Results for “exploration techniques” — Page 56

DOE OSTI2016

WE-A-BRC-00: The Quality Gap

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk-based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk-based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomes D. Followill, NIH Grant CA180803.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-A-BRC-01: Introduction to the Certificate Course

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk-based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk-based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomes D. Followill, NIH Grant CA180803.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-A-BRC-02: Lessons Learned: Clinical Trials and Operations

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk-based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk-based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomes D. Followill, NIH Grant CA180803.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-A-BRC-03: Lessons Learned: IROC Audits

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk-based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk-based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomes D. Followill, NIH Grant CA180803.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

Assessing the Effect of Parametric Uncertainty on the FRAPCON-3.4 Thermal Conductivity Model

In the absence of a well-accepted, mathematical description of how units of material respond to one or more external actions, scientists must often rely upon empirically-derived models to make predictions. These models are often employed to model very complex phenomena, with an unfortunate side-effect that intuition, as to the values of particular model parameters, may not serve to guide their use. Given our increased reliance on modeling and simulation to make predictions in the absence of experimental data, it befits the scientific and engineering communities to explore and report upon uncertainty quantification techniques applied to previously adopted (or at least well-accepted) empirical models that derive from or pertain to substantial experimental data sets. This report represents a collection of three methodologies aimed at assessing the predictive capability of the empirical thermal conductivity model adopted by the nuclear fuel performance code, FRAPCON-3.4. Each of these methodologies considers the effect of uncertain parameters – a plausible reality in the context of empirically-derived models – on the ability of the model to predict uranium dioxide conductivity data from open literature sources. The results lead the authors to question the predictive capability of the FRAPCON model for predicting the thermal conductivities associated with irradiated fuel samples. The report concludes with a preliminary examination of Idaho National Laboratory’s (INL) nuclear fuel performance code, BISON, developed under INL’s Multiphysics Object Oriented Simulation Environment (MOOSE).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2012

Reduced order modelling for dynamic simulations: LDRD feasibility study final report

This feasibility study (12-FS-007) investigated the current state-of-the-art for the construction of reduced order models (ROMs) from dynamic PDE-based simulations. One novel result of was the demonstration of a time-partitioned ROM for the advection-diffusion equation that achieved high accuracy with a small ROM size. The time-domain of a model PDE was partitioned and a fixed-size ROM was tuned to each subdomain resulting in an effective method for achieving an efficient and accurate ROM for a dynamic problem. This LDRD also investigated the construction ROMs for simulations that utilize overlapping grids. In this case, it was found that weighting the discrete inner product in a manner that approximates the continuous inner product yields a significantly more accurate ROM. This project demonstrated the feasibility of applying reduced order models to complex PDE-based simulation tools and explored the benefits of adaptive ROM techniques. The results of the work led to an Exploratory Research LDRD, funded for FY13, that will focus on the development of composite adaptive reduced order models suitable for use with a number of LLNL applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Final technical report for project titled Quantitative Characterization of Cell Aggregation/Adhesion as Predictor for Distribution and Transport of Microorganisms in Subsurface Environment

This project aims to explore and develop enabling methodology and techniques for nano-scale characterization of microbe cell surface contact mechanics, interactions and adhesion quantities that allow for identification and quantification of indicative properties related to microorganism migration and transport behavior in porous media and in subsurface environments. Microbe transport has wide impact and therefore is of great interest in various environmental applications such as in situ or enhanced subsurface bioremediation,filtration processes for water and wastewater treatments and protection of drinking water supplies. Although great progress has been made towards understanding the identities and activities of these microorganisms in the subsurface, to date, little is known of the mechanisms that govern the mobility and transport of microorganisms in DOE’s contaminated sites, making the outcomes of in situ natural attenuation or contaminant stability enhancement unpredictable. Conventionally, movement of microorganisms was believed to follows the rules governing solute (particle) transport. However, recent studies revealed that cell surface properties, especially those pertaining to cell attachment/adhesion and aggregation behavior, can cause the microbe behavior to deviate from non-viable particles and hence greatly influence the mobility and distribution of microorganisms in porous media.This complexity highlights the need to obtain detailed information of cell-cell and cell-surface interactions in order to improve and refine the conceptual and quantitative model development for fate and transport of microorganisms and contaminant in subsurface. Traditional cell surface characterization methods are not sufficient to fully predict the deposition rates and transport behaviors of microorganism observed. A breakthrough of methodology that would allow for quantitative and molecular-level description of intrinsic cell surface properties indicative for cell-surface interactions is essential for the field. To tackle this, we have developed a number of new Bio-nanomechanical techniques, including reflection interference contrast microscopy (RICM) and bio-AFM (Atomic Force Microscopy), for cell adhesion-detachment measurement of the long-range surface interactions, in combination with mathematical modeling, which would allow us to characterize the mechanical behavior from single cell to multi-cell aggregate, critical thresholds for large scale coaggregation and transportation of cells and aggregates in the presence of long range inter-surface forces etc. Although some technical and mathematical challenges remain, the preliminary results promise great breakthrough potential. In this study, we investigated the cellular surface characteristics of representative bio-remediating microorganisms relevant to DOE IFRC (Integrated Field-Scale Subsurface Research Challenges) sites and their transport behaviors in porous media, aiming to draw a groundbreaking correlation between the micro-scale genetic and biological origin-based cell surface properties, the consequent mechanical adhesion and aggregation behaviors, and the macro-scale microbial mobility and retention in porous media, which are unavailable in the literature. The long-term goal is to significantly improve the mechanistic and quantitative understanding of microbial mobility, sorption, and transport within reactive transport models as needed to manipulate subsurface contaminant fate and transport predictions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Literature Review of Nanosprings

Nanosprings are helical structures grown on the nanoscale. Numerous choices exist for composition and coating which give them a wide range of possible uses. They compare favorably in some aspects to other nanostructures and unfavorably in other aspects. This paper reviews the available literature, discusses techniques for formation and coating, and explores a variety of potential applications that may be developed in the near future.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2019

Mobile Device Application for Gunshot Trilateration

The New Mexico Small Business Assistance program at Sandia National Labs and Parental Values, LLC have agreed to explore commonly known principles to describe techniques in trilateration. The objective from Parental Values' standpoint is to use these commonly known principles for the purpose of their own software development by their employees. The software would be meant for mobile devices held by minors and the software would be monitored by parent(s) and/or guardians. The software would be able to notify parent(s)/guardian(s) in the event of an active shooter in a proximity close enough for the mobile devices' onboard microphones to detect a gunshot's noise. This document is meant for the employees of Parental Values to understand the commonly known principles as it applies to their intended implementation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Growth of New High-Quality and Large-Size Single Crystals via High Pressure Floating-Zone Technique

This award supports experimental materials physics research on a class of technologically relevant materials that cannot form under ambient conditions. With the complementary expertise at Louisiana State University (LSU) and infrastructure at Oak Ridge National Laboratory (ORNL), single crystals of these materials will be synthesized using the high-pressure floating-zone technique. Our ability to grow high-quality single crystals will facilitate advanced characterization of these materials and improve the scientific outcomes. In addition to in-house material characterization, the principle investigator will partner with scientists at ORNL and Brookhaven National Laboratory (BNL) to tackle materials problems using the state-of-the-art characterization techniques. This will allow us to explore the fundamental physics underlying the emergent phenomena only seen in materials prepared under extreme conditions. Our ultimate goal is to address one of the grand challenges of materials science: how do complex phenomena emerge from simple ingredients? The proposed project will also spearhead a unique opportunity to train “new breed” scientists, co-advised by experts at both LSU and U. S. Department of Energy National Laboratories. They will be essential for expanding materials physics research with ability to grow crystals, characterize their properties, and design new materials -- an imperative skill that is scarce in the U. S. scientific community.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Chemical Vapor Deposition of Cubic Boron Nitride

This project explored chemical vapor deposition as a technique to synthesis cubic boron nitride (c-BN) for electronics and coating applications. Current c-BN synthesis techniques are greatly limiting due to requiring high pressure or non-equilibrium energy sources, such as ion bombardment.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Developing a high-speed terahertz imaging system based on parametric upconversion imaging for penetrative sensing

Imaging using THz waves has been a promising option for penetrative measurements in environments that are opaque to visible wavelengths. However, available THz imaging systems have been limited to relatively low frame rates and cannot be applied to study fast dynamics. This work explores the use of upconversion imaging techniques based on nonlinear optics to enable wavelength-flexible high frame rate THz imaging. UpConversion Imaging (UCI) uses nonlinear conversion techniques to shift the THz wavelengths carrying a target image to shorter visible or near-IR wavelengths that can be detected by available high-speed cameras. This report describes the analysis methodology used to design a prototype high-rate THz UCI system and gives a detailed explanations of the design choices that were made. The design uses a high-rate pulse-burst laser system to pump both THz generation and THz upconversion detection, allowing for scaling to acquisition rates in excess of 10 kHz. The design of the prototype system described in this report has been completed and all necessary materials have been procured. Assembly and characterization testing is on-going at the submission of this report. This report proposes future directions for work on high-rate THz UCI and potential applications of future systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

ALP Experiment Sensitivity Exploration (Preliminary Findings)

This report presents an exploration of sensitivity estimates for multiple prominent proposed techniques to search for axion-like particles (ALPs). The sensitivities are plotted over particle mass ($m_a$) and coupling ($g_{aγγ}$) parameter space. Explorations include variation over detector type, integration time, background cosmology, and size of the apparatus.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)

Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.

58 GEOSCIENCES↗

DOE OSTI2024

Qutrit Circuits and Algebraic Relations: A Pathway to Efficient Spin-1 Hamiltonian Simulation

Quantum information processing has witnessed significant advancements through the application of qubit- based techniques within universal gate sets. Recently, exploration beyond the qubit paradigm to d-dimensional quantum units or qudits has opened new avenues for improving computational efficiency. This paper delves into the qudit-based approach, particularly addressing the challenges presented in the high-fidelity implementation of qudit-based circuits due to increased complexity. As an innovative approach towards enhancing qudit circuit fidelity, we explore algebraic relations, such as the Yang-Baxter-like turnover equation, which may enable circuit compression and optimization. The paper introduces the turnover relation for the three-qutrit time propagator and its potential use in reducing circuit depth. We further investigate whether this relation can be generalized for higher-dimensional quantum circuits, including a focused study on the one-dimensional spin-1 Heisenberg model. Our paper outlines both rigorous and numerically efficient approaches to potentially achieve this generalization, providing a foundation for further explorations in the field of qudit-based quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Spin-Polarized Electron Sources Based on Group II-VI Compounds Grown by Atomic Layer Deposition

This project explored ALD as an alternative growth technique for II–VI photocathodes and assessed CdTe for spin-polarized electron production. Working with BNL (Cultrera group), we established the workflow to measure QE and spin polarization using BNL’s Mott polarimeter, and we prepared both conventional Cs/O NEA activation and a heterostructure NEA route leveraging an ultrathin Cs2Te overlayer. The latter provides a pragmatic activation alternative while maintaining photoexcitation primarily in CdTe.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Accelerating Discovery of Atomistic Defects via Machine Learning

The quantification of defects such as vacancies in crystalline structures is a cornerstone of materials science research. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within a crystalline lattice, aiming to expedite detection while improving accuracy. Additionally, we explore the transferability of these ML techniques, identifying characteristics of atomistic imaging data that complicate this task. We show how the integration of ML can drive innovation, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗

DOE OSTI2025

Applications of Federated Learning in Semiconductor Manufacturing [Poster]

As semiconductor manufacturers explore advanced data analytics and modeling techniques and data hungry machine learning models increase in popularity due to their accuracy in solving generalized problems and ability to learn complex relationships, federated learning emerges as a privacy preserving machine learning technique for preserving data privacy and ensuring intellectual property protection. Federated Learning is a machine learning technique focused on training models using distributed data that never needs to be centrally stored, allowing the use of advanced machine learning techniques without compromising data privacy, and in the semiconductor manufacturing industry advanced machine learning techniques can reduce cost and time, but maintaining data privacy is essential to maintaining a competitive advantage. This paper systematically reviews existing literature on applications of federated learning in the semiconductor manufacturing industry with a focus on identifying common themes, algorithms, and gaps within the literature to drive future research directions. The findings reveal five key themes, including improvements in quality assurance, virtual models, privacy preservation, reliable data practices, and emerging trends and developments. By identifying key themes in literature on federated learning and semiconductor manufacturing and analyzing gaps and discussed methodologies, this study highlights several potential future research directions to expand the application of federated learning techniques in the semiconductor manufacturing domain.

42 ENGINEERING↗