIENCES↗

The contribution of Humboldt Glacier, northern Greenland, to sea-level rise through 2100 constrained by recent observations of speedup and retreat

Abstract. Humboldt Glacier, northern Greenland, has retreated and accelerated through the 21st century, raising concerns that it could be a significant contributor to future sea-level rise. We use a data-constrained ensemble of three-dimensional higher-order ice sheet model simulations to estimate the likely range of sea-level rise from the continued retreat of Humboldt Glacier. We first solve for basal traction using observed ice thickness, bed topography, and ice surface velocity from the year 2007 in a PDE-constrained (partial differential equation) optimization. Next, we impose calving rates to match mean observed retreat rates from winter 2007–2008 to winter 2017–2018 in a transient calibration of the exponent in the power-law basal friction relationship. We find that power-law exponents in the range of 1/7–1/5 – rather than the commonly used 1/3–1 – are necessary to reproduce the observed speedup over this period. We then tune an iceberg calving parameterization based on the von Mises stress yield criterion in another transient-calibration step to approximate both observed ice velocities and terminus position in 2017–2018. Finally, we use the range of basal friction relationship exponents and calving parameter values to generate the ensemble of model simulations from 2007–2100 under three climate forcing scenarios from CMIP5 (two RCP8.5 forcings, Representative Concentration Pathway) and CMIP6 (one SSP5-8.5 forcing, Shared Socioeconomic Pathway). Our simulations predict 5.2–8.7 mm of sea-level rise from Humboldt Glacier, significantly higher than a previous estimate (∼ 3.5 mm) and equivalent to a substantial fraction of the 40–140 mm predicted by ISMIP6 from the whole Greenland Ice Sheet. Our larger future sea-level rise prediction results from the transient calibration of our basal friction law to match the observed speedup, which requires a semi-plastic bed rheology. In many simulations, our model predicts the growth of a sizable ice shelf in the middle of the 21st century. Thus, atmospheric warming could lead to more retreat than predicted here if increased surface melt promotes hydrofracture of the ice shelf. Our data-constrained simulations of Humboldt Glacier underscore the sensitivity of model predictions of Greenland outlet glacier response to warming to choices of basal shear stress and iceberg calving parameterizations. Further, transient calibration of these parameterizations, which has not typically been performed, is necessary to reproduce observed behavior. Current estimates of future sea-level rise from the Greenland Ice Sheet could, therefore, contain significant biases.

54 ENVIRONMENTAL SCIENCES↗

Levelized Cost of Charging Electric Vehicles

This data set includes the levelized cost of charging (LCOC) and lifetime fuel cost savings (LFCS) values as reported in "Levelized Cost of Charging of Electric Vehicles in the United States." Values are reported at the state and national levels for battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). The data set also includes the four annual direct current fast charging (DCFC) station load profiles used to approximate the levelized cost of DCFC charging. Each profile provides 15-min resolved power requirements for one full year. Borlaug, B., Salisbury, S., Gerdes, M., and Muratori, M., Levelized Cost of Charging Electric Vehicles in the United States, Joule (2020), https://doi.org/10.1016/j.joule.2020.05.013.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Levelized Cost of Charging Electric Vehicles

This data set includes the levelized cost of charging (LCOC) and lifetime fuel cost savings (LFCS) values as reported in "Levelized Cost of Charging of Electric Vehicles in the United States." Values are reported at the state and national levels for battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). The data set also includes the four annual direct current fast charging (DCFC) station load profiles used to approximate the levelized cost of DCFC charging. Each profile provides 15-min resolved power requirements for one full year. Borlaug, B., Salisbury, S., Gerdes, M., and Muratori, M., Levelized Cost of Charging Electric Vehicles in the United States, Joule (2020), https://doi.org/10.1016/j.joule.2020.05.013.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performance CMOS voltage level-up shifter circuit topology using pre-drive pull-up transistors

In a first example a voltage level-shifting device includes a level-shifting stage circuit. The level-shifting stage circuit includes a first level-shifting inverter circuit to invert a buffered input signal to drive a first internal node, a second level-shifting inverter circuit to invert a buffered inverted input signal to drive a second internal node, a first pre-drive circuit that receives the buffered inverted input signal, and drives the second internal node based on the state of the buffered inverted input signal, and a second pre-drive circuit that receives the buffered input signal, and drives the first internal node based on the state of the buffered input signal.

Armstrong, Paul R.↗

High-Level Synthesis of Parallel Specifications Coupling Static and Dynamic Controllers

The increased need for efficient ways to implement domain-specific accelerators is driving design methodologies towards the use of abstractions higher than the Register Transfer Level (RTL). In this scenario, High Level Synthesis (HLS) plays a significant role by enabling the automatic generation of custom hardware accelerators starting from high level descriptions (e.g., C code). Conventional HLS tools exploit parallelism mostly at the Instruction Level (ILP). They statically schedule the input specifications, and build centralized Finite State Machine (FSM) controllers. However, aggressive exploitation of ILP in many applications has diminishing returns and, usually, centralized approaches do not efficiently exploit coarser parallelism because FSMs are inherently serial. In this paper we present a HLS framework able to synthesize applications that, beside ILP, also expose Task Level Parallelism (TLP). An application can expose TLP through annotations that identify the parallel functions (i.e., tasks). To generate accelerators that efficiently execute concur- rent tasks, we need to solve several issues: devise a mechanism to support concurrent execution flows, exploit memory parallelism, and manage synchronization. To support concurrent execution flows, we introduce a novel adaptive controller. The adaptive controller is composed of a set of interacting control elements that independently manage the execution of a single operation or function call. These control elements check dependencies and resource constraints at runtime, enabling as soon as possible execution. To support parallel access to shared memories and synchronization, we introduce a novel Hierarchical Memory Interface (HMI). With respect to previous solutions, the proposed interface supports multi-ported memories and atomic memory operations, which commonly occur in parallel programming. Our framework can generate the hardware implementation of C functions by employing two different approaches, depending on its characteristics. If a function exposes TLP, then the framework generates hardware implementations based on the adaptive controller. Otherwise, the framework implements the function by exploiting a more conventional FSM approach, which is optimized for ILP exploitation. We evaluate our framework on a set of parallel applications, and show substantial performance improvements (average speedup of 4.7) with limited area over- heads (average area increase of 5.48 times).

Castellana, Vito G.↗

High-Level Synthesis of Parallel Specifications Coupling Static and Dynamic Controllers

The increased need for efficient ways to implement domain-specific accelerators is driving design methodologies towards the use of abstractions higher than the Register Transfer Level (RTL). In this scenario, High Level Synthesis (HLS) plays a significant role by enabling the automatic generation of custom hardware accelerators starting from high level descriptions (e.g., C code). Conventional HLS tools exploit parallelism mostly at the Instruction Level (ILP). They statically schedule the input specifications, and build centralized Finite State Machine (FSM) controllers. However, aggressive exploitation of ILP in many applications has diminishing returns and, usually, centralized approaches do not efficiently exploit coarser parallelism because FSMs are inherently serial. In this paper we present a HLS framework able to synthesize applications that, beside ILP, also expose Task Level Parallelism (TLP). An application can expose TLP through annotations that identify the parallel functions (i.e., tasks). To generate accelerators that efficiently execute concur- rent tasks, we need to solve several issues: devise a mechanism to support concurrent execution flows, exploit memory parallelism, and manage synchronization. To support concurrent execution flows, we introduce a novel adaptive controller. The adaptive controller is composed of a set of interacting control elements that independently manage the execution of a single operation or function call. These control elements check dependencies and resource constraints at runtime, enabling as soon as possible execution. To support parallel access to shared memories and synchronization, we introduce a novel Hierarchical Memory Interface (HMI). With respect to previous solutions, the proposed interface supports multi-ported memories and atomic memory operations, which commonly occur in parallel programming. Our framework can generate the hardware implementation of C functions by employing two different approaches, depending on its characteristics. If a function exposes TLP, then the framework generates hardware implementations based on the adaptive controller. Otherwise, the framework implements the function by exploiting a more conventional FSM approach, which is optimized for ILP exploitation. We evaluate our framework on a set of parallel applications, and show substantial performance improvements (average speedup of 4.7) with limited area over- heads (average area increase of 5.48 times).

Castellana, Vito G.↗

Computational Fermi Level Engineering and Doping-Type Conversion of Ga2O3 Via Three-Step Processing

Ga2O3 is being actively explored for power electronics, deep-ultraviolet optoelectronics, and other applications due to its ultra-wide bandgap and low projected fabrication cost of large-size and high-quality crystals. N-type doping of Ga2O3 can be achieved and tuned, but p-type doping faces fundamental obstacles due to deep character of acceptor levels and polaron transport of resulting holes. However, successful engineering of Ga2O3 based devices requires critical control of doping density, Fermi level position, and free carrier concentration, providing opportunities for predictive process simulation. We use first-principles defect theory and defect equilibrium calculations to simulate a 3-step growth-annealing-quench protocol for hydrogen assisted Mg doping in Ga2O3, taking into account the hydrogen-oxygen-water gas phase equilibrium. We predict type conversion to a net p-type regime following O-rich annealing after growth under reducing conditions in the presence of H2. This process is similar to the Mg acceptor activation by H removal in GaN. We show that there is an optimal temperature that maximizes the net acceptor density during the equilibrium annealing step for a given Mg doping level. Quenching of non-equilibrium annealed samples then results in a Fermi level EF below mid-gap down to about EV +1.5 eV, creating a significant number of uncompensated neutral MgGa0 acceptors. The resulting free hole concentration in quenched samples is very low (109 – 1012 cm-3) due to deep energy level of these Mg acceptors, but this type converted Ga2O3 material can create a significant built-in field in a p-n junction with an adjoining n-type material. Additionally, the electron concentration is greatly suppressed in such acceptor-doped Ga2O3, which could enable the use as a current blocking layer to fabricate normally-off (enhancement-mode) vertical Ga2O3 based metal-oxide-semiconductor field effect transistors (MOSFETs), and as a guard ring for edge termination in MOSFETs and Schottky barrier diodes (SBDs) with increased breakdown voltage.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗

New transitions and levels for 163 Tb obtained from β-decay studies

Transitions in 163 Tb following β decay of 163 Gd were obtained as part of investigations of γ rays emitted following 163 Euβ decay to 163 Gd. In this work, detailed analysis of the low-energy structure of 163 Tb has been carried out with these data to expand previous β-decay studies and reactions studies of levels in 163 Tb. Data were collected at the LeRIBSS station of the Holifield Radioactive Ion Beam Facility at Oak Ridge National Laboratory with an array of four Clover HPGe detectors for γ rays and two plastic scintillators for β detection. The γ rays were identified as belonging to 163 Gd and 163 Tb via mass selection and γ-γ-β, γ-γ, or γ-x-ray coincidence. In total, 38 new γ-ray transitions were observed in 163 Tb from 15 newly identified levels and 12 previously identified levels. Potential energy surface calculations were performed which support a rigid prolate deformation. Previously identified unplaced transitions in 163 Tb have been placed within the level scheme of 163 Tb and additional states and transitions have been identified.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Wavelength- and irradiance-dependent changes in intracellular nitric oxide level

Photobiomodulation (PBM) refers to beneficial effects of low energy light absorption. Although there is a large and growing body of literature describing down-stream physiological benefits of PBM, there is limited understanding of the molecular mechanisms that initiate and mediate these effects at the level of photon absorption. At present, the leading hypothesis is that light absorption induces release of nitric oxide (NO) from the active site of cytochrome c oxidase (COX), allowing it to bind O 2 instead. This is believed to increase mitochondrial respiration, and result in greater overall health of the cell due to increased ATP production. Aim: Although NO itself is a powerful signaling molecule involved in a host of biological responses, less attention has been devoted to the mechanisms of NO release and subsequent effects on cell signaling. The purpose of this work is to investigate wavelength-specific effects on intracellular NO release in living cells. Approach: We have conducted in depth dosimetry analyses of NO production and function in an in vitro retinal model in response to low energy exposure to one or more wavelengths of laser light. Results: We found statistically significant wavelength-dependent elevations (10-30%) in intracellular NO levels following laser exposures at 447, 532, 635 or 808 nm. Sequential or simultaneous exposures to light at two different wavelengths enhanced the NO modulation up to 50% of unexposed controls. Additionally, the immediate increases in cellular NO levels were independent of the function of nitric oxide synthase, depended greatly on the substrate source of electrons entering the electron transport chain, and did not result in increased levels of cGMP. Conclusions: This study concludes the simple model of light-mediated release of NO from COX is unlikely to explain the wide variety of PBM effects reported in the literature. Our multi-wavelength method provides a novel tool for studying immediate and early mechanisms of PBM, as well as exploring intracellular NO signaling networks.

59 BASIC BIOLOGICAL SCIENCES↗

A Level Set Model for Structured Mesh Representation of Fibrous Preforms used in Composites Manufacturing

Here, a model for implicit representation of fibrous and woven preforms used for composites manufacturing is described. The method is based on a level set function defined on a structured mesh to implicitly capture the complex fiber and weave geometries. Since most software packages used to model woven preforms are based on unstructured mesh, a numerical model for transforming a discretized surface to a structured mesh representation and vice-a-versa is presented. Specific emphasis is on scalable computation of a level set function for large and complex 3D woven structures from a triangulated surface of the smallest unit (yarn). The model is applied to capture a periodic 3D layered 5-harness satin (5HS) weave geometry on a structured mesh. Geometric transformations needed to efficiently compute the level set function for the 3D structure on a high resolution mesh are described. Effects of mesh resolution on the geometric features such as number of resolved fibers, effective fiber size, and the surface area to volume ratio of the iso-surface are analyzed. Using the distance property of the level set function, an approach to evaluate the structure function resulting from transient evolving topology representing densification due to matrix phase depositions is also presented. The approach captures transition of the geometric characteristic from fiber governed at early stages of densification to yarn governed at the terminal stage.

36 MATERIALS SCIENCE↗

Continuum-Level Modeling of Li-Ion Battery SEI by Upscaling Atomistically Informed Reaction Mechanisms

Understanding and controlling solid-electrolyte interphase (SEI) formation to stabilize cell performance is a significant challenge for next-generation Li-ion battery technologies. In recent years, computational modeling has become an essential tool in providing fundamental insights into SEI properties and dynamics. However, neither atomistic nor continuum-level approaches alone can capture the complexities of SEI chemistry across all relevant length and time scales. In this work, a continuum-level model is developed that is informed by reaction mechanisms obtained from first-principle calculations. The atomistically informed continuum-level model is used to understand electrolyte degradation, including the decomposition of ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). The model presented here is the most chemically complex continuum-level SEI model in the literature to date. The SEI model is calibrated against experimental irreversible leakage currents and shows qualitative agreement with expected SEI growth trends. The model framework is expected to accelerate fundamental understanding of SEI formation, facilitate mechanism development feedback, and dynamically interact with experimental insights.

continuum-level model↗

Impact of representative ground motion level on seismic PSA with the boundary between overestimation and underestimation

One commonly used approach in seismic probabilistic safety assessment (PSA) is the discrete method. This method follows the standard PSA framework and can be applied to various models, such as multi-unit models, while reducing computational costs using standard software. However, due to the inability to subdivide intervals infinitely, the discrete method approximates with a finite number of subintervals. In practice, different numbers of subintervals are applied, and the representative ground motion level is selected based on expert judgment. When employing a smaller number of subintervals, it is important to take caution to prevent underestimation. This study analyzes the impact of the representative ground motion level on seismic risk. It confirms that underestimation can occur with a small number of subintervals depending on the representative ground motion level. This study also proposes a method for determining the boundary of underestimation and overestimation. The method is demonstrated through examples, providing a mathematical foundation for selecting appropriate representative ground motion levels. By avoiding underestimation, this research helps prevent the oversight of significant risk contributors and enhances the understanding of seismic risk.

99 - GENERAL AND MISCELLANEOUS↗

A phenology- and trend-based approach for accurate mapping of sea-level driven coastal forest retreat

The rapid replacement of upland forest by encroaching marshland is a striking manifestation of global sea-level rise (SLR). Timely and high-resolution information on the location and extent of transition forest (the ecotone between upland forest and marsh where tree mortality due to seawater intrusion begins) is fundamental to understanding the processes and patterns of SLR-driven landscape reorganization. Despite its significance, accurate characterization of salt-impacted transition forest remains challenging due to the complexity of coastal environments, scarcity of ground-truth data, and the lack of effective mapping algorithms. Here we use the full archive of Landsat images between 1984 and 2021 to investigate the spectral, temporal, and phenological characteristics of transition forest, and develop a robust framework for monitoring coastal vegetation shifts in the mid-Atlantic U.S., a global SLR hotspot. Here, we found that transition forest exhibits strong negative NDVI trends and a deviation of land surface phenology from marsh and upland forest that distinguishes itself from surrounding vegetation. By integrating temporal trends and land surface phenology, our results demonstrate superior discrimination between marsh and coastal forests to existing map products (e.g. NOAA Coastal Change Analysis Program, National Land Cover Database) that allows a reliable identification of the coastal treeline. We applied the approach to map regional land cover in 1985, 2000 and 2020 (overall classification accuracy >92%) and found that the area of coastal forest decreased by 22.0% from 1985 to 2020, the majority of which transitioned to marshland (92.3%, 5.3 × 10 3 ha). Based upon fine-scale patterns of coastal transgression, we created a practical workflow for spatially explicit quantification of forest retreat rates. Concurrent with rising sea level, coastal forests migrated upslope from 0.63 (± 0.27) m above sea level in 1985 to 0.78 (± 0.32) m above sea level in 2020, and horizontal forest retreat rates accelerated from 3.1 (range of 0–36) m yr -1 during 1985–2000 to 4.7 (0–55) m yr -1 during 2001–2020. As SLR continues to accelerate, our study may serve as a scalable solution for consistent tracking of coastal landscape evolution that is urgently needed for sustainable forest and wetland management.

54 ENVIRONMENTAL SCIENCES↗

Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability

Estimating street-level air temperature is a challenging task due to the highly heterogeneous urban surfaces, canyon-like street morphology, and the diverse physical processes in the built environment. Though pioneering studies have embarked on investigations via data-driven approaches, many questions remain to be answered. Here, in this study, we leveraged an innovative framework and redefined the street-level temperature estimation problem using Graph Neural Networks (GNN) with spatial embedding techniques. The results showed that GNN models are more capable and consistent of estimating street-level temperature among tested locations, benefiting from its unique strength in handling extensive data over unstructured graph topology. In addition, we conducted in-depth analysis of feature importance to enhance the model interpretability. Among the urban features analyzed in this study, the time-variant canopy density and meter-level land use data emerge as crucial factors. Our findings highlight GNN 's high potential in capturing the complex dynamics between urban elements and their impacts on microclimate, thus offering valuable insights for comprehensive urban data collection and urban climate modeling in general. Collectively, this study also contributes to urban planning and policy by providing avenues to enhance city resilience against climate change, thereby advancing the agenda for environmental stewardship and urban sustainability.

54 ENVIRONMENTAL SCIENCES↗

Rates of Sea‐Level Rise Are Highly Sensitive to Ice Viscosity Parameters in Model Benchmarks

Glacier flow plays a major role in current and future rates of globally averaged sea-level rise. The viscosity of glacial ice, controlling the rate of flow, decreases as stress increases and is highly sensitive to the value of the stress exponent, $n$, in the constitutive equation for viscous flow. Glaciologists and climate modelers almost exclusively assume $n=3$ when modeling ice flow and projecting sea-level rise through forward modeling. However, recent work suggests that $n\approx 4$ better fits observations, prompting the question: How sensitive are projections of sea-level rise to the value of $n$? We use an established community ice flow model and standard benchmark experiments designed as an idealized representation of Pine Island Glacier, West Antarctica. While initializing an $n=3$ model to match observations of an $n=4$ ice sheet is possible, we find that incorrectly assuming $n=3$ when in fact $n=4$ dramatically underestimates rates of sea-level rise. The scale of this error grows nonlinearly with the magnitude of the climate forcing, acting to increase projection uncertainties. Additionally, we find that models often account for this stress-dependent rheology mismatch during model initialization in a way that masks this rheological effect in the short term while leaving model outputs vulnerable to larger biases in longer-term projections. Initializations to observations of Pine Island Glacier display similar rheology-mismatch fingerprints to our idealized example.

climate sensitivity↗

Role of deep levels and barrier height lowering in current-flow mechanism in 150 μ m thick epitaxial n-type 4H–SiC Schottky barrier radiation detectors

Schottky barrier detectors (SBDs) require larger surface areas than conventional electronics to increase the detection efficiency although such SBDs manifest large diode ideality factors due to inhomogeneous areal distribution of surface barrier height (SBH). Inhomogeneous SBH distributions lead to various current flow mechanisms in SBDs, which need to be identified to optimize detector performance. In this Letter, we identify the current flow mechanism in large area Schottky barrier diodes for radiation detection fabricated on 150 μm thick n-4H–SiC epitaxial layers. The analysis of temperature-dependent forward current–voltage (I–V–T) characteristics of SBDs revealed two linear regions in current–voltage curves up to 450 K, one corresponding to the current flow through a low barrier patch, while the other corresponds to that of average barrier distribution. Applying a SBH distribution model to the reverse I–V–T characteristics, an activation energy of 0.76 eV for the current flow over the Schottky barrier was calculated. Additionally, the activation energy did not directly correspond to any of the defect levels observed from the deep level transient spectroscopy (DLTS). Above 450 K, a Schottky type barrier lowering suggested a current flow through a low barrier patch of ≈ 0.8 eV. The absence of any SBH lowering below 450 K indicated that the current corresponded to a neutrally charged trap level at ≈ 0.6 eV below the conduction band edge, which was consistent with DLTS measurements revealing the presence of an electron trap level Z1/2 at 0.59 eV below the conduction band edge.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗