Results for “Advanced Workflow” — Page 31

DOE OSTI2024

HTESP (High-throughput electronic structure package): A package for high-throughput ab initio calculations

High-throughput ab initio calculations are the indispensable parts of data-driven discovery of new materials with desirable properties, as reflected in the establishment of several online material databases. The accumulation of extensive theoretical data through computations enables data-driven discovery by constructing machine learning and artificial intelligence models to predict novel compounds and forecast their properties. Efficient usage and extraction of data from these existing online material databases can accelerate the next stage materials discovery that targets different and more advanced properties, such as electron–phonon coupling for phonon-mediated superconductivity. However, extracting data from these databases, generating tailored input files for different ab initio calculations, performing such calculations, and analyzing new results can be demanding tasks. Here, in this work, we introduce a software package named “HTESP” (High-Throughput Electronic Structure Package) written in Python and Bash languages, which automates the entire workflow including data extraction, input file generation, calculation submission, result collection and plotting. Our HTESP will help speed up future computational materials discovery processes.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Discovery, characterization, and application of chromosomal integration sites in the hyperthermophilic archaeon Sulfolobus islandicus

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, in this work, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Turbo‐charging crop improvement: harnessing multiplex editing for polygenic trait engineering and beyond

Multiplex CRISPR editing has emerged as a transformative platform for plant genome engineering, enabling the simultaneous targeting of multiple genes, regulatory elements, or chromosomal regions. This approach is effective for dissecting gene family functions, addressing genetic redundancy, engineering polygenic traits, and accelerating trait stacking and de novo domestication. Its applications now extend beyond standard gene knockouts to include epigenetic and transcriptional regulation, chromosomal engineering, and transgene‐free editing. These capabilities are advancing crop improvement not only in annual species but also in more complex systems such as polyploids, undomesticated wild relatives, and species with long generation times. At the same time, multiplex editing presents technical challenges, including complex construct design and the need for robust, scalable mutation detection. We discuss current toolkits and recent innovations in vector architecture, such as promoter and scaffold engineering, that streamline workflows and enhance editing efficiency. High‐throughput sequencing technologies, including long‐read platforms, are improving the resolution of complex editing outcomes such as structural rearrangements—often missed by standard genotyping—when targeting repetitive or tandemly spaced loci. To fully realize the potential of multiplex genome engineering, there is growing demand for user‐friendly, synthetic biology‐compatible, and scalable computational workflows for gRNA design, construct assembly, and mutation analysis. Experimentally validated inducible or tissue‐specific promoters are also highly desirable for achieving spatiotemporal control. As these tools continue to evolve, multiplex CRISPR editing is poised to become a foundational technology of next‐generation crop improvement to address challenges in agriculture, sustainability, and climate resilience.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S005R001/2477501/urtec-2021-5243-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5243 The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. Furthermore, the workflow and learnings can also be transferred to other unconventional plays.

58 GEOSCIENCES↗

DOE OSTI2021

2019 Computing Sciences Strategic Plan

Computing has transformed nearly every aspect of scientific inquiry — across disciplines and across scales — from the behavior of subatomic particles to the formation of structures in the early universe, from the assembly of the human genome to the evolution of earth systems. Over the past two decades, computing has become an integral part of how Berkeley Lab is “Bringing Science Solutions to the World.” Advances in computing and mathematics have been key, with new mathematical models of complex physical phenomena, new methods for analyzing complex data, new algorithms for accuracy and scaling and sophisticated software systems that encapsulate these techniques into open, reusable tools. The performance of NERSC computers and the ESnet network have grown by several orders of magnitude, along with our understanding of how to map scientific computations and workflows onto these systems. From research to facility operations, the passion, talent and dedication of the Computing Sciences Area staff has been the cornerstone of our success. The plan outlined in this document describes the next step in a journey to expand the influence and impact of our efforts, building an increasingly connected global enterprise for science that places more powerful instruments in the hands of scientists, along with more powerful methods and tools for modeling, analysis and prediction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

MO-B-BRB-00: Three Dimensional Dosimetry

Full three-dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end-to-end dosimetry QA Understand the potential for 3D dosimetry for end-to-end radiation therapy process validation in the in-house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-BRB-01: 3D Dosimetry in the Clinic: Background and Motivation

Full three-dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end-to-end dosimetry QA Understand the potential for 3D dosimetry for end-to-end radiation therapy process validation in the in-house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-BRB-02: 3D Dosimetry in the Clinic: IMRT Technique Validation in Sweden

Full three-dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end-to-end dosimetry QA Understand the potential for 3D dosimetry for end-to-end radiation therapy process validation in the in-house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-BRB-03: 3D Dosimetry in the Clinic: Validating Special Techniques

Full three-dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end-to-end dosimetry QA Understand the potential for 3D dosimetry for end-to-end radiation therapy process validation in the in-house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-BRB-04: 3D Dosimetry in End-To-End Dosimetry QA

Full three-dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end-to-end dosimetry QA Understand the potential for 3D dosimetry for end-to-end radiation therapy process validation in the in-house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

SAGIPS: A scalable Framework for scidac quantom

As part of the Scientific Discovery through Advanced Computing (SciDAC) program, the Quantum Chromodynamics Nuclear Tomography (QuantOM) project aims to analyze data from Deep Inelastic Scattering (DIS) experiments conducted at Thomas Jefferson National Accelerator Facility and the upcoming Electron Ion Collider. The DIS data analysis is performed on an event level by taking into leveraging nuclear theory models and accounting for experimental conditions. In order to efficiently run multiple analyses under varying conditions, a composable workflow was designed where each section (theory, experiment, objective minimization, etc.) has its own dedicated module. This presentation gives an overview over of the current status of this workflow, highlights present and future challenges, and highlights possible extensions to other projects with similar requirements.

Lersch, Daniel [Thomas Jefferson National Accelera↗

DOE OSTI2021

Design-Space Data: Informing Common Design Decisions with Pre-Simulated Data

Design Space Exploration (DSE) analysis techniques represent a data-centric approach to integrating performance analysis in early design phases when there is the greatest potential to cheaply improve the energy efficiency of a building. We focus on a novel extension of DSE called Universal Design Space Exploration (UDSE), which leverages massive databases of pre-simulated analysis that represent all possible outcomes of common analysis workflows. These databases, called Design Spaces, become “universal” when a single pre-simulated design space can be re-applied to future unknown projects. Unlike current simulation methods, which require a design to exist before it can be analyzed and often take minutes or hours to simulate, UDSE leverages pre-simulation to deliver rapid and relevant insight as new designs are conceptualized. The data underpinning UDSE enables advanced statistical and Artificial Intelligence methods, allowing UDSE to deliver a greater understanding of the larger problem being explored, rather than simply delivering analysis of several pre-conceived design options. We believe that UDSE can provide instantaneous, relevant analysis for all building design projects at negligible cost. This paper has two main goals, to develop a relevant Universal Design Space that showcases the potential of UDSE and to release this data freely to industry and academia; thereby lowering the barrier to entry to digital literacy in statistics, ML and AI within the architecture, engineering, construction (AEC) industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Solar Spectrum Conversion for an Algae Bioreactor (CRADA Final Report)

This project focused on developing advanced optical coatings to improve solar energy utilization. The research aimed to create lanthanide-doped upconversion nanoparticles (UCNPs) capable of capturing unused near-infrared (NIR) light from the sun and converting it into visible light (blue and red photons) that can be used for photosynthesis. The primary goal was to identify, synthesize, and integrate highly efficient UCNPs into a transparent thin-film device. Through a comprehensive workflow involving computer simulations, high-throughput robotic synthesis, and detailed optical characterization, the project successfully developed a high-performance material. The key technical achievement was the creation of a core-shell UCNP (NaYF₄:20%Yb³⁺, 2%Er³⁺ coated with a 10 nm NaYF₄ shell) that demonstrated a quantum yield of 3.2% for converting 980 nm NIR light into visible light. Transparent thin films fabricated from these nanoparticles showed excellent optical properties, confirming their potential for practical applications. This research adds to the scientific understanding of energy transfer in lanthanide materials and demonstrates a technically effective method for creating efficient light-converting coatings. The primary benefit to the public lies in the potential for these coatings to enhance the efficiency of solar-driven processes, such as boosting the growth of algae in photobioreactors for biofuel production.

14 SOLAR ENERGY↗

DOE OSTI2026

Active learning enables generation of molecules that advance the known Pareto front

Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecules that improve upon the properties of the structures represented in the training distribution. We find that this limitation arises not only from the molecule generation process itself, but also from the poor generalization capabilities of molecular property predictors. We address this challenge by creating a closed-loop molecule generation pipeline with iterative retraining on new quantum chemical simulation data. Compared against static, single-pass generative modeling approaches, only our closed-loop iterative workflow generates molecules with properties extending beyond the training distribution (up to 0.44 standard deviations beyond the original range) and achieves a 79% improvement in out-of-distribution molecule classification accuracy. Furthermore, by conditioning molecular generation on thermodynamic stability data obtained during the iterative loop, the proportion of stable and hence potentially synthesizable molecules generated is 3.5x higher than the next-best model.

Chemistry↗

DOE OSTI2025

Tailoring composition and deformation modes at the microstructural level for next generation low-cost high-strength austenitic stainless steels

The objective of this project is to enable deliberate development of cost-effective, hydrogen resistant alloys by establishing detailed relationships specific to the effects of alloy composition, short-range order (SRO), and microsegregation in the presence of hydrogen on the transition between homogeneous deformation and localized plasticity in shear bands. In collaboration with the International Institute for Carbon-Neutral Energy Research, I2CNER, at Kyushu University in Japan, we conceptualized, designed, and manufactured four austenitic alloys that maintain corrosion resistance and ensure lower cost relative to baseline commercial alloys. The mechanical properties and deformation modes of the novel alloys (KU alloys) were assessed in the presence of hydrogen (H). Correlations between composition and performance revealed that two of the KU alloys are suitable replacements for 316 steel, while another is a viable replacement for 304 steel at room temperature. We found that, in the presence of other austenite stabilizing elements namely Mn and N, replacing Ni with Cu does not lead to martensite formation as has been previously reported.1–3 Furthermore, we found that the addition of Cu leads to an earlier onset of multiple slip resulting in an relative earlier onset of a higher work hardening rate (WHR). Greater understanding of the relationships between alloy composition and SRO required the development of a novel advanced electron diffraction methodology to characterize SRO in complex FCC alloys. This innovative approach, which combines fluctuation and correlation analyses of diffuse-scattering signals, successfully differentiated between SRO and long-range ordering (LRO). Further investigations into annealed austenitic stainless steels could provide insights into manipulating SRO and its effects on material properties. Atomistic simulations provided understanding of SRO behavior that was difficult to capture experimentally. This project created the first spin cluster expansion model that is able to capture and describe SRO effects in Fe-Ni-Cr FCC alloys, accounting for the non-negligible effects of magnetism. An automated computational workflow was established to provide reliable predictions of SRO in Fe-Ni-Cr austenitic alloys, both with and without the presence of H atoms. Analysis of the propensity for SRO in Fe-Ni-Cr alloys revealed that H tends to cluster with specific, well-defined SRO domains. The computational framework is general purpose and can be extended to realistic stainless steels across diverse composition ranges. With confidence that SRO is possible in austenitic stainless steels, we developed a discrete dislocation finite element code to understand the interaction of dislocations with SRO in the presence of H. By incorporating H effects on the dislocation emission and SRO stress field we show that the critical stress for the dislocation pileup to breakthrough the SRO domain decreases in the presence of H, which directly contributes localized deformation at the macroscale. Through the simulation of a uniaxial tension test, we demonstrated that H-induced weakening of SRO stress field and H-enhanced dislocation emission can lead to the onset of shear localization at lower macroscopic strains. As a whole, this project identified three novel alloys that show improvements in performance and cost efficiency for H-facing applications by studying correlations between alloy chemistry and deformation behavior. We also made significant advancements to experimental and computational methodologies necessary to study the chemistry and distribution of SRO across a range of alloys, which in turn allowed us to demonstrate how deformation mechanisms change due to the contributions of SRO in austenitic alloys in the presence of H. The combined advancements in fundamental understanding with novel alloy development in this project has increased the viability of next generation H-technologies for the broader public through accessible low-cost alloys and accelerated development towards future H-infrastructure.

08 HYDROGEN↗

DOE OSTI2018

Design-to-Device Approach Affords Panchromatic Co-sensitized Solar Cells

Data–driven materials discovery has become increasingly important in identifying materials that exhibit specific, desirable properties from a vast chemical search space. Synergic prediction and experimental validation are needed to accelerate scientific advances related to critical societal applications. A design–to–device study that uses high–throughput screens with algorithmic encodings of structure–property relationships is reported to identify new materials with panchromatic optical absorption, whose photovoltaic device applications are then experimentally verified. The data–mining methods source 9431 dye candidates, which are auto–generated from the literature using a custom text–mining tool. These candidates are sifted via a data–mining workflow that is tailored to identify optimal combinations of organic dyes that have complementary optical absorption properties such that they can harvest all available sunlight when acting as co–sensitizers for dye–sensitized solar cells (DSSCs). Six promising dye combinations are shortlisted for device testing, whereupon one dye combination yields co–sensitized DSSCs with power conversion efficiencies comparable to those of the high–performance, organometallic dye, N719. Here, these results demonstrate how data–driven molecular engineering can accelerate materials discovery for panchromatic photovoltaic or other applications.

14 SOLAR ENERGY↗

DOE OSTI2026

A Step-by-Step Protocol from METASPACE to Biological Interpretation

Mass spectrometry imaging (MSI) represents an exceptional tool for exploring complex biological systems spatially at the molecular level. However, due to its multidimensional nature and large-scale data output, it presents considerable challenges when it comes to extracting meaningful biological insights. Recent advancements, such as the METASPACE platform, have enabled researchers to efficiently process, annotate, and interpret MSI datasets by leveraging machine learning and cloud-based infrastructure. In this tutorial, we present a detailed and user-friendly R-pipeline designed to help METASPACE users navigate untargeted metabolomic annotations and transform them into practical insights about their biological systems. By combining METASPACE annotations with rapid R-based screening, this workflow not only streamlined the analytical process but also enhanced the understanding of spatial molecular distribution, especially for complex systems. Here, this easy-to-follow approach has the potential for applications in diagnostics, drug discovery, environmental and ecological processes, and more. We envision this pipeline to be particularly useful for newcomers to the field of MSI and

Moreno Pedraza, Abigail↗

DOE OSTI2020

Accelerating Scientific Computing in the Post-Moore’s Era

Novel uses of graphical processing units for accelerated computation revolutionized the field of high-performance scientific computing by providing specialized workflows tailored to algorithmic requirements. As the era of Moore’s law draws to a close, many new non–von Neumann processors are emerging as potential computational accelerators, including those based on the principles of neuromorphic computing, tensor algebra, and quantum information. While development of these new processors is continuing to mature, the potential impact on accelerated computing is anticipated to be profound. We discuss how different processing models can advance computing in key scientific paradigms: machine learning and constraint satisfaction. Significantly, each of these new processor types utilizes a fundamentally different model of computation, and this raises questions about how to best use such processors in the design and implementation of applications. While many processors are being developed with a specific domain target, the ubiquity of spin-glass models and neural networks provides an avenue for multi-functional applications. Furthermore, this also hints at the infrastructure needed to integrate next-generation processing units into future high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗