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At least 343 records · Page 19

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DOE OSTI2015

Derivation of effective penetration depth of femtosecond laser pulses in metal from ablation rate dependence on laser fluence, incidence angle, and polarization

Ablation rate dependence on laser fluence for copper subjected to oblique femtosecond laser irradiation has been determined experimentally in order to investigate processing induced by oblique irradiation. A difference of ablation rate between p-polarized and s-polarized oblique irradiation is clearly observed. Effective penetration depth is defined to explain the ablation rate dependence instead of using optical penetration depth, which is treated as a key value for determining the ablation rate in conventional theory. The effective penetration depth for copper is presented in simple formulas as a function of laser incidence angle for each polarization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Crack depth profiling using guided wave angle dependent reflectivity

Tomographic corrosion monitoring techniques have been developed, using two rings of sensors around the circumference of a pipe. This technique is capable of providing a detailed wall thickness map, however this might not be the only type of structural damage. Therefore this concept is expanded to detect and size cracks and small corrosion defects like root corrosion. The expanded concept uses two arrays of guided-wave transducers, collecting both reflection and transmission data. The data is processed such that the angle-dependent reflectivity is obtained without using a baseline signal of a defect-free situation. The angle-dependent reflectivity is the input of an inversion scheme that calculates a crack depth profile. From this profile, the depth and length of the crack can be determined. Preliminary experiments show encouraging results. The depth sizing accuracy is in the order of 0.5 mm.

42 ENGINEERING↗

DOE OSTI2015

Depth profile characterization with noncollinear beam mixing

Noncollinear beam mixing is an ultrasonic approach to quantify elastic nonlinearity within a subsurface volume of material. The technique requires interaction between two beams of specific frequency, angle, and vibration mode to generate a third beam propagating from the intersection volume. The subsurface depth to interaction zone is controlled by changing the separation distance between the two input transducers, and the amplitude of the third generated beam is proportional to the elastic nonlinearity within the interaction zone. Therefore, depth profiling is possible if a suitable parameter is established to normalize the detected signal independent of propagation distances and input amplitudes. This foundational effort has been conducted toward developing such a parameter for depth profile measurements in homogeneous aluminum that includes corrective terms for attenuation, beam overlap noise, beam spread, and input amplitudes. Experimental and analytical results are provided, and suggested applications and improvements are discussed toward characterizing subsurface material property profiles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Long range surface plasmon resonance with ultra-high penetration depth for self-referenced sensing and ultra-low detection limit using diverging beam approach

Using an insulator-metal-insulator structure with dielectric having refractive index (RI) larger than the analyte, long range surface plasmon (SP) resonance exhibiting ultra-high penetration depth is demonstrated for sensing applications of large bioentities at wavelengths in the visible range. Based on the diverging beam approach in Kretschmann-Raether configuration, one of the SP resonances is shown to shift in response to changes in the analyte RI while the other is fixed; thus, it can be used as a built in reference. The combination of the high sensitivity, high penetration depth and self-reference using the diverging beam approach in which a dark line is detected of the high sensitivity, high penetration depth, self-reference, and the diverging beam approach in which a dark line is detected using large number of camera pixels with a smart algorithm for sub-pixel resolution, a sensor with ultra-low detection limit is demonstrated suitable for large bioentities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

STARSPOTS-TRANSIT DEPTH RELATION OF THE EVAPORATING PLANET CANDIDATE KIC 12557548b

Violent variation of transit depths and an ingress-egress asymmetry of the transit light curve discovered in KIC 12557548 have been interpreted as evidence of a catastrophic evaporation of atmosphere with dust ( M-dot {sub p}∼>1 M{sub ⊕} Gyr{sup –1}) from a close-in small planet. To explore what drives the anomalous atmospheric escape, we perform time-series analysis of the transit depth variation of Kepler archival data for ∼3.5 yr. We find a ∼30% periodic variation of the transit depth with P {sub 1} = 22.83 ± 0.21 days, which is within the error of the rotation period of the host star estimated using the light curve modulation, P {sub rot} = 22.91 ± 0.24 days. We interpret the results as evidence that the atmospheric escape of KIC 12557548b correlates with stellar activity. We consider possible scenarios that account for both the mass loss rate and the correlation with stellar activity. X-ray and ultraviolet (XUV)-driven evaporation is possible if one accepts a relatively high XUV flux and a high efficiency for converting the input energy to the kinetic energy of the atmosphere. Star-planet magnetic interaction is another possible scenario, though huge uncertainty remains for the mass loss rate.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

ODDS: Real-Time Object Detection Using Depth Sensors on Embedded GPUs

Detecting objects that are carried when someone enters or exits a room is very useful for a wide range of smart building applications including safety, security, and energy efficiency. While there has been a significant amount of work on object recognition using large-scale RGB image datasets, RGB cameras are too privacy invasive in many smart building applications and they work poorly in the dark. Additionally, deep object detection networks require powerful and expensive GPUs. We propose a novel system that we call ODDS (Object Detector using a Depth Sensor) that can detect objects in real-time using only raw depth data on an embedded GPU, e.g., NVIDIA Jetson TX1. Hence, our solution is significantly less privacy invasive (even if the sensor is compromised) and less expensive, while maintaining a comparable accuracy with state of the art solutions. Specifically, we resort to training a deep convolutional neural network using raw depth images, with curriculum based learning to improve accuracy by considering the complexity and imbalance in object classes and developing a sparse coding based technique that speeds up the system ~2× with minimal loss of accuracy. Based on a complete implementation and real-world evaluation, we see ODDS achieve 80.14% mean average precision in object detection in real-time (5-6 FPS) on a Jetson TX1.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Real-Time Fine Grained Occupancy Estimation Using Depth Sensors on ARM Embedded Platforms

Occupancy estimation is an important primitive for a wide range of applications including building energy efficiency, safety, and security. In this paper, we explore the potential of using depth sensors to detect, estimate, identify, and track occupants in buildings. While depth sensors have been widely used for human detection and gesture recognition, computer vision algorithms are typically run on a powerful computer like XBOX or Intel R CoreTM i7 processor. In this work, we develop a prototype system called FORK using off-the-shelf components that performs the entire depth data processing on a cheaper and low power ARM processor in real-time. As ARM processors are extremely weak in running computer vision algorithms, FORK is designed to detect humans and track them in a very efficient way by leveraging a novel lightweight model based approach instead of traditional approaches based on histogram of oriented gradients (HOG) features. Unlike other camera based approaches, FORK is much less privacy invasive (even if the sensor is compromised). Based on a complete implementation, real-world deployment, and extensive evaluation at realistic scenarios, we observe that FORK achieves over 99% accuracy in real-time (4-9 FPS) in occupancy estimation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

High resolution depth profiling using near-total-reflection hard x-ray photoelectron spectroscopy

By adjusting the incidence angle of incoming x rays near the critical angle of x-ray total reflection, photoelectron intensity is strongly modulated due to the variation of x-ray penetration depth. Photoelectron spectroscopy combined with near-total reflection exhibits tunable surface sensitivity, providing depth-resolved information. In this Review, we first describe the experimental setup and specific data analysis process. We then review three different examples that show the broad application of this method. Furthermore, the emphasis is on its applications correlated to oxide heterostructures, especially quantitative depth analyses of compositions and electronic states. In the last part, we discuss the limitations of this technique, mostly in terms of the range of samples that can be studied.

36 MATERIALS SCIENCE↗

DOE OSTI2015

SU-E-T-93: Activation of Psoralen at Depth Using Kilovoltage X-Rays: Physics Considerations in Implementing a New Teletherapy Paradigm

Purpose: Psoralen is a UV-light activated anti-cancer biotherapeutic used for treating skin lesions (PUVA) and advanced cutaneous T-cell lymphoma (ECP). To date psoralen has not been used to treat deep seated tumors due to difficulty in generating UV-light at depth. We recently demonstrated psoralen activation at depth by introducing energy converting particles that absorb kV x-ray radiation and re-emit UV-light. Our in-vitro work found that 0.2–1Gy using 40–100kVp x-rays combined with psoralen and particles can induce a substantial apoptotic response beyond that expected from the sum of individual components. In preparation for a phase I clinical trial of canine companion animals, we address the physics and dosimetry considerations for applying this new teletherapy paradigm to an in-vivo setting. Methods: The kV on-board imaging (OBI) system mounted on a medical linear accelerator (Varian) was commissioned to deliver the prescribed dose (0.6Gy) using 80 and 100kVp. Dosimetric measurements included kVp, HVL, depth dose, backscatter factors, collimator and phantom scatter factors, field size factors, and blade leakage. Absolute dosimetry was performed following AAPM TG61 recommendations and verified with an independent kV dose meter. We also investigated collimated rotational delivery to minimize skin dose using simple dose calculations on homogeneous cylindrical phantoms. Results: Single beam delivery is feasible for shallow targets (<5cm) without exceeding skin tolerance, while a rotational delivery may be utilized for deeper targets; skin dose is ∼75% of target dose for 80kVp collimated rotational delivery to a 3cm target within a 20cm phantom. Heat loading was tolerable; 0.6Gy to 5cm can be delivered before the anode reaches 75% capacity. Conclusion: KV teletherapy for Psoralen activation in deep seated tissue was successfully commissioned for a Varian OBI machine for use in a phase I clinical trial in canines. Future work will use Monte Carlo dosimetry to investigate dose in presence of bone. Research funded by Immunolight LLC. H. Walder, Z. Fathi, & W. Beyer are employees of Immunolight LLC which holds a patent on the technology. Drs. Adamson and Oldham are consultants to Immunolight LLC.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-678: Response Calibration Using Electron Depth-Dose Data for MRI-Based 3D Polymer Gel Dosimetry

Purpose: To evaluate a calibration method using the depth-dose data of an electron beam for MRI-based polymer gel dosimetry. Methods: MAGAT was manufactured in-house to fill two 400mL-cylindrical phantoms and nine 22mL-glass vials. Phantom-A was irradiated along the cylinder axis with a 9MeV electron beam of 6 cm x 6 cm field size (FS). Phantom-B was irradiated with a 6MV photon beam of 3 cm x 3 cm FS by a 360-degree arc technique. Eight vials were irradiated in a water-bath to various doses with a 20 cm x 20 cm FS 6MV photon beam. All irradiated phantoms and one un-irradiated vial were scanned with a 3T MRI scanner to obtain the spin-spin relaxation rate (R2) distributions. By comparing the measured R2-to-depth data with the known depth-dose data for Phantom-A, R2-to-dose calibration data were obtained (e-beam method). Another calibration data were obtained from the 9 vials data (9-vial method). We tested two regression equations, i.e., third-order polynomial and tangent functions, and two dose normalization methods, i.e., one-point and two-point methods. Then, these two calibration methods were used to obtain the 3D dose distribution of Phantom-B and evaluated by comparing the measured data with the dose distribution from a treatment planning system. The comparison was made with gamma passing rate (2%/2mm criteria). Results: We did not observe a clear advantage of the e-beam method over the 9-vial method for the 3D dose comparison with the test case. Nevertheless, we found that the e-beam method required a smaller dose scaling for the dose comparison. Furthermore, the tangent function showed better data fitting than the polynomial function with smaller uncertainty of the estimated coefficients. Conclusions: Considering the overall superior performance, we recommend the e-beam method with the tangent function as the regression equation and one-point dose normalization for the MRI-based polymer gel dosimetry.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Influence of soil depth, irrigation, and plant genotype on the soil microbiome, metaphenome, and carbon chemistry

ABSTRACT Climate change is causing an increase in drought in many soil ecosystems and a loss of soil organic carbon. Calcareous soils may partially mitigate these losses via carbon capture and storage. Here, we aimed to determine how irrigation-supplied soil moisture and perennial plants impact biotic and abiotic soil properties that underpin deep soil carbon chemistry in an unfertilized calcareous soil. Soil was sampled up to 1 m in depth from irrigated and planted field treatments and was analyzed using a suite of omics and chemical analyses. The soil microbial community composition was impacted more by irrigation and plant cover treatments than by soil depth. By contrast, metabolomes, lipidomes, and proteomes differed more with soil depth than treatments. Deep soil (>50 cm) had higher soil pH and calcium concentrations and higher levels of organic acids, bicarbonate, and triacylglycerides. By contrast, surface soil (0–5 cm) had higher concentrations of soil organic matter, organic carbon, oxidizable carbon, and total nitrogen. Surface soils also had higher amounts of sugars, sugar alcohols, phosphocholines, and proteins that reflect osmotic and oxidative stress responses. The lipidome was more responsive to perennial tall wheatgrass treatments compared to the metabolome or proteome, with a striking change in diacylglyceride composition. Permanganate oxidizable carbon was more consistently correlated to metabolites and proteins than soil organic and inorganic carbon and soil organic matter. This study reveals specific compounds that reflect differences in organic, inorganic, and oxidizable soil carbon fractions that are impacted by interactions between irrigation-supplied moisture and plant cover in calcareous soil profiles. IMPORTANCE Carbon is cycled through the air, plants, and belowground environment. Understanding soil carbon cycling in deep soil profiles will be important to mitigate climate change. Soil carbon cycling is impacted by water, plants, and soil microorganisms, in addition to soil mineralogy. Measuring biotic and abiotic soil properties provides a perspective of how soil microorganisms interact with the surrounding chemical environment. This study emphasizes the importance of considering biotic interactions with inorganic and oxidizable soil carbon in addition to total organic carbon in carbonate-containing soils for better informing soil carbon management decisions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Сomposition Depth Profiling of the GaAs Native Oxide Irradiated by an Ar{sup +} Ion Beam

The elemental and chemical compositions throughout the thickness of the GaAs native oxide layer slightly irradiated by Ar{sup +} ions have been studied by synchrotron-based photoelectron spectroscopy at different photon energies enabling variation of probing depth. The presence of only two phases was observed: of the gallium oxide Ga{sub 2}O{sub 3} and elementary arsenic As{sup o} generated due to complete decay of arsenic oxides under the ion irradiation. Depth composition profiles were determined nondestructively. Despite inhomogeneous depth distribution, these profiles demonstrated domination (90 at %) of the dielectric Ga{sub 2}O{sub 3} phase virtually throughout all the oxide thickness (~2 nm).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Data depth based clustering analysis

Here, this paper proposes a new algorithm for identifying patterns within data, based on data depth. Such a clustering analysis has an enormous potential to discover previously unknown insights from existing data sets. Many clustering algorithms already exist for this purpose. However, most algorithms are not affine invariant. Therefore, they must operate with different parameters after the data sets are rotated, scaled, or translated. Further, most clustering algorithms, based on Euclidean distance, can be sensitive to noises because they have no global perspective. Parameter selection also significantly affects the clustering results of each algorithm. Unlike many existing clustering algorithms, the proposed algorithm, called data depth based clustering analysis (DBCA), is able to detect coherent clusters after the data sets are affine transformed without changing a parameter. It is also robust to noises because using data depth can measure centrality and outlyingness of the underlying data. Further, it can generate relatively stable clusters by varying the parameter. The experimental comparison with the leading state-of-the-art alternatives demonstrates that the proposed algorithm outperforms DBSCAN and HDBSCAN in terms of affine invariance, and exceeds or matches the ro-bustness to noises of DBSCAN or HDBSCAN. The robust-ness to parameter selection is also demonstrated through the case study of clustering twitter data.

58 GEOSCIENCES↗

DOE OSTI2019

Dataset: Occupancy Detection, Tracking, and Estimation Using a Vertically Mounted Depth Sensor

Occupancy detection, tracking, and estimation has a wide range of applications including improving building energy efficiency, safety, and security of the occupants. As depth sensors are getting cheaper, they offer a viable solution to estimate occupancy accurately in a non-privacy invasive manner. Even though there are publicly available depth datasets, they do not consider placing the sensor in the ceiling looking downwards to estimate occupancy. We deployed four Kinect for XBOX One in four CMU classrooms and conference rooms for a period of four weeks in 2017 and collected over 6 TB of depth data. We annotate this huge dataset by labelling bounding boxes around occupants and release the annotated dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Kinetic and temperature sensitivity properties of soil exoenzymes through the soil profile down to one-meter depth at a temperate coniferous forest (Blodgett, CA)

This dataset contains data on kinetic and temperature sensitivity parameters of the exoenzymes β-glucosidase (BG), leucine/leucyl aminopeptidase (LAP) and acid phosphatase (AP) across a soil profile down to 90 cm depth at Blodgett forest, CA, USA. These data were generated to determine if kinetic and thermal properties of microbial exoenzymes involved in organic matter decomposition varied with soil depth, following variation in soil properties and microbial communities, as part of the study: Alves et al. (2021). Kinetic Properties of Microbial Exoenzymes Vary with Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile. Frontiers in Microbiology 12:3618. https://doi.org/10.3389/fmicb.2021.735282. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a long-term field warming experiment of the whole soil profile at Blodgett forest. Samples for this work were collected from locations representative of the field experimental plots. Potential enzyme activity rates were measured using laboratory fluorometric assays with soils collected at 0-10, 10-20, 30-40, 50-60, 60-70 and 80-90 cm deep in biological triplicates (i.e., three soil cores collected at different representative locations). Assays with each soil were conducted over a gradient of eight substrate concentrations per enzyme, and incubated at 4, 10, 16, 25, 35 or 50°C. Enzyme Michaelis-Menten kinetics were modeled over the eight substrate concentrations at each temperature, and the temperature sensitivity of the kinetic parameters was modeled over the six temperatures using linear Arrhenius/Q10 and non-linear Macromolecular Rate Theory (MMRT) models. The dataset includes the fully processed enzyme activity rate data used to model Michaelis-Menten kinetics, calculated kinetic and temperature sensitivity parameters, and basic soil and microbial biomass chemistry for each sample. All data is provided for each individual biological replicate, and kinetic and temperature sensitivity parameters are also provided as means of the biological replicates. The dataset also includes all raw measurement data and code used to parse, combine and perform the analyses described by Alves et al. (2021). For file descriptions, see the file-level metadata files: “enzymes_dataProcessed_flmd.xlsx” (processed data); “enzymes_dataRaw_flmd.xlsx” (compressed raw data and metadata); and “enzymes_code_flmd.xlsx” (compressed code). The experimental design, list of parameters measured, soil and microbial biomass chemistry data, and means of biological replicates for kinetic and temperature sensitivity parameters are also provided as human-readable tables in file “enzymeTraits_design_results_tables.xlsx”.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023

This data package presents snow depths data from distributed temperature probes at 18 locations near Snodgrass catchment, Colorado. These data show that snow melt-out dates are approximately one or two weeks later under evergreen forests compared to other vegetation types even at the same elevation. These data were collected to understand how snowmelt heterogeneity impacts headwater hydrology, including streamflow and groundwater levels. They were also used to compare with process-based model simulations of snow depth to evaluate whether the model accurately represents snowmelt dynamics and their effects on headwater hydrology. Snow_DTPs_locations.csv includes all probes locations and their associated elevation and vegetation types. Snow_Depth_Snodgrass_WY2022_2023.csv includes processed snow depths datasets for Water Year (WY) 2022 and 2023. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Several probes have recordings for WY 2021.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Results of Hg speciation testing on tanks 30, 32, and 37 depth samples

The Savannah River National Laboratory (SRNL) was tasked with preparing and shipping samples for Hg speciation by Eurofins Frontier Global Sciences, Inc. in Seattle, WA on behalf of the Savannah River Remediation (SRR) Mercury Task Team. The twelfth shipment of samples was designated to include 3H evaporator system Tank 30, 32, and 37 depth samples. The Tank 30 depth sample (HTF-30-15-70) was taken at 190 inches from the tank bottom and the Tank 32 depth sample (HTF-32-15-68) was taken at 89 inches from the tank bottom and both were shipped to SRNL on June 29, 2015 in an 80 mL stainless steel dip bottles. The Tank 37 surface sample (HTF-37-15-94) was taken around 253.4 inches from the tank bottom and shipped to SRNL on July 21, 2015 in an 80 mL stainless steel dip bottle. All samples were placed in the SRNL Shielded Cells and left unopened until intermediate dilutions were made on July 24, 2015 using 1.00 mL of sample diluted to 100.00 mL with deionized H 2 O. A 30 mL Teflon® bottle was rinsed twice with the diluted tank sample and then filled leaving as little headspace as possible. It was immediately removed from the Shielded Cells and transferred to refrigerated storage where it remained at 4 °C until final dilutions were made on October 20. A second portion of the cells diluted tank sample was poured into a shielded polyethylene bottle and transferred to Analytical Development for radiochemical analysis data needed for Hazardous Material Transportation calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

Trade-offs in sensitivity and sampling depth in bimodal atomic force microscopy and comparison to the trimodal case

This paper presents experiments on Nafion ® proton exchange membranes and numerical simulations illustrating the trade-offs between the optimization of compositional contrast and the modulation of tip indentation depth in bimodal atomic force microscopy (AFM). We focus on the original bimodal AFM method, which uses amplitude modulation to acquire the topography through the first cantilever eigenmode, and drives a higher eigenmode in open-loop to perform compositional mapping. This method is attractive due to its relative simplicity, robustness and commercial availability. We show that this technique offers the capability to modulate tip indentation depth, in addition to providing sample topography and material property contrast, although there are important competing effects between the optimization of sensitivity and the control of indentation depth, both of which strongly influence the contrast quality. Furthermore, we demonstrate that the two eigenmodes can be highly coupled in practice, especially when highly repulsive imaging conditions are used. Finally, we also offer a comparison with a previously reported trimodal AFM method, where the above competing effects are minimized.

36 MATERIALS SCIENCE↗