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At least 1,567 records · Page 87

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DOE OSTI2018

Development of Novel Biodegradable Enrofloxacin–Silica Composite for In Vitro Drug Release Kinetic Studies

A sustained drug delivery system is developed by using nonionic polymer to formulate drug release rate from silica capsules. To serve this purpose, silica capsules filled with poly(ethylene glycol) (PEG) were incorporated with a veterinary antibiotic drug enrofloxacin (ENF); as a model hydrophobic drug by using a general and facile sol–gel route. The physicochemical properties of the prepared drug-loaded composites were investigated by scanning electron microscope (SEM), nitrogen adsorption, Fourier transform infrared spectroscopy and thermal analysis (TGA). The impact of the media’s ionic strength on the drug release was evaluated over a range of 0–0.4 M to simulate the gastrointestinal feed in two physiological pH conditions. Sodium chloride was applied for ionic concentration adjustment due to its ability to salt out polymers in the midrange of the lyotropic series. Simultaneously, the drug release kinetics was evaluated by fitting experimental data to common empirical (zero-order, first order and Higuchi) and semi-empirical (Ritger–Peppas and Sahlin–Peppas) models. The drug release kinetics from capsules revealed a non-Fickian diffusion and pure relaxation-controlled release. Of these models, Sahlin–Peppas equation best fit the release data of ENF. To determine the best model, non-linear regressions were carried out.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Advanced Processing of Functional Magnetic Materials

Functional materials, specifically those which respond to external stimuli such as magnetic and electrical field, are increasingly important for many green energy technologies. Functional magnetic materials are increasingly been investigated from basic and applied sciences perspectives. Probably, the best-known of these are permanent magnets, they are used to supply a magnetic field and are widely applied in motors, generators, data storage, sensors, and actuators. Other examples of functional materials include soft magnets, magnetocalorics, and thermoelectrics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. Here, the deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Time-resolved momentum imaging of UV photodynamics in structural isomers of iodopropane probed by site-selective XUV ionization

The photodynamics of 1- and 2-iodopropane (1 and 2-IP) were studied in a time-resolved scheme incorporating ultraviolet (UV) excitation and extreme ultraviolet (XUV) probing, which initiates photoionization selectively from the I 4d core orbital. UV absorption in the A-band of both isomers leads to prompt C–I bond fission, with significant disposal of internal energy into the propyl radical product. Site-selective ionization enables a range of charge transfer (CT) processes between the nascent highly charged iodine ions and neutral propyl radicals, dependent on the interfragment distance at the instant of ionization. Subtle differences in the dynamics of these CT processes between the two isomers are observed. In 1-IP, the kinetic energies of iodine ions produced by UV photodissociation and subsequent XUV multiple ionization increased notably over the first few hundred femtoseconds, which could be understood in terms of differing gradients along the photodissociation coordinates of the neutral and polycationic states involved in the pump and probe steps, respectively. Led by a recent report of HI elimination in UV photoexcited 2-IP [Todt et al., Phys. Chem. Chem. Phys., 22(46), 27338 (2020)], we also model the most likely signatures of this process in the present experiment, and can identify signal in the 2-IP data (that is absent or significantly weaker in the data from the unbranched 1-IP isomer) that is consistent with such a process occurring on ultrafast timescales.

Allum, Felix [Deutsches Elektronen-Synchrotron (DE↗

DOE OSTI2024

Identifying Sample Provenance From SEM/EDS Automated Particle Analysis via Few-Shot Learning Coupled With Similarity Graph Clustering

Automated particle analysis (APA) provides a vast amount of compositional data via energy-dispersive X-ray spectroscopy along with size and shape data via scanning electron microscopy for individual particles in a sample. In many instances, APA data are leveraged to support identification of the source of a sample based on the detection of particles of a specific composition. Often, the particles that provide context make up a minuscule portion of the sample. Additionally, the interpretation of complex samples can be difficult due to the diversity of compositions both in the mixture and within a particle. In this work, we demonstrate a method to compute and cluster similarity graphs that describe inter-particle relationships within a sample using a multi-modal few-shot learning neural network. Here, as a proof-of-concept, we show that samples known to have been exposed to gunshot residue can be distinguished from samples occasionally mistaken for gunshot residue. Our workflow builds upon standard APA techniques and data processing methods to unveil additional information in a readily interpretable and quantitatively comparable format.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Precautions of Using Three-Electrode Configuration to Measure Electrode Overpotential in Solid Oxide Electrochemical Cells: Insights from Finite Element Modeling

Accurate determination of electrode overpotentials is essential to assess the performance of the electrode and understand the rate-limiting steps involved. Three-electrode configuration with the use of a reference electrode at a fixed potential is a standard way to measure overpotential of a specific electrode in liquid electrochemical systems. However, application of such three-electrode configuration to solid electrochemical cells for overpotential determination is not straightforward and requires extra caution. Here we report a theoretical Finite Element Analysis on the geometrical requirements for which the reference electrode can be applied to anode- or electrolyte-supported solid oxide button cells. The modeling results suggest that the symmetry of the working and counter electrodes is the key factor determining if a reference electrode is suitable to use. For anode-supported fuel cells with asymmetrical working and counter electrodes, reference electrode cannot be used under all circumstances. To use reference electrode for overpotential measurements, electrolyte-supported cells with symmetrical semicircular-shaped electrodes are preferred. A data processing procedure has also been presented to obtain the electrode overpotential from the measured potential using the three-electrode scheme in solid oxide electrochemical cells.

25 ENERGY STORAGE↗

DOE OSTI2026

Data for Yield from Iowa’s first commercial miscanthus fields: implications of spatial variability for productivity and sustainability beyond research plots

This dataset contains biomass yield measurements and associated vegetation index data collected from commercial Miscanthus × giganteus fields in eastern Iowa during the 2022–2023 growing seasons. The data support the analyses presented in the article: “Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots.” We collected 105 ground-truth biomass samples from four mature commercial fields (>4 years old) covering 92.81 ha. Samples were taken from 3 m² quadrats that were hand-harvested in alignment with commercial harvest timing. Stem biomass (excluding leaves) was weighed, moisture-corrected, and converted to dry-matter yield expressed in Mg DM ha⁻¹. Sampling locations were selected to capture spatial variability visible in aerial imagery and were recorded using RTK GPS. Each biomass observation was paired with vegetation indices derived from high-resolution PlanetScope satellite imagery (3 m resolution). Images were acquired throughout the growing season, and indices were calculated to evaluate their ability to predict end-of-season biomass yield. Statistical and machine learning approaches were used to identify key predictors, and a linear regression model based on end-of-July Green Normalized Difference Vegetation Index (GNDVI) was developed and evaluated. This repository includes the data used in that modeling workflow. Management practices, economic data, full imagery time series, and additional methodological details are described in the associated publication and are not included here. The dataset consists of three comma-separated value (CSV) files: 1. Combine_Groundtruth_Yield_VI_22_23.csv This file contains ground-truth biomass yield measurements and associated key vegetation index values collected during the 2022 and 2023 growing seasons. Rows: 105 observations Columns: Year — Year of observation (2022 or 2023) Field — Field location identifier Sample_number — Unique sample identifier GNDVI_End_Jul — Green Normalized Difference Vegetation Index calculated at end of July GNDVI_End_Aug — Green Normalized Difference Vegetation Index calculated at end of August NDRE_End_Aug — Normalized Difference Red Edge index calculated at end of August Biomass_Stem_Yield_MgDM/ha — Measured stem biomass yield (megagrams dry matter per hectare) 2. trainData_GNDVI.csv This file contains the subset of observations used to train the predictive relationship between July GNDVI and biomass yield. Rows: 76 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Stem_Yield_MgDM/ha — Observed stem biomass yield (Mg DM ha⁻¹) 3. testData_GNDVI.csv This file contains the test dataset used to evaluate model performance. Rows: 29 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Predicted_Yield_MgDM/ha — Model-predicted stem biomass yield (Mg DM ha⁻¹) Observed_Yield_MgDM/ha — Measured stem biomass yield (Mg DM ha⁻¹)

Potential yield, yield gap, in-field management, y↗

DOE OSTI2025

Processed Soil Respiration at the TRACE experimental Warming project, Aug 2015 - Sep 2017, Sabana, Luquillo, Puerto Rico

This data package contains processed measurements of soil carbon dioxide (CO₂) efflux collected using LI-COR LI-8100 soil respiration chambers at the Tropical Responses to Altered Climate Experiment (TRACE) located at the Sabana Field Research Station near Luquillo, Puerto Rico. The TRACE site is a mature, closed-canopy tropical wet forest within the Luquillo Experimental Forest. These data quantify soil surface CO₂ fluxes from both ambient (control) and experimentally warmed plots to evaluate how long-term soil warming affects belowground carbon cycling in tropical ecosystems. The data files include time-series tables of CO₂ flux (µmol CO₂ m⁻² s⁻¹), soil temperature (°C), and ancillary environmental variables, stored in comma-separated values (CSV) format and viewable with any text editor, spreadsheet, or statistical software (e.g., R, Python, Excel). Associated metadata describe plot identifiers, measurement intervals, and processing steps. These data were generated to address the research question: How does sustained soil warming influence soil respiration and carbon flux dynamics in tropical wet forests?

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Thick Concrete Specimen Construction, Testing, and Preliminary Analysis

The purpose of the U.S. Department of Energy Office of Nuclear Energy’s Light Water Reactor Sustainability (LWRS) Program is to develop technologies and other solutions that can improve the reliability, sustain the safety, and extend the operating lifetimes of nuclear power plants (NPPs) beyond 60 years. Since many important safety structures in an NPP are constructed of concrete, inspection techniques must be developed and tested to evaluate the internal condition. In-service containment structures generally do not allow for the destructive measures necessary to validate the accuracy of these inspection techniques. This creates a need for comparative testing of the various nondestructive evaluation (NDE) measurement techniques on concrete specimens with known material properties, voids, internal microstructure flaws, and reinforcement locations. A preliminary report detailed some of the challenges associated with thick reinforced concrete sections and prioritized conceptual designs of specimens that could be fabricated to represent NPP concrete structures for using in NDE evaluation comparisons. This led to the construction of the concrete specimen presented in this report, which has sufficient reinforcement density and cross-sectional size to represent an NPP containment wall. Details on how a suitably thick concrete specimen was constructed are presented, including the construction materials, final nominal design schematic, as well as formwork and rigging required to safely meet the desired dimensions of the concrete structure. The report also details the type and methods of forming the concrete specimen as well as information on how the rebar and simulated defects were embedded. Details on how the resulting specimen was transported, safely anchored, and marked to allow access for systematic comparative NDE testing of defects in a representative NPP containment wall concrete specimen are also given. Data collection using the MIRA Ultrasonic NDE equipment and initial results are also presented along with a discussion of the preliminary findings. Comparative NDE of various defects in reinforced concrete specimens is a key component in identifying the most promising techniques and directing the research and development efforts needed to characterize concrete degradation in commercial NPPs. This requires access to the specimens for data collection using state-of-the-art technology. The construction of the specimen detailed in this report allows for an evaluation of how different NDE techniques may interact with the size and complexities of NPP concrete structures. These factors were taken into account when determining specimen size and features to ensure a realistic design. The lateral dimensions of the specimen were also chosen to mitigate unrealistic boundary effects that would not affect the results of field NPP concrete testing. Preliminary results show that, while the current methods are able to identify some of the deeper defects, improvements in data processing or hardware are necessary to be able to achieve the precision and reliability achieved in evaluating thinner and less heavily reinforced concrete structures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

First-principles Studies of Tritium Reactivity and Diffusivity on Defective and Carbon Doped Surfaces of $\gamma$-LiAlO 2 Pellets (Tritium Science Program Report FY 2019 )

In tritium-producing burnable absorber rods (TPBARs), tritium ($^{3}_{1}$H,T) is produced in 6 Li isotope enriched γ-LiAlO 2 ceramic pellet. However, a better understanding of $^{3}_{1}$H transport through the pellets, getters and the barrier/cladding system is hampered by a lack of fundamental data about the $^{3}_{1}$H solubility and diffusivity. In the process of $^{3}_{1}$H diffusion from bulk γ-LiAlO 2 to its surface, it is possible that $^{3}_{1}$H atoms bind with surface atoms or become trapped at vacancies sites. By increasing the number of $^{3}_{1}$H diffused from bulk to surface, upon recombination and desorption from surface sites, they will escape from the γ-LiAlO 2 surface to form different $^{3}_{1}$H species (possibly being as T, T 2 , T 2 O, OT, or CT x (x=1-4, with C impurity present at a 100-600 ppm level in pellets) that need to be identified and can become captured by the getter. Therefore, exploring the $^{3}_{1}$H diffusion from bulk to surface, corroborated with surface adsorption, diffusion and recombination and followed by desorption from surface as various types of $^{3}_{1}$H species becomes a very important task as an integral part of the study of $^{3}_{1}$H solubility and diffusivity in the pellets.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Electric Power Research Institute (EPRI) [Abstract]

Carbon dioxide (CO 2 ) capture from flue gas generated by fossil fuel-fired power plants has been proposed as an efficient approach to limit CO 2 emissions to the atmosphere. Due to the high cyclic CO 2 sorption capacity, well-tuned adsorption chemistry and non-volatility, solid sorbents are widely studied for CO 2 capture processes such as pressure swing adsorption (PSA) and temperature swing adsorption (TSA). Realistic applications of traditional solid sorbent systems face many challenges since moisture and heat management are problematic and solid-solid heat exchange is inefficient. Recently, a novel solid sorbent system, the sorbent polymer composite (SPC), has been developed to overcome those challenges in an energy-saving CO 2 capture process using TSA membrane contactors. A SPC material is comprised of a powdered solid sorbent embedded into a hydrophobic and porous polymer matrix. It allows gases to permeate through and achieve full contact with the sorbents while rejecting water moisture in the CO 2 capture process. In this collaborative research, NETL will conduct performance testing of a novel SPC material and EPRI will conduct a cost analysis based on that performance data.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

A double peak in the seasonality of California's photosynthesis as observed from space

Solar-induced chlorophyll fluorescence (SIF) has been shown to be a powerful proxy for photosynthesis and gross primary productivity (GPP). The recently launched TROPOspheric Monitoring Instrument (TROPOMI) features the required spectral resolution and signal-to-noise ratio to retrieve SIF from space. Here, we present a downscaling method to obtain 500 m spatial resolution SIF over California. We report daily values based on a 14 d window. TROPOMI SIF data show a strong correspondence with daily GPP estimates at AmeriFlux sites across multiple ecosystems in California. We find a linear relationship between SIF and GPP that is largely invariant across ecosystems with an intercept that is not significantly different from zero. Measurements of SIF from TROPOMI agree with MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation indices – the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near-infrared reflectance of vegetation index (NIR$_v$) – at annual timescales but indicate different temporal dynamics at monthly and daily timescales. TROPOMI SIF data show a double peak in the seasonality of photosynthesis, a feature that is not present in the MODIS vegetation indices. The different seasonality in the vegetation indices may be due to a clear-sky bias in the vegetation indices, whereas previous work has shown SIF to have a low sensitivity to clouds and to detect the downregulation of photosynthesis even when plants appear green. We further decompose the spatiotemporal patterns in the SIF data based on land cover. The double peak in the seasonality of California's photosynthesis is due to two processes that are out of phase: grasses, chaparral, and oak savanna ecosystems show an April maximum, while evergreen forests peak in June. An empirical orthogonal function (EOF) analysis corroborates the phase offset and spatial patterns driving the double peak. The EOF analysis further indicates that two spatiotemporal patterns explain 84 % of the variability in the SIF data. Results shown here are promising for obtaining global GPP at sub-kilometer spatial scales and identifying the processes driving carbon uptake.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The contributions of microclimatic information in advancing ecosystem science

Drawing upon over 100 years of scholarly work on microclimate, we first present an overview of the history, key references, and critical issues surrounding the collection and utilization of microclimate records in ecosystem studies. We place particular emphasis on addressing specific and pressing issues related to the applications of microclimate at the community-ecosystem-landscape level, excluding those of controlled experiment such as growth chambers and greenhouses. Specifically, we: (1) highlight some key issues concerning the collection, quality assurance/quality control (QA/QC), and utilization of microclimatic data in ecosystem studies; (2) revisit microclimatic responses to the structural changes of ecosystems and landscapes; and (3) emphasize the significance of microclimate in understanding major ecosystem/landscape processes and functions. Vapor pressure deficit (VPD) is particularly emphasized for its calculation and use because of its burgeoning applications in the literature. Case studies for each of the three thematic topics are provided with selected references to demonstrate challenges and solutions. As the scientific community gears up to enhance microclimatic stations, we envision significant increases in the use of smart sensors, wireless access, networking, open databases, and computational capabilities. Understanding and addressing some of the issues raised in this synthesis paper may help advance microclimate research and foster collaboration with other relevant disciplines, such as ecosystem science.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

Report on the ASCR Workshop on Modeling and Simulation of Exascale Systems and Applications

In the last few years, numerous studies commissioned by the Department of Energy (DOE), the Defense Advanced Research Projects Agency (DARPA), and others have examined the challenges that will have to be overcome for computational science to achieve exascale, a two order-of-magnitude increase in capability beyond what is possible today. Exponential growth in the number of devices (Moore’s Law) is expected to continue unabated, but the end of Dennard scaling, and hence the growth in performance of individual processors, has led to exponential growth in concurrency. Power consumption has also grown to the point where the cost of the electrical power for systems threatens to exceed the cost of acquiring them. Ever-shrinking devices, and the growth in their number, are expected to increase the rate of soft, or transient, errors such that applications will no longer be able to assume correct behavior of the underlying machine. Adapting to such systems will require new mathematical algorithms that minimize synchronization and data movement, and a new generation of scientific software. Rather than addressing these issues in isolation, a new process of “Co-Design” is being pursued in which application and computer scientists work toward the common goal of an exascale ecosystem of systems and applications. Modeling and simulation (ModSim) is a critical part of this process. It enables scientists and engineers to analyze future algorithms, applications, and computing systems, long before they are realized, and make the necessary design decisions such that exascale science is broadly achieved. Later, when exascale applications and systems are realized, ModSim technology will enable us to understand their behavior, debugging and optimizing them. Given the increasing importance of modeling and simulation, a workshop was organized by DOE/ASCR to assess the current state of the art and to identify research challenges that must be overcome in this field. Fifty experts, representing academia, industry, and government, participated in the workshop, and others contributed both beforehand and afterwards. This report summarizes their findings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Report on the ASCR Workshop on Modeling and Simulation of Exascale Systems and Applications

In the last few years, numerous studies commissioned by the Department of Energy (DOE), the Defense Advanced Research Projects Agency (DARPA), and others have examined the challenges that will have to be overcome for computational science to achieve exascale, a two order-of-magnitude increase in capability beyond what is possible today. Exponential growth in the number of devices (Moore's Law) is expected to continue unabated, but the end of Dennard scaling, and hence the growth in performance of individual processors, has led to exponential growth in concurrency. Power consumption has also grown to the point where the cost of the electrical power for systems threatens to exceed the cost of acquiring them. Ever-shrinking devices, and the growth in their number, are expected to increase the rate of soft, or transient, errors such that applications will no longer be able to assume correct behavior of the underlying machine. Adapting to such systems will require new mathematical algorithms that minimize synchronization and data movement, and a new generation of scientific software. Rather than addressing these issues in isolation, a new process of "Co-Design" is being pursued in which application and computer scientists work toward the common goal of an exascale ecosystem of systems and applications. Modeling and simulation (ModSim) is a critical part of this process. It enables scientists and engineers to analyze future algorithms, applications, and computing systems, long before they are realized, and make the necessary design decisions such that exascale science is broadly achieved. Later, when exascale applications and systems are realized, ModSim technology will enable us to understand their behavior, debugging and optimizing them. Given the increasing importance of modeling and simulation, a workshop was organized by DOE/ASCR to assess the current state of the art and to identify research challenges that must be overcome in this field. Fifty experts, representing academia, industry, and government, participated in the workshop, and others contributed both beforehand and afterwards. This report summarizes their findings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Fission gas bubble identification using MATLAB's image processing toolbox

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.

36 MATERIALS SCIENCE↗

DOE OSTI2012

'Abnormal' angle response curves of TW/Rs for near zero tilt and high tilt channeling implants

Angle control has been widely accepted as the key requirement for ion implantation in semiconductor device processing. From an ion implanter point of view, the incident ion direction should be measured and corrected by suitable techniques, such as XP-VPS for the VIISta implanter platform, to ensure precision ion placement in device structures. So called V-curves have been adopted to generate the wafer-based calibration using channeling effects as the Si lattice steer ions into a channeling direction. Thermal Wave (TW) or sheet resistance (Rs) can be used to determine the minimum of the angle response curve. Normally it is expected that the TW and Rs have their respective minima at identical angles. However, the TW and Rs response to the angle variations does depend on factors such as implant species, dose, and wafer temperature. Implant damage accumulation effects have to be considered for data interpretation especially for some 'abnormal' V-curve data. In this paper we will discuss some observed 'abnormal' angle responses, such as a) TW/Rs reverse trend for Arsenic beam, 2) 'W' shape of Rs Boron, and 3) apparent TW/Rs minimum difference for high tilt characterization, along with experimental data and TCAD simulations.

36 MATERIALS SCIENCE↗

DOE OSTI2015

High performance techniques for micro channel plate computations in photo multipliers

Monte Carlo - MC methods, requiring heavy computations of large data volume, can be used to predict the amplitude distribution and variance of outputted electron charge in Micro Channel Plates - MCPs, which are fed with primary emitted electrons in their inputs. The concept of parallel and serial combination of separate stages of such stochastic processes, which can be applied in MCP systems and simulated using MC computations, has recently proposed and shown interesting theorems and results. Separating the electron multiplication procedures, occurring in the channels of MCP systems, into sub-procedures, which are similar in nature and occur either in parallel or in consecutive manners, is equivalent to splitting the relevant stochastic system calculations into smaller ones, which can be performed concurrently and/or sequentially. In this way, calculations similar in nature, can be executed only once, thus, eliminating a great percentage of heavy computations. However, when designing and implementing the calculation inferences of the derived theorems using High Performance Computation - HPC techniques, the overall computation cost can further and significantly be reduced. In this paper, the hardware mappings of the relevant theorem inferences onto parallel computing architectures, resulting in circuits of computing blocks for calculation purposes of MCP system stochastic processes, are investigated. Each of the designed and implemented computing circuits corresponds to a theorem inference or to a combination of inferences. The parallelism of the proposed circuits consists of both the concurrent functioning of all the system blocks and of the simultaneous operation of each block, which is processing pieces of data, for many parts of the whole circuit in which it belongs. All the circuits are designed and tested using Altera Quartus II environment and can be implemented as chips, which can be incorporated in computing devices to assist Monte Carlo computations for the estimation of different MCP electron multiplication system performances.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗