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DOE OSTI2024

Navigating phase diagram complexity to guide robotic inorganic materials synthesis

Abstract Efficient synthesis recipes are needed to streamline the manufacturing of complex materials and to accelerate the realization of theoretically predicted materials. Often, the solid-state synthesis of multicomponent oxides is impeded by undesired by-product phases, which can kinetically trap reactions in an incomplete non-equilibrium state. Here we report a thermodynamic strategy to navigate high-dimensional phase diagrams in search of precursors that circumvent low-energy, competing by-products, while maximizing the reaction energy to drive fast phase transformation kinetics. Using a robotic inorganic materials synthesis laboratory, we perform a large-scale experimental validation of our precursor selection principles. For a set of 35 target quaternary oxides, with chemistries representative of intercalation battery cathodes and solid-state electrolytes, our robot performs 224 reactions spanning 27 elements with 28 unique precursors, operated by 1 human experimentalist. Our predicted precursors frequently yield target materials with higher phase purity than traditional precursors. Robotic laboratories offer an exciting platform for data-driven experimental synthesis science, from which we can develop fundamental insights to guide both human and robotic chemists.

Chen, Jiadong (ORCID:0009000476038838)↗

DOE OSTI2015

3D model generation using an airborne swarm

Using an artificial kinematic field to provide co-ordination between multiple inspection UAVs, the authors herein demonstrate full 3D modelling capability based on a photogrammetric system. The operation of the system is demonstrated by generating a full 3D surface model of an intermediate level nuclear waste storage drum. Such drums require periodic inspection to ensure that drum distortion or corrosion is carefully monitored. Performing this inspection with multiple airborne platforms enables rapid inspection of structures that are inaccessible to on-surface remote vehicles and are in human-hazardous environments. A three-dimensional surface-meshed model of the target can then be constructed in post-processing through photogrammetry analysis of the visual inspection data. The inspection environment uses a tracking system to precisely monitor the position of each aerial vehicle within the enclosure. The vehicles used are commercially available Parrot AR. Drone quadcopters, controlled through a computer interface connected over an IEEE 802.11n (WiFi) network, implementing a distributed controller for each vehicle. This enables the autonomous and distributed elements of the control scheme to be retained, while alleviating the vehicles of the control algorithm’s computational load. The control scheme relies on a kinematic field defined with the target at its centre. This field defines the trajectory for all the drones in the volume relative to the central target, enabling the drones to circle the target at a set radius while avoiding drone collisions. This function enables complete coverage along the height of the object, which is assured by transitioning to another inspection band only after completing circumferential coverage. Using a swarm of vehicles, the time until complete coverage can be significantly reduced.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Imaging redshift estimates for Fermi BL Lac objects

We have obtained WIYN and SOAR i' images of BL Lacertae objects and used these to detect or constrain the flux of the host galaxy. Under common standard candle assumptions, these data provide estimates of, or lower bounds on, the redshift. Our targets are a set of flat-spectrum radio counterparts of high flux Fermi Large Area Telescope sources, with sensitive spectral observations showing them to be continuum-dominated BL Lac objects. In this sample, 5 of 11 BL Lac objects yielded significant host detections, with standard candle redshifts z = 0.13-0.58. Our estimates and lower bounds are generally in agreement with other redshifts estimates, although our z = 0.374 estimate for J0543–5532 implies a significantly sub-luminous host.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Casting a wide signal net with future direct dark matter detection experiments

As dark matter (DM) direct detection experiments continue to improve their sensitivity they will inevitably encounter an irreducible background arising from coherent neutrino scattering. This so-called "neutrino floor" may significantly reduce the sensitivity of an experiment to DM-nuclei interactions, particularly if the recoil spectrum of the neutrino background is approximately degenerate with the DM signal. This occurs for the conventionally considered spin-independent (SI) or spin-dependent (SD) interactions. In such case, an increase in the experiment's exposure by multiple orders of magnitude may not yield any significant increase in sensitivity. The typically considered SI and SD interactions, however, do not adequately reflect the whole landscape of the well-motivated DM models, which includes other interactions. Since particle DM has not been detected yet in laboratories, it is essential to understand and maximize the detection capabilities for a broad variety of possible models and signatures. Here, we investigate the impact of the background arising from various neutrino sources on the discovery potential of a DM signal for a large class of viable DM-nucleus interactions and several potential futuristic experimental settings, with different target elements. For some momentum suppressed cross sections, large DM particle masses and heavier targets, we find that there is no suppression of the discovery limits due to neutrino backgrounds. Further, we explicitly demonstrate that inelastic scattering, which could appear in models with multicomponent dark sectors, would help to lift the signal degeneracy associated with the neutrino floor. This research could assist with mapping out the optimal DM detection strategy for the next generation of experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Probe microscopy is all you need *

We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods. Indeed, the tremendous progress achieved by machine learning (ML) and artificial intelligence over the last decade has been largely achieved via the utilization of static data sets, from the paradigmatic MNIST to the bespoke corpora of text and image data used to train large models such as GPT3, DALL·E and others. However, it is now recognized that continuous, minute improvements to state-of-the-art do not necessarily translate to advances in real-world applications. We argue that a promising pathway for the development of ML methods is via the route of domain-specific deployable algorithms in areas such as electron and scanning probe microscopy and chemical imaging. This will benefit both fundamental physical studies and serve as a test bed for more complex autonomous systems such as robotics and manufacturing. Favorable environment characteristics of scanning and electron microscopy include low risk, extensive availability of domain-specific priors and rewards, relatively small effects of exogenous variables, and often the presence of both upstream first principles as well as downstream learnable physical models for both statics and dynamics. Recent developments in programmable interfaces, edge computing, and access to application programming interfaces (APIs) facilitating microscope control, all render the deployment of ML codes on operational microscopes straightforward. We discuss these considerations and hope that these arguments will lead to create novel set of development targets for the ML community by accelerating both real world ML applications and scientific progress.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

First Search for Axion Dark Matter with a MADMAX Prototype

This Letter presents the first search for dark matter axions with mass in the ranges 76.56 to 76.82 μ⁢eV and 79.31 to 79.53 μ⁢eV using a prototype setup for the MAgnetized Disk and Mirror Axion eXperiment (MADMAX). The experimental setup employs a dielectric haloscope consisting of three sapphire disks and a mirror to resonantly enhance the axion-induced microwave signal within the magnetic dipole field provided by the 1.6 T Morpurgo magnet at CERN. Over 14.5 days of data collection, no axion signal was detected. A 95% CL upper limit on the axion-photon coupling strength down to |𝑔 𝑎⁢𝛾 |∼2×10 −11 GeV −1 is set in the targeted mass ranges, surpassing previous constraints, assuming a local axion dark matter density 𝜌 𝑎 of 0.3 GeV/cm 3 . This study marks the first axion dark matter search using a dielectric haloscope.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Search for physics beyond the standard model in events with overlapping photons and jets

Results are reported from a search for new particles that decay into a photon and two gluons, in events with jets. Novel jet substructure techniques are developed that allow photons to be identified in an environment densely populated with hadrons. The analyzed proton-proton collision data were collected by the CMS experiment at the LHC, in 2016 at $ \sqrt{s}$ = 13 TeV, and correspond to an integrated luminosity of 35.9 fb -1 . The spectra of total transverse hadronic energy of candidate events are examined for deviations from the standard model predictions. No statistically significant excess is observed over the expected background. The first cross section limits on new physics processes resulting in such events are set. The results are interpreted as upper limits on the rate of gluino pair production, utilizing a simplified stealth supersymmetry model. The excluded gluino masses extend up to 1.7 TeV, for a neutralino mass of 200 GeV and exceed previous mass constraints set by analyses targeting events with isolated photons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

Towards Resiliency Evaluation of Vector Programs

The systems resilience research community has developed methods to manually insert additional source-program level assertions to trap errors, and also devised tools to conduct fault injection studies for scalar program codes. In this work, we contribute the first vector oriented LLVM-level fault injector VULFI to help study the effects of faults in vector architectures that are of growing importance, especially for vectorizing loops. Using VULFI, we conduct a resiliency study of nine real-world vector benchmarks using Intel’s AVX and SSE extensions as the target vector instruction sets, and offer the first reported understanding of how faults affect vector instruction sets. We take this work further toward automating the insertion of resilience assertions during compilation. This is based on our observation that during intermediate (e.g., LLVM-level) code generation to handle full and partial vectorization, modern compilers exploit (and explicate in their code-documentation) critical invariants. These invariants are turned into error-checking code. We confirm the efficacy of these automatically inserted low-overhead error detectors for vectorized for-loops.

fault injection↗

DOE OSTI2015

Guest Editorial Electric Machines in Renewable Energy Applications

The main objective of this special issue is to collect and disseminate publications that highlight recent advances and breakthroughs in the area of renewable energy resources. The use of these resources for production of electricity is increasing rapidly worldwide. As of 2015, a majority of countries have set renewable electricity targets in the 10%-40% range to be achieved by 2020-2030, with a few notable exceptions aiming for 100% generation by renewables. We are experiencing a truly unprecedented transition away from fossil fuels, driven by environmental, energy security, and socio-economic factors.Electric machines can be found in a wide range of renewable energy applications, such as wind turbines, hydropower and hydrokinetic systems, flywheel energy storage devices, and low-power energy harvesting systems. Hence, the design of reliable, efficient, cost-effective, and controllable electric machines is crucial in enabling even higher penetrations of renewable energy systems in the smart grid of the future. In addition, power electronic converter design and control is critical, as they provide essential controllability, flexibility, grid interface, and integration functions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Eelgrass (Zostera marina L.) Restoration in Puget Sound: Development of a Site Suitability Assessment Process

The restoration of eelgrass (Zostera marina L.), a critical ecosystem component and ‘vital sign’ indicator of ecosystem health, is a high priority in Puget Sound, Washington, United States. In 2011, the state set a restoration target to increase eelgrass area by 4,200 ha, a 20%) increase over the present 21,500 ha by 2020. In a region as large and complex as Puget Sound, locating areas to restore eelgrass effectively and efficiently is challenging. We developed a modeling and screening process to identify and test potential restoration sites. The spatially explicit analysis of habitat suitability incorporated information from predictive models of hydrodynamics and eelgrass biomass, shoreline manager input, historical and current eelgrass area, substrate, stressors, test plantings, and monitoring of light, temperature, and survival. We evaluated 2,630 sites from which we identified 6,292 ha of highly to very highly suitable conditions for potential eelgrass habitat, which provides ample area for restoring eelgrass to meet the 20% target. Test plantings were successful at four of nine areas, and indicated significant site-specific data needs to improve predictive capability. We summarized the results of our analysis on maps of habitat suitability for the majority of the ~3,220 km of shoreline in Puget Sound, which serve as a starting point for restoration site selection and planning. Overall, our approach provides a foundation for identifying and testing potential restoration sites, and highlights information needs and potential management actions to reduce stressors and increase eelgrass cover to meet the challenging restoration goal.

eelgrass model, Puget Sound, restoration sites, Zo↗

DOE OSTI2020

Infrared spectroscopic method for uranium isotopic analysis

A high performance infrared (HPIR) system was developed and demonstrated for the infrared absorption analysis of {sup 235}U and {sup 238}U isotopes in uranium hexafluoride gas samples. Sweeping the quantum cascade laser light source over the spectral range and sampling via a high-rate analog-to-digital converter provided 0.0005 cm-1 spectral resolution, which allowed for high-precision measurements of the isotopic peak shift. A data analysis method was developed using principal component analysis to predict the isotope weight % content of {sup 235}U. The HPIR precision, accuracy, and error were evaluated for a wide range of isotopic ratio samples (0.287 – 93.7 weight % {sup 235}U), and the results were compared to the International Target Values (ITVS) set forth by the International Atomic Energy Agency (IAEA) for non-destructive and destructive analytical techniques. The method meets or surpasses the IAEA ITVs for non-destructive analysis of samples with isotopic content of depleted to highly enriched. The results also demonstrated the capability of the HPIR system to correctly predict the {sup 235}U weight % content of a mislabeled sample whose isotopic distribution was validated by mass spectroscopic measurements. The HPIR measurement is nondestructive and, thus, allows for confirmatory analyses of the exact sample at a designated IAEA lab if higher-resolution or a certified analysis is needed. (author)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2014

SU-E-T-157: Evaluation and Comparison of Doses to Pelvic Lymph Nodes and to Point B with 3D Image Guided Treatment Planning for High Dose Brachytherapy for Treatment of Cervical Cancer

Purpose: To estimate and compare the doses received by the obturator, external and internal iliac lymph nodes and point Methods: CT-MR fused image sets of 15 patients obtained for each of 5 fractions of HDR brachytherapy using tandem and ring applicator, were used to generate treatment plans optimized to deliver a prescription dose to HRCTV-D90 and to minimize the doses to organs at risk (OARs). For each set of image, target volume (GTV, HRCTV) OARs (Bladder, Rectum, Sigmoid), and both left and right pelvic lymph nodes (obturator, external and internal iliac lymph nodes) were delineated. Dose-volume histograms (DVH) were generated for pelvic nodal groups (left and right obturator group, internal and external iliac chains) Per fraction DVH parameters used for dose comparison included dose to 100% volume (D100), and dose received by 2cc (D2cc), 1cc (D1cc) and 0.1 cc (D0.1cc) of nodal volume. Dose to point B was compared with each DVH parameter using 2 sided t-test. Pearson correlation were determined to examine relationship of point B dose with nodal DVH parameters. Results: FIGO clinical stage varied from 1B1 to IIIB. The median pretreatment tumor diameter measured on MRI was 4.5 cm (2.7– 6.4cm).The median dose to bilateral point B was 1.20 Gy ± 0.12 or 20% of the prescription dose. The correlation coefficients were all <0.60 for all nodal DVH parameters indicating low degree of correlation. Only 2 cc of obturator nodes was not significantly different from point B dose on t-test. Conclusion: Dose to point B does not adequately represent the dose to any specific pelvic nodal group. When using image guided 3D dose-volume optimized treatment nodal groups should be individually identified and delineated to obtain the doses received by pelvic nodes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Current Challenges in Commercially Producing Biofuels from Lignocellulosic Biomass

Biofuels that are produced from biobased materials are a good alternative to petroleum based fuels. They offer several benefits to society and the environment. Producing second generation biofuels is even more challenging than producing first generation biofuels due the complexity of the biomass and issues related to producing, harvesting, and transporting less dense biomass to centralized biorefineries. In addition to this logistic challenge, other challenges with respect to processing steps in converting biomass to liquid transportation fuel like pretreatment, hydrolysis, microbial fermentation, and fuel separation still exist and are discussed in this review. The possible coproducts that could be produced in the biorefinery and their importance to reduce the processing cost of biofuel are discussed. About $1 billion was spent in the year 2012 by the government agencies in US to meet the mandate to replace 30% existing liquid transportation fuels by 2022 which is 36 billion gallons/year. Other countries in the world have set their own targets to replace petroleum fuel by biofuels. Because of the challenges listed in this review and lack of government policies to create the demand for biofuels, it may take more time for the lignocellulosic biofuels to hit the market place than previously projected.

09 BIOMASS FUELS↗

DOE OSTI2021

Building Performance Database API (BPD API) v2.1

The Building Performance Database (BPD) is the largest publicly-available source of measured energy performance data for buildings in the United States. It contains information about the building's energy use, location, and physical and operational characteristics. The BPD can be used by building owners, operators, architects and engineers to compare a building's energy efficiency against customized peer groups, identify energy efficiency opportunities, and set energy efficiency targets. It can also be used by energy efficiency program implementers and policymakers to analyze energy efficiency features and trends in the building stock. The BPD compiles data from various data sources, converts it into a standard format, cleanses and quality checks the data, and provides users with access to the data in a way that maintains anonymity for data providers. This software is the database and the Application Programming Interface (API). Users can utilize the BPD's data to develop their own applications using the API. Version 2.1 included a major update for multiple years of data and refactoring of code for faster queries.

Mathew, Paul↗

DOE OSTI2021

Too Good to Be True? Evaluation of Colonoscopy Sensitivity Assumptions Used in Policy Models

Background: Models can help guide colorectal cancer screening policy. Although models are carefully calibrated and validated, there is less scrutiny of assumptions about test performance. Methods: We examined the validity of the CRC-SPIN model and colonoscopy sensitivity assumptions. Standard sensitivity assumptions, consistent with published decision analyses, assume sensitivity equal to 0.75 for diminutive adenomas (<6 mm), 0.85 for small adenomas (6–10 mm), 0.95 for large adenomas (≥10 mm), and 0.95 for preclinical cancer. We also selected adenoma sensitivity that resulted in more accurate predictions. Targets were drawn from the Wheat Bran Fiber study. In the study, we examined how well the model predicted outcomes measured over a three-year follow-up period, including the number of adenomas detected, the size of the largest adenoma detected, and incident colorectal cancer. Results: Using standard sensitivity assumptions, the model predicted adenoma prevalence that was too low (42.5% versus 48.9% observed, with 95% confidence interval 45.3%–50.7%) and detection of too few large adenomas (5.1% versus 14.% observed, with 95% confidence interval 11.8%–17.4%). Predictions were close to targets when we set sensitivities to 0.20 for diminutive adenomas, 0.60 for small adenomas, 0.80 for 10- to 20-mm adenomas, and 0.98 for adenomas 20 mm and larger. Conclusions: Colonoscopy may be less accurate than currently assumed, especially for diminutive adenomas. Alternatively, the CRC-SPIN model may not accurately simulate onset and progression of adenomas in higher-risk populations. Impact: Misspecification of either colonoscopy sensitivity or disease progression in high-risk populations may affect the predicted effectiveness of colorectal cancer screening. When possible, decision analyses used to inform policy should address these uncertainties.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

The Art and Science of Climate Model Tuning

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling with its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Prior knowledge driven Granger causality analysis on gene regulatory network discovery

Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, the propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Status of the WPEC subgroup 46 - Efficient and effective use of integral experiments for nuclear data validation

The present paper summarizes the current status of the activities of the on-going WPEC subgroup 46 which was the last significant initiative of Massimo before he passed away. The goal of WPEC/SG46 is to define, test and document a methodology to provide unambiguous feedback to the nuclear data evaluator community, based on the joint use of integral experiments and data assimilation techniques. Part of this effort resulted in a renewed analysis of the original Target Accuracy Requirement (TAR) exercise of WPEC/SG26, by adding more diverse nuclear systems and parameters, including reaction channels correlations and a coarser energy group structure; and making use of the progress made in the most recent evaluations in terms of both nuclear data and covariance matrices. The preliminary outcomes of the updated TAR exercise, documented by various groups worldwide are clear already: uncertainty reductions are required for many nuclide-reaction pairs in a variety of energy range if the target uncertainty requirements set by the industry are to be met, especially for k{sub eff}. The inclusion of correlations between the various reaction channels had a major impact on the magnitude of the required uncertainty reduction. Those uncertainty reductions are unlikely to be met by differential measurements alone. However, the selection of relevant integral experiment and a subsequent adjustment procedure may help meet these requirements. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗