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DOE OSTI2023

Inferring colloidal interaction from scattering by machine learning

A machine learning solution for the potential inversion problem in elastic scattering is outlined. The inversion scheme consists of two major components, a generative network featuring a variational autoencoder which extracts the targeted static two-point correlation functions from experimentally measured scattering cross sections, and a Gaussian process framework which probabilistically infers the relevant structural parameters from the inverted correlation functions. Via a case study of charged colloidal suspensions, the feasibility of this approach for quantitative study of molecular interaction is critically benchmarked and its merit over existing deterministic approaches, in terms of numerical accuracy and computationally efficiency, is demonstrated.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Short-term solar radiation forecast using total sky imager via transfer learning

Ground-based sky cameras, which capture hemispherical images, have been extensively used for localized monitoring of clouds. This paper proposes a short-term forecasting approach based on transfer learning using Total Sky-Imager (TSI) images of the Southern Great Plains (SGP) site obtained from the Atmospheric Radiation Measurement (ARM) dataset. An accurate estimation of solar irradiance using TSI is key for short-term solar energy generation forecasting and optimal energy consumption planning. We make use of deep neural network architectures such as AlexNet and ResNet-101 to extract the underlying deep convolution features from TSI images and then train using an ensemble learning approach to model and forecast solar radiation. We demonstrate the performance of the proposed approach by showcasing the best and worst cases. Thus, the transfer learning approach significantly reduces the time and resources required for modeling solar radiation. We outperform with reference to another state-of-art technique for solar modeling using TSI images at different forecast lead times.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Neptune long-lived atmospheric features in 2013–2015 from small (28-cm) to large (10-m) telescopes

Since 2013, observations of Neptune with small telescopes (28–50 cm) have resulted in several detections of long-lived bright atmospheric features that have also been observed by large telescopes such as Keck II or Hubble. The combination of both types of images allows the study of the long-term evolution of major cloud systems in the planet. In 2013 and 2014 two bright features were present on the planet at southern mid-latitudes. These may have merged in late 2014, possibly leading to the formation of a single bright feature observed during 2015 at the same latitude. This cloud system was first observed in January 2015 and nearly continuously from July to December 2015 in observations with telescopes in the 2-10-m class and in images from amateur astronomers. These images show the bright spot as a compact feature at -40.1 ± 1.6° planetographic latitude well resolved from a nearby bright zonal band that extended from -42° to -20°. The size of this system depends on wavelength and varies from a longitudinal extension of 8000 ± 900 km and latitudinal extension of 6500 ± 900 km in Keck II images in H and Ks bands to 5100 ± 1400 km in longitude and 4500 ± 1400 km in latitude in HST images in 657 nm. Over July to September 2015 the structure drifted westward in longitude at a rate of 24.48 ± 0.03°/day or -94 ± 3 m/s. This is about 30 m/s slower than the zonal winds measured at the time of the Voyager 2 flyby. Tracking its motion from July to November 2015 suggests a longitudinal oscillation of 16° in amplitude with a 90-day period, typical of dark spots on Neptune and similar to the Great Red Spot oscillation in Jupiter. The limited time covered by high-resolution observations only covers one full oscillation and other interpretations of the changing motions could be possible. HST images in September 2015 show the presence of a dark spot at short wavelengths located in the southern flank (planetographic latitude -47.0°) of the bright compact cloud observed throughout 2015. The drift rate of the bright cloud and dark spot translates to a zonal speed of -87.0 ± 2.0 m/s, which matches the Voyager 2 zonal speeds at the latitude of the dark spot. Identification of a few other features in 2015 enabled the extraction of some limited wind information over this period. This work demonstrates the need of frequently monitoring Neptune to understand its atmospheric dynamics and shows excellent opportunities for professional and amateur collaborations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Effects of build orientation and heat treatment on the evolution of microstructure and mechanical properties of alloy Mar-M-509 fabricated via laser powder bed fusion

We present the main results from an experimental investigation into the consequences of various microstructural features, created by laser powder bed fusion (LPBF) and subsequent heat treatments (HTs), in alloy Mar-M-509 on several aspects of plastic deformation including mechanical anisotropy and elongation-to-fracture (ETF). To ensure successful manufacturing of the alloy, porosity fraction and distribution are first characterized using micro X-ray computed tomography. Next, grain structure, crystallographic texture, and regions of recrystallization in the studied microstructures are measured using electron backscattered diffraction (EBSD). Lastly, chemistry, distribution, and morphological features of carbide phases are extracted using electron microscopy and X-ray diffraction. Strength in tension and compression are measured at room temperature for different initial microstructures created by variations in manufacturing conditions and sample orientations with respect to sample processing frame. While the strength of the alloy varies with sample orientation by approximately 30% in the as-built condition, the alloy is softer, more ductile, and approximately isotropic after HT. These results are discussed and critically compared with the data reported for the as-cast material. The alloy manufactured via LPBF is found to be significantly stronger and more ductile than the same alloy produced by casting. The interesting deformation behavior characteristics of the samples in different conditions are explained in terms of their microstructures. EBSD measurements reveal evolution from columnar grains along the build direction favoring a moderately strong <001> fiber texture in the as-built material to equiaxed grains favoring the {110}<001> Goss texture component after subsequent HTs. The major change in grain structure and texture is a result of recrystallization. While carbide phases precipitate primarily at dendrite and cellular interfaces in the as-built material, these phases are both intra-and inter-granular within the HT materials and coarsen with HT duration. These microstructural observations formed bases to rationalize the observed mechanical behavior of the alloy. With this being said, tailoring the alloy performance characteristics with HTs is reported on.

36 MATERIALS SCIENCE↗

DOE OSTI2018

A Deep Look Into the Future of Quantitative Imaging in Oncology: A Statement of Working Principles and Proposal for Change

The adoption of enterprise digital imaging, along with the development of quantitative imaging methods and the re-emergence of statistical learning, has opened the opportunity for more personalized cancer treatments through transformative data science research. In the last 5 years, accumulating evidence has indicated that noninvasive advanced imaging analytics (i.e., radiomics) can reveal key components of tumor phenotype for multiple lesions at multiple time points over the course of treatment. Many groups using homegrown software have extracted engineered and deep quantitative features on 3-dimensional medical images for better spatial and longitudinal understanding of tumor biology and for the prediction of diverse outcomes. These developments could augment patient stratification and prognostication, buttressing emerging targeted therapeutic approaches. Unfortunately, the rapid growth in popularity of this immature scientific discipline has resulted in many early publications that miss key information or use underpowered patient data sets, without production of generalizable results. Quantitative imaging research is complex, and key principles should be followed to realize its full potential. The fields of quantitative imaging and radiomics in particular require a renewed focus on optimal study design and reporting practices, standardization, interpretability, data sharing, and clinical trials. Standardization of image acquisition, feature calculation, and statistical analysis (i.e., machine learning) are required for the field to move forward. A new data-sharing paradigm enacted among open and diverse participants (medical institutions, vendors and associations) should be embraced for faster development and comprehensive clinical validation of imaging biomarkers. In this review and critique of the field, we propose working principles and fundamental changes to the current scientific approach, with the goal of high-impact research and development of actionable prediction models that will yield more meaningful applications of precision cancer medicine.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Three-dimensional reconstruction and morphologic characteristics of porous metal fiber sintered sheet

This paper presents an approach to achieve morphological characterizing for complex porous materials based on micro X-ray tomography images, with an example of a novel porous metal fiber sheet produced through solid-state sintering method. The geometrical reconstruction was performed after selection of volume of interest and image processing of anisotropic diffusion smooth. The reconstructed gray level images were then transferred into binary images by adjusting binarization threshold according to the actual porosity. Taking into account the tubular structural feature of the fibers, skeleton extraction algorithm based on the distance transform function was applied and further improved by the scale axis transform method. The skeleton was later pruned and segmented according to the contact points to perform morphological characterizing. Compared with actual manufacturing parameters, the style, length, radius, orientation and tortuosity of fiber segments were discussed. The results show that our proposed method can well describe the actual geometrical and morphological characteristics, which will provide a promising method for the structural description of fibrous networks. - Highlights: • Micro-CT technology was used to achieve the 3D geometrical reconstruction. • Skeleton extraction algorithm was modified to get the medial skeleton. • Skeleton filter operation was adopted to deal with the segmented skeleton. • Useful morphological statistics was obtained through skeleton segments. • Relationship between structure and manufacturing processes was discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Solid-state NMR studies of proteins immobilized on inorganic surfaces

Solid state NMR is the primary tool for studying the quantitative, site-specific structure, orientation, and dynamics of biomineralization proteins under biologically relevant conditions. Two calcium phosphate proteins, statherin and leucine rich amelogenin protein (LRAP), have been studied in depth and have different features, challenging our ability to extract design principles. More recent studies of the significantly larger full-length amelogenin represent a challenging but necessary step to ultimately investigate the full diversity of biomineralization proteins. Interactions of amino acids and silaffin peptide with silica are also being studied, along with qualitative studies of proteins interacting with calcium carbonate. Dipolar recoupling techniques have formed the core of the quantitative studies, yet, the need for isolated spin pairs makes this approach costly and time intensive. The use of multi-dimensional techniques is advancing, methodology which, despite its challenges with these difficult-to-study proteins, will continue to drive future advancements in this area.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Association Between Injection and Microseismicity in Geothermal Fields With Multiple Wells: Data-Driven Modeling of Rotokawa, New Zealand, and Húsmúli, Iceland

Understanding injection-induced microseismicity in geothermal systems can provide insight into reservoir connectedness. However, fault and reservoir complexity are difficult to represent in simple analytical models, which makes it difficult to discern clear relationships from incidental associations. Here, we have used data-driven models to study how fluid injection and microseismicity are related in the Rotokawa (New Zealand) and Hellisheiði (Iceland) geothermal fields. We tested two classes of model: (a) lagged linear regression of seismicity rate as a function of well injection rates; and (b) systematic extraction of injection time series features that are then evaluated for associations with the seismicity. These models allowed us to determine which wells had the greatest correlation with microseismicity and to explain this association in a reservoir context. Finally, exploring different data types and transformations, we were unable to establish a link between rapid changes in injection rate and seismicity spikes, as suggested by some theoretical models.

15 GEOTHERMAL ENERGY↗

DOE OSTI2014

In-stream hydrokinetic power: Review and appraisal

The objective of this paper is to provide a review of in-stream hydrokinetic power, which is defined as electric power generated by devices capturing the energy of naturally flowing water-stream, tidal, or open ocean flows-without impounding the water. North America has significant in-stream energy resources, and hydrokinetic electric power technologies to harness those resources have the potential to make a significant contribution to U.S. electricity needs by adding as much as 120 TWh/year from rivers alone to the present hydroelectric power generation capacity. Additionally, tidal and ocean current resources in the U.S. respectively contain 438 TWh/year and 163 TWh/year of extractable power. Among their attractive features, in-stream hydrokinetic operations do not contribute to greenhouse gas emissions or other air pollution and have less visual impact than wind turbines. Since these systems do no utilize dams the way traditional hydropower systems typically do, their impact on the environment will differ, and a small but growing number of studies support conclusions regarding those impacts. Furthermore, potential environmental impacts include altered water quality, altered sediment deposition, altered habitats, direct impact on biota, and navigability of waterways.

13 HYDRO ENERGY↗

DOE OSTI2016

Theoretical investigation of carrier transfer by an optical contacting scheme for optoelectronic application

As a promising charge carrier transfer scheme, optical coupling could potentially improve the performance of an optoelectronic device for energy harvesting based on well developed nanotechnology. By extracting carriers optically, the functional features of the nano-structured material could be better used by minimizing the concerns about its electrical properties. In this paper, we present a rigorous electromagnetic model to analyze the optical carrier transfer problem. The flow of the energy is analyzed carefully by the photon transfer spectrum, and the photon emitters (electron-hole pairs) are assumed in a thermal equilibrium described by Bose-Einstein distribution. The result shows that an energy selective carrier transfer can be optically achieved at the device level by integrating the emitter and receiver into a nano-optical resonator, where both the photon emission and absorption are significantly amplified by a near-field coupling around the resonant frequency. General design and optimization schemes in practice are addressed by examining the influence of the photonic design and an energy dependent emissivity of the emitter, which can be used to develop the optical contacting concept further.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Transient vibration and product formation of photoexcited CS 2 measured by time-resolved x-ray scattering

Here, we have observed details of the internal motion and dissociation channels in photoexcited carbon disulfide (CS 2 ) using time-resolved x-ray scattering (TRXS). Photoexcitation of gas-phase CS 2 with a 200 nm laser pulse launches oscillatory bending and stretching motion, leading to dissociation of atomic sulfur in under a picosecond. During the first 300 fs following excitation, we observe significant changes in the vibrational frequency as well as some dissociation of the C–S bond, leading to atomic sulfur in the both 1 D and 3 P states. Beyond 1400 fs, the dissociation is consistent with primarily 3 P atomic sulfur dissociation. This channel-resolved measurement of the dissociation time is based on our analysis of the time-windowed dissociation radial velocity distribution, which is measured using the temporal Fourier transform of the TRXS data aided by a Hough transform that extracts the slopes of linear features in an image. The relative strength of the two dissociation channels reflects both their branching ratio and differences in the spread of their dissociation times. Measuring the time-resolved dissociation radial velocity distribution aids the resolution of discrepancies between models for dissociation proposed by prior photoelectron spectroscopy work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Development of an ultrafast wide-field microscope for single-shot laser-driven shock and ablation studies

We build an ultrafast wide-field microscope that captures single-shot events at near-optical diffraction limit for time-resolved studies of ablation and shock compression. Here, we provide insights on how the imaging and spectroscopic modalities of our single-shot microscope are impacted by the depth of field of a microscope objective. At high spatial resolution, the depth of field can critically impede these experiments and novel strategies must be implemented to acquire high-quality optical micrographs at high throughput. Here, we highlight how custom lithography-prepared samples enable us to rectify optical artifacts that arise during sample motion. With a complete knowledge of how the mechanical and optical components couple together, we can then extract critical spatial and temporal features of our ablation and shock compression experiments. For example, during the ablation processes, we show that shock waves created in metal thin films form Newton’s interference rings, whose evolution can be recorded with picosecond temporal resolution and at near optical diffraction-limit resolution.

Ultrafast microscopy↗

DOE OSTI2020

Unraveling intrinsic correlation effects with angle-resolved photoemission spectroscopy

Interaction effects can change materials properties in intriguing ways, and they have, in general, a huge impact on electronic spectra. In particular, satellites in photoemission spectra are pure many-body effects, and their study is of increasing interest in both experiment and theory. However, the intrinsic spectral function is only a part of a measured spectrum, and it is notoriously difficult to extract this information, even for simple metals. Our joint experimental and theoretical study of the prototypical simple metal aluminum demonstrates how intrinsic satellite spectra can be extracted from measured data using angular resolution in photoemission. A nondispersing satellite is detected and explained by electron–electron interactions and the thermal motion of the atoms. Additional nondispersing intensity comes from the inelastic scattering of the outgoing photoelectron. The ideal intrinsic spectral function, instead, has satellites that disperse both in energy and in shape. Theory and the information extracted from experiment describe these features with very good agreement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Cosmological imprints of frozen-in light sterile neutrinos

We investigate observable cosmological aspects of sterile neutrino dark matter produced via the freeze-in mechanism. The study is performed in a framework that admits many cosmologically interesting variations: high temperature production via annihilation processes from higher dimensional operators or low temperature production from decays of a scalar, with the decaying scalar in or out of equilibrium with the thermal bath, in supersymmetric or non-supersymmetric setups, thus allowing us to both extract generic properties and highlight features unique to particular variations. We find that while such sterile neutrinos are generally compatible with all cosmological constraints, interesting scenarios can arise where dark matter is cold, warm, or hot, has nontrivial momentum distributions, or provides contributions to the effective number of relativistic degrees of freedom N {sub eff} during Big Bang nucleosynthesis large enough to be probed by future measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

KG-Hub—building and exchanging biological knowledge graphs

Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract–transform–load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial–environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Contrastive learning for robust representations of neutrino data

In neutrino physics, analyses often depend on large simulated datasets, making it essential for models to generalize effectively to real-world detector data. Contrastive learning, a well-established technique in deep learning, offers a promising solution to this challenge. By applying controlled data augmentations to simulated data, contrastive learning enables the extraction of robust and transferable features. This improves the ability of models trained on simulations to adapt to real experimental data distributions. In this paper, we investigate the application of contrastive learning methods in the context of neutrino physics. Through a combination of empirical evaluations and theoretical insights, we demonstrate how contrastive learning enhances model performance and adaptability. Additionally, we compare it to other domain adaptation techniques, highlighting the unique advantages of contrastive learning for this field. Published by the American Physical Society 2025

Wilkinson, Alex (ORCID:0000000253404506)↗

DOE OSTI2021

The effect of longer-range waviness on X-ray reflectivity measurements

A model for calculating the X-ray reflectivity (XRR) of surfaces to extract both roughness and waviness features is presented. Expressions of reflectivity intensity are derived as a function of root-mean-square (RMS) roughness σ, RMS waviness σ L , and the cut-off frequency between the features ω 0 . Experiments were conducted at the Advanced Light Source at Lawrence Berkeley National Laboratory, beamline 8.3.2, on BK7 glass manufactured with a multi-step polishing process to validate the model, and were compared with atomic force microscopy (AFM), Fizeau interferometry and surface profilometry measurements. Here, the parameter results and their deviations for XRR measurements were σ = 2.9 ± 0.2 nm and σ L = 14.6 ± 0.5 nm with a wavelength cut-off of 1/(18 ± 2) µm –1 , while the results from the AFM, Fizeau and profilometry measurements were σ AFM = 3.4 ± 0.4 nm, σ L,Fizeau = 21.6 nm, σ prof = 4.0 ± 0.1 nm, and σ L,prof = 21.4 ± 0.1 nm with cut-offs for the profilometry and Fizeau measurements limited to frequencies of (1/16) µm –1 to (1/4) mm –1 .

42 ENGINEERING↗

DOE OSTI2024

Localized Evaluation for Constructing Discrete Vector Fields

Topological abstractions offer a method to summarize the behavior of vector fields, but computing them robustly can be challenging due to numerical precision issues. One alternative is to represent the vector field using a discrete approach, which constructs a collection of pairs of simplices in the input mesh that satisfies criteria introduced by Forman's discrete Morse theory. While numerous approaches exist to compute pairs in the restricted case of the gradient of a scalar field, state-of-the-art algorithms for the general case of vector fields require expensive optimization procedures. This paper introduces a fast, novel approach for pairing simplices of two-dimensional, triangulated vector fields that do not vary in time. The key insight of our approach is that we can employ a local evaluation, inspired by the approach used to construct a discrete gradient field, where every simplex in a mesh is considered by no more than one of its vertices. Specifically, we observe that for any edge in the input mesh, we can uniquely assign an outward direction of flow. We can further expand this consistent notion of outward flow at each vertex, which corresponds to the concept of a downhill flow in the case of scalar fields. Working with outward flow enables a linear-time algorithm that processes the (outward) neighborhoods of each vertex one-by-one, similar to the approach used for scalar fields. Here, we couple our approach to constructing discrete vector fields with a method to extract, simplify, and visualize topological features. Empirical results on analytic and simulation data demonstrate drastic improvements in running time, produce features similar to the current state-of-the-art, and show the application of simplification to large, complex flows.

97 MATHEMATICS AND COMPUTING↗