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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-D-BRC-05: Effects of Motion and Variable RBE in a Lung Patient Treated with Passively Scattered Protons

Purpose: To evaluate effects of motion and variable relative biological effectiveness (RBE) in a lung cancer patient treated with passively scattered proton therapy using dose volume histograms associated with patient dose computed using three different methods. Methods: A proton treatment plan of a lung cancer patient optimized using clinical treatment planning system (TPS) was used to construct a detailed Monte Carlo (MC) model of the beam delivery system and the patient specific aperture and compensator. A phase space file containing all particles transported through the beam line was collected at the distal surface of the range compensator and subsequently transported through two different patient models. The first model was based on the average CT used by the TPS and the second model included all 10 phases of the corresponding 4DCT. The physical dose and proton linear energy transfer (LET) were computed in each voxel of two models and used to compute constant and variable RBE MC dose on average CT and 4D CT. The MC computed doses were compared to the TPS dose using dose volume histograms for relevant structures. Results: The results show significant differences in doses to the target and critical structures suggesting the need for more accurate proton dose computation methods. In particular, the 4D dose shows reduced coverage of the target and higher dose to the spinal cord, while variable RBE dose shows higher lung dose. Conclusion: The methodology developed in this pilot study is currently used for the analysis of a cohort of ∼90 lung patients from a clinical trial comparing proton and photon therapy for lung cancer. The results from this study will help us in determining the clinical significance of more accurate dose computation models in proton therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-207B-04: Morphological Features of MRI as a Correlate of Capsular Contracture in Breast Cancer Patients with Implant-Based Reconstructions

Purpose: Capsular contracture (CC) is a serious complication in patients receiving implant-based reconstruction for breast cancer. The goal of this study was to identify image-based correlates of CC using MRI imaging in breast cancer patients who received both MRI and clinical evaluation following reconstructive surgery. Methods: We analyzed a retrospective dataset of 50 patients who had both a diagnostic MR and a plastic surgeon’s evaluations of CC score (Baker’s score) within a six month period following mastectomy and reconstructive surgery. T2w sagittal MRIs (TR/TE = 3500/102 ms, slice thickness = 4 mm) were used for morphological shape features (roundness, eccentricity, solidity, extent and ratio-length) and histogram features (median, skewness and kurtosis) of the implant and the pectoralis muscle overlying the implant. Implant and pectoralis muscles were segmented in 3D using Computation Environment for Radiological Research (CERR) and shape and histogram features were calculated as a function of Baker’s score. Results: Shape features such as roundness and eccentricity were statistically significant in differentiating grade 1 and grade 2 (p = 0.009; p = 0.06) as well as grade 1 and grade 3 CC (p = 0.001; p = 0.006). Solidity and extent were statistically significant in differentiating grade 1 and grade 3 CC (p = 0.04; p = 0.04). Ratio-length was statistically significant in differentiating all grades of CC except grade 2 and grade 3 that showed borderline significance (p = 0.06). The muscle thickness, median intensity and kurtosis were significant in differentiating between grade 1 and grade 3 (p = 0.02), grade 1 and grade 2 (p = 0.03) and grade 1 and grade 3 (p = 0.01) respectively. Conclusion: Morphological shape features described on MR images were associated with the severity of CC. MRI may be important in objectively evaluating outcomes in breast cancer patients who undergo implant reconstruction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-31: Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease

Purpose: Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (radiation pneumonitis and radiation fibrosis). For these features to be clinically useful, they need to be relatively invariant (robust) to tumor size and not correlated with normal lung volume. Methods: The free-breathing CTs of 14 lung SBRT patients were studied. Different sizes of GTVs were simulated with spheres placed at the upper lobe and lower lobe respectively in the normal lung (contralateral to tumor). 27 texture features (9 from intensity histogram, 8 from grey-level co-occurrence matrix [GLCM] and 10 from grey-level run-length matrix [GLRM]) were extracted from [normal lung-GTV]. To measure the variability of a feature F, the relative difference D=|Fref -Fsim|/Fref*100% was calculated, where Fref was for the entire normal lung and Fsim was for [normal lung-GTV]. A feature was considered as robust if the largest non-outlier (Q3+1.5*IQR) D was less than 5%, and considered as not correlated with normal lung volume when their Pearson correlation was lower than 0.50. Results: Only 11 features were robust. All first-order intensity-histogram features (mean, max, etc.) were robust, while most higher-order features (skewness, kurtosis, etc.) were unrobust. Only two of the GLCM and four of the GLRM features were robust. Larger GTV resulted greater feature variation, this was particularly true for unrobust features. All robust features were not correlated with normal lung volume while three unrobust features showed high correlation. Excessive variations were observed in two low grey-level run features and were later identified to be from one patient with local lung diseases (atelectasis) in the normal lung. There was no dependence on GTV location. Conclusion: We identified 11 robust normal lung CT texture features that can be further examined for the prediction of radiation-induced lung disease. Interestingly, low grey-level run features identified normal lung diseases. This work was supported in part by the National Cancer Institute Grants R01CA172638.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-56: Early Assessment of Treatment Response During Radiation Therapy Delivery for Esophageal Cancer Using Quantitative CT

Purpose: To investigate the feasibility of assessing treatment response using CTs during delivery of radiation therapy (RT) for esophageal cancer. Methods: Daily CTs acquired using a CT-on-Rails during the routine CT-guided RT for 20 patients with stage II to IV esophageal cancers were analyzed. All patients were treated with combined chemotherapy and IMRT of 45–50 Gy in 25 fractions, and were followed up for two years. Contours of GTV, spinal cord, and non-specified tissue (NST) irradiated with low dose were generated on each daily CT. A series of CT-texture metrics including Hounsfield Unit (HU) histogram, mean HU, standard derivation (STD), entropy, and energy were obtained in these contours on each daily CT. The changes of these metrics and GTV volume during RT delivery were calculated and correlated with treatment outcome. Results: Changes in CT texture (e.g., HU histogram) in GTV and spinal cord (but not in NST) were observed during RT delivery and were consistently increased with radiation dose. For the 20 cases studied, the mean HU in GTV was reduced on average by 4.0HU from the first to the last fractions, while 8 patients (responders) had larger reductions in GTV mean HU (average 7.8 HU) with an average GTV reduction of 51% and had increased consistently in GTV STD and entropy with radiation dose. The rest of 12 patients (non-responders) had lower reductions in GTV mean HU (average 1.5HU) and almost no change in STD and entropy. For the 8 responders, 2 experienced complete response, 7 (88%) survived and 1 died. In contrast, for the 12 non-responders, 4 (33%) survived and 8 died. Conclusion: Radiation can induce changes in CT texture in tumor (e.g., mean HU) during the delivery of RT for esophageal cancer. If validated with more data, such changes may be used for early prediction of RT response for esophageal cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

Purpose: Chemo-radiation therapy (CRT) is widely used in treating patients with locally advanced non-small cell lung cancer (NSCLC). Determination of the likelihood of patient response to treatment and optimization of treatment regime is of clinical significance. Up to date, no imaging biomarker has reliably correlated to NSCLC patient survival rate. This pilot study is to extract CT texture information from tumor regions for patient survival prediction. Methods: Thirteen patients with stage II-III NSCLC were treated using CRT with a median dose of 6210 cGy. Non-contrast-enhanced CT images were acquired for treatment planning and retrospectively collected for this study. Texture analysis was applied in segmented tumor regions using the Local Binary Pattern method (LBP). By comparing its HU with neighboring voxels, the LBPs of a voxel were measured in multiple scales with different group radiuses and numbers of neighbors. The LBP histograms formed a multi-dimensional texture vector for each patient, which was then used to establish and test a Support Vector Machine (SVM) model to predict patients’ one year survival. The leave-one-out cross validation strategy was used recursively to enlarge the training set and derive a reliable predictor. The predictions were compared with the true clinical outcomes. Results: A 10-dimensional LBP histogram was extracted from 3D segmented tumor region for each of the 13 patients. Using the SVM model with the leave-one-out strategy, only 1 out of 13 patients was misclassified. The experiments showed an accuracy of 93%, sensitivity of 100%, and specificity of 86%. Conclusion: Within the framework of a Support Vector Machine based model, the Local Binary Pattern method is able to extract a quantitative imaging biomarker in the prediction of NSCLC patient survival. More patients are to be included in the study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-662: Feasibility Study of Fe3O4/TaOx Nano Particles as a Radiosensitizer for Radiation Therapy

Purpose: To investigate the feasibility of using multifunctional Fe{sub 3}O{sub 4}/TaOx(core / shell) nano particles developed for CT and MRI contrast agent as dose enhancing radiosensitizers. Methods: Firstly, to verify the imaging detectability of Fe{sub 3}O{sub 4}/TaOx nano particles, in-vivo tests were conducted. Approximately 600 mg/kg of 19 nm diameter Fe{sub 3}O{sub 4}/TaOx nano particles dispersed in phosphate buffered saline(PBS) were injected to ten nude Balb/c mice through the tail vein. Difference between pre- and post-injection images was analyzed by computing the pixel histogram and correlation coefficient factor using MATLAB in the user defined ROI. Secondly, to quantify the potential therapeutic enhancement with nano materials, DER (Dose Enhancement Ratio) and number of SER (Secondary Electron Ratio) were computed using TOPAS(ver.2.0 P-03) MC simulation. Results: In CT, MRI imaging, the aorta, the blood vessel, and the liver were clearly visualized after intravenous injection of Fe{sub 3}O{sub 4}/TaOx nano particles. There was large different between pre and post-injection images of Histogram data and Coefficients of correlation factor in CT and MR are 0.006, 0.060, respectively. When 70 MeV protons were irradiated for a Gold, Tantalum, TaOx, Fe{sub 3}O{sub 4}/TaOx, Fe{sub 3}O{sub 4} nano particle, DER was 2.59, 2.41, 1.68, 1.54 and 1.36 respectively. Similarly, SER increment was 2.31, 2.15, 1.56, 1.46, and 1.27 for Gold, Tantalum, TaOx, Fe{sub 3}O{sub 4}/TaOx, Fe{sub 3}O{sub 4} nano particle, respectively. Conclusion: Fe{sub 3}O{sub 4}/TaOx nano particles have potential as a multifunctional agent which enhances the accuracy in cancer detection through visualization of developed tumor lesion and increases the therapeutic effect in proton therapy. The dose enhancement with Fe{sub 3}O{sub 4}/TaOx was estimated as half of the Gold. However, tumor targeting such as combined with magnetic field may overcome the low DER. This research was supported by the NRF funded by the Ministry of Science, ICT & Future Planning (2012M3A9B6055201 and 2012R1A1A2042414), Samsung Medical Center grant[GFO1130081].

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP1-09: Modality-Specific Dose Gradient Modeling for Prostate IMRT Using Spherical Distance Maps of PTV and Isodose Contours

Purpose: Overlapping volume histogram (OVH) and distance-to-target histogram (DTH) calculations rely on the assumption that dose gradients are symmetric with respect to primary target volume (PTV) expansion and minimum distance to PTV surface, respectively. It is desirable to lift this assumption and instead account for achievable modality-specific dose gradients (MSDG) for a given PTV shape. Methods: From a library of 96 prostate 7-beam IMRT plans, we computed spherical distance maps (SDMs) for PTVs and 3 iso-dose contours. Each SDM contains the minimum distances between plan isocenter and the object’s surface for a fixed set of azimuthal and polar angles. We performed principal component analysis (PCA)-based missing data recovery with PTV SDM as input and a single iso-dose contour SDM as output. Repeating this process for the set of iso-dose contours sparsely reconstructed the MSDG for a given PTV. DVH points were computed from the MSDG for bladder and rectum (OARs) as a natural way of casting patient-specific geometric information into modality-specific dose space (vs. OVH and DTH where data is purely geometric). For comparison, we implemented a cumulative (c)DTH-based prediction algorithm, and produced DVH for both OARs separately. We then computed linear regressions between each method and the DVH of the original patient plan for three different OAR DVH points. Results: R-squared for MSD-Gcomputed DVH vs. original plan DVH at V90%, V80% and V60% of max dose were 0.86, 0.83, and 0.78, for bladder and 0.36, 0.52, and 0.55 for rectum, respectively; R-squared for cDTH-based predicted DVH vs. original plan DVH were 0.67, 0.81, and 0.83, for bladder and 0.44, 0.50, and 0.51, for rectum, respectively. Conclusion: By simply modeling the MSDG about a given PTV, we are able to reproduce DVHs consistent with a validated cDTH-based DVH prediction. Regression analysis suggests MSDG could further improve predictions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-202-06: Improving the Performance of Gamma Analysis QA with Radiomics- Based Image Analysis

Purpose: The use of gamma analysis for IMRT quality assurance has well-known limitations. Traditionally, a simple thresholding technique is used to evaluated passing criteria. However, like any image the gamma distribution is rich in information which thresholding mostly discards. We therefore propose a novel method of analyzing gamma images that uses quantitative image features borrowed from radiomics, with the goal of improving error detection. Methods: 368 gamma images were generated from 184 clinical IMRT beams. For each beam the dose to a phantom was measured with EPID dosimetry and compared to the TPS dose calculated with and without normally distributed (2mm sigma) errors in MLC positions. The magnitude of 17 intensity histogram and size-zone radiomic features were derived from each image. The features that differed most significantly between image sets were determined with ROC analysis. A linear machine-learning model was trained on these features to classify images as with or without errors on 180 gamma images.The model was then applied to an independent validation set of 188 additional gamma distributions, half with and half without errors. Results: The most significant features for detecting errors were histogram kurtosis (p=0.007) and three size-zone metrics (p<1e-6 for each). The sizezone metrics detected clusters of high gamma-value pixels under mispositioned MLCs. The model applied to the validation set had an AUC of 0.8, compared to 0.56 for traditional gamma analysis with the decision threshold restricted to 98% or less. Conclusion: A radiomics-based image analysis method was developed that is more effective in detecting error than traditional gamma analysis. Though the pilot study here considers only MLC position errors, radiomics-based methods for other error types are being developed, which may provide better error detection and useful information on the source of detected errors. This work was partially supported by a grant from the Agency for Healthcare Research and Quality, grant number R18 HS022244-01.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-202-06: Correlating Lung CT HU with Transformation-Based and Xe-CT Derived Ventilation

Purpose: Regional lung ventilation is useful to reduce radiation-induced function damage during lung cancer radiation therapy. Recently a new direct HU (Hounsfield unit)-based method was proposed to estimate the ventilation potential without image registration. The purpose of this study is to examine if there is a functional dependence between HU values and transformation-based or Xe-CT derived ventilation. Methods: 4DCT images acquired from 13 patients prior to radiation therapy and 4 mechanically ventilated sheep subjects which also have associated Xe-CT images were used for this analysis. Transformation-based ventilation was computed using Jacobian determinant of the transformation field between peak-exhale and peak-inhale 4DCT images. Both transformation and Xe-CT derived ventilation was computed for each HU bin. Color scatter plot and cumulative histogram were used to compare and validate the direct HU-based method. Results: There was little change of the center and shape of the HU histograms between free breathing CT and 4DCT average, with or without smoothing, and between the repeated 4DCT scans. HU of −750 and −630 were found to have the greatest transformation-based ventilation for human and sheep subjects, respectively. Maximum Xe-CT derived ventilation was found to locate at HU of −600 in sheep subjects. The curve between Xe-CT ventilation and HU was noisy for tissue above HU −400, possibly due to less intensity change of Xe gas during wash-out and wash-in phases. Conclusion: Both transformation-based and Xe-CT ventilation demonstrated that lung tissues with HU values in the range of (-750, −600) HU have the maximum ventilation potential. The correlation between HU and ventilation suggests that HU might be used to help guide the ventilation calculation and make it more robust to noise and image registration errors. Research support from NIH grants CA166703 and CA166119 and a gift from Roger Koch.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-202-12: Voxel-Wise Analysis of Apparent Diffusion Coefficient and Perfusion Maps in Multi-Parametric MRI of Prostate Cancer

Purpose: Multi-parametric MRI (mp-MRI) is being introduced in radiotherapy (RT) of prostate cancer, including for tumour delineation in focal boosting strategies. We recently developed an image-based tumour control probability model, based on cell density distributions derived from apparent diffusion coefficient (ADC) maps. Beyond tumour volume and cell densities, tumour hypoxia is also an important determinant of RT response. Since tissue perfusion from mp-MRI has been related to hypoxia we have explored the patterns of ADC and perfusion maps, and the relations between them, inside and outside prostate index lesions. Methods: ADC and perfusion maps from 20 prostate cancer patients were used, with the prostate and index lesion delineated by a dedicated uro-radiologist. To reduce noise, the maps were averaged over a 3×3×3 voxel cube. Associations between different ADC and perfusion histogram parameters within the prostate, inside and outside the index lesion, were evaluated with the Pearson’s correlation coefficient. In the voxel-wise analysis, scatter plots of ADC vs perfusion were analysed for voxels in the prostate, inside and outside of the index lesion, again with the associations quantified with the Pearson’s correlation coefficient. Results: Overall ADC was lower inside the index lesion than in the normal prostate as opposed to ktrans that was higher inside the index lesion than outside. In the histogram analysis, the minimum ktrans was significantly correlated with the maximum ADC (Pearson=0.47; p=0.03). At the voxel level, 15 of the 20 cases had a statistically significant inverse correlation between ADC and perfusion inside the index lesion; ten of the cases had a Pearson < −0.4. Conclusion: The minimum value of ktrans across the tumour was correlated to the maximum ADC. However, on the voxel level, the ‘local’ ktrans in the index lesion is inversely (i.e. negatively) correlated to the ‘local’ ADC in most patients. Research agreement with Varian Medical Systems, not related to the work presented in this abstract.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-207A-10: Using the Gamma Index to Flag Changes in Anatomy During Radiation Therapy of Head and Neck Cancer

Purpose: This article presents a fast algorithm for comparing 3-D anatomy from Cone-Beam CT (CBCT) imaging using the gamma comparison index and to demonstrate how this can be used to flag patients for possible re-planning of treatment. Methods: CBCT scans acquired on a Varian linear accelerator during treatment were used as input to the gamma comparator using thresholds of 5 mm distance to agreement and 30 Hounsfield Unit CT number difference. The fraction 1 CBCT study was initially used as the reference. Should there be a re-plan during treatment, the reference resets to the CBCT study acquired on the day 1 of the re-plan. Histograms of failing pixels (γ > 1) were generated from each 3-D gamma map. An indicator of anatomy congruence, the match quality parameter (MQP), was derived from failed pixel histograms using the 90th percentile gamma value. The MQP was plotted versus fraction number and related to actual repeat computed tomography (re-CT) order dates as decided by a radiation oncologist. From this, decision criteria were derived for the algorithm to “trigger” re-CT consideration and predictive power was scored using receiver-operator characteristic (ROC) analysis. Results: The MQP plot generally showed that the on-line match from CBCT image guidance deteriorated as the treatment progressed due to weight loss and tumor regression. The optimized MQP criteria for triggering re-CT consideration demonstrated high sensitivity and specificity, consistent with actual re-CT order dates within ± 3 fractions. Out of 20 patients that were actually re-planned, the algorithm failed to trigger a re-CT recommendation only twice and this was caused by CBCT ring artifacts. Conclusion: We have demonstrated that gamma comparisons can be used to evaluate CBCT-acquired anatomy pairs and, from this, an algorithm can be “trained” to flag patients for possible re-planning in a manner consistent with local radiation oncology practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-209-05: Impact of Spot Size and Spacing On the Quality of Robustly-Optimized Intensity-Modulated Proton Therapy Plans for Lung Cancer

Purpose: To investigate how spot size and spacing affect plan quality, especially, plan robustness and the impact of interplay effect, of robustly-optimized intensity-modulated proton therapy (IMPT) plans for lung cancer. Methods: Two robustly-optimized IMPT plans were created for 10 lung cancer patients: (1) one for a proton beam with in-air energy dependent large spot size at isocenter (σ: 5–15 mm) and spacing (1.53σ); (2) the other for a proton beam with small spot size (σ: 2–6 mm) and spacing (5 mm). Both plans were generated on the average CTs with internal-gross-tumor-volume density overridden to irradiate internal target volume (ITV). The root-mean-square-dose volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under RVH curves were used to evaluate plan robustness. Dose evaluation software was developed to model time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Patient anatomy voxels were mapped from phase to phase via deformable image registration to score doses. Dose-volume-histogram indices including ITV coverage, homogeneity, and organs-at-risk (OAR) sparing were compared using Student-t test. Results: Compared to large spots, small spots resulted in significantly better OAR sparing with comparable ITV coverage and homogeneity in the nominal plan. Plan robustness was comparable for ITV and most OARs. With interplay effect considered, significantly better OAR sparing with comparable ITV coverage and homogeneity is observed using smaller spots. Conclusion: Robust optimization with smaller spots significantly improves OAR sparing with comparable plan robustness and similar impact of interplay effect compare to larger spots. Small spot size requires the use of larger number of spots, which gives optimizer more freedom to render a plan more robust. The ratio between spot size and spacing was found to be more relevant to determine plan robustness and the impact of interplay effect than spot size alone. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant, and by The Kemper Marley Foundation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Multicanonical sampling of the space of states of ℋ(2, n)-vector models

Problems of temperature behavior of specific heat are solved by the entropy simulation method for Ising models on a simple square lattice and a square spin ice (SSI) lattice with nearest neighbor interaction, models of hexagonal lattices with short-range (SR) dipole interaction, as well as with long-range (LR) dipole interaction and free boundary conditions, and models of spin quasilattices with finite interaction radius. It is established that systems of a finite number of Ising spins with LR dipole interaction can have unusual thermodynamic properties characterized by several specific-heat peaks in the absence of an external magnetic field. For a parallel multicanonical sampling method, optimal schemes are found empirically for partitioning the space of states into energy bands for Ising and SSI models, methods of concatenation and renormalization of histograms are discussed, and a flatness criterion of histograms is proposed. It is established that there is no phase transition in a model with nearest neighbor interaction on a hexagonal lattice, while the temperature behavior of specific heat exhibits singularity in the same model, in case of LR interaction. A spin quasilattice is found that exhibits a nonzero value of residual entropy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Simulation of polarized optical radiation transport in time and frequency representations

Monte Carlo simulation of backward scattering of polarized optical radiation has been performed in the time and frequency representations based on the description of radiation transport in terms of the Bethe–Salpeter equation. The histograms of an ultrashort pulse of linearly or circularly polarized radiation have been calculated in the time representation; it is found that for distances between the source and detector on the order of the transport length, the histograms exhibit a strong dependence on the polarization type; in the case of circular polarization, the direction of the polarization plane rotation changes upon an increase in the scattering anisotropy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Formation of Radiation Defects by Proton Braking in Lightly Doped n- and p-SiC Layers

Mathematical simulation of the cascade of displacements in SiC is used to consider the specific features of Frenkel-pair generation upon the scattering of 8- and 15-MeV protons. The distribution histograms of energies acquired not only by primary knocked-out atoms, but also by recoil atoms generated in displacement cascades, are calculated. An analysis of the histograms considers two energy ranges. In the first range of “low” energies, the spontaneous recombination of genetically related Frenkel pairs is dominant. Recoil atoms in the second range have a higher energy, which enables these atoms to leave the spontaneousrecombination zone and dissociate into isolated components. The compensation of lightly doped n- and p-4H-SiC samples grown by gas-phase epitaxy is experimentally studied under irradiation with 8- and 15-MeV protons. The carrier removal rates are measured. The calculated and experimental data are compared and estimates are obtained for the size of the spontaneous-recombination zone.

36 MATERIALS SCIENCE↗
DOE OSTI2019

pnnl/rhizo_phosph

Python package to be used when working with the DDAO method of visualizing phosphatase activity in the rhizosphere. Includes a module with functions that generate figures for analysis of phosphatase levels in images of soil and root based on pixel intensity. These functions can be used on images with a single root or multiple roots. Figures include distance maps to show how phosphatase levels change as you move away from the root and along the roots themselves, line plots to show average phosphatase levels moving down the root and the soil surrounding the root, 2D histograms to show how phosphatase levels change moving away from the root, and 1D histograms to show overall differences in phosphatase distribution depending on whether a root was grown next to a phosphorus source or not.

McGrady, Monee↗
DOE OSTI2018

pnnl/pg-histogram

PostgreSQL histograms for ActiveRecord relations. A plugin for the Ruby on Rails (RoR) web application development framework web application development framework that leverages the "Active Relation" relational algebra component to automatically formulate SQL statements for the construction of histograms.

Borkum, Mark↗
DOE OSTI2022

areaDetector/ADTimePix3

ADTimePix3 is an open‑source EPICS areaDetector driver for TimePix3 pixel detectors from Advanced Scientific Instruments (ASI). It provides a complete control and data‑acquisition interface between EPICS and the Serval server, supporting both real detectors (single‑chip and 2×2 quad configurations) and the TimePix3 emulator. The driver configures measurements via an HTTP/JSON REST API and acquires data through high‑rate TCP streams for raw events, images, and histograms. It offers real‑time preview and accumulated images, Time‑of‑Flight histogram processing, pixel masking (including Binary Pixel Configuration files and hot‑pixel tools), extensive health and status monitoring, and integration with standard areaDetector plugins for file saving and downstream analysis. ADTimePix3 is designed for Linux 64‑bit systems (tested on Ubuntu and RHEL) and is distributed under an MIT license with additional institutional disclaimers, enabling reuse and extension in photon science beamlines and other TimePix3‑based experimental facilities.

Gofron, Kaz↗