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DOE OSTI2025

Atomate2: modular workflows for materials science

High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

2019 Argonne Leadership Computing Facility Science Report

The Argonne Leadership Computing Facility (ALCF) is a U.S. Department of Energy (DOE) Office of Science User Facility that enables breakthroughs in science and engineering by providing supercomputing resources and expertise to the research community. ALCF computing resources - available to researchers from academia, industry, and government agencies - support large-scale computing projects aimed at solving some of the world’s most complex and challenging scientific problems. Through awards of supercomputing time and support services, the ALCF enables its users to accelerate the pace of discovery and innovation across disciplines.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Challenges of open data in aquatic sciences: issues faced by data users and data providers

Free use and redistribution of data (i.e., Open Data) increases the reproducibility, transparency, and pace of aquatic sciences research. However, barriers to both data users and data providers may limit the adoption of Open Data practices. Here, we describe common Open Data challenges faced by data users and data providers within the aquatic sciences community (i.e., oceanography, limnology, hydrology, and others). These challenges were synthesized from literature, authors’ experiences, and a broad survey of 174 data users and data providers across academia, government agencies, industry, and other sectors. Through this work, we identified seven main challenges: 1) metadata shortcomings, 2) variable data quality and reusability, 3) open data inaccessibility, 4) lack of standardization, 5) authorship and acknowledgement issues 6) lack of funding, and 7) unequal barriers around the globe. Our key recommendation is to improve resources to advance Open Data practices. This includes dedicated funds for capacity building, hiring and maintaining of skilled personnel, and robust digital infrastructures for preparation, storage, and long-term maintenance of Open Data. Further, to incentivize data sharing we reinforce the need for standardized best practices to handle data acknowledgement and citations for both data users and data providers. We also highlight and discuss regional disparities in resources and research practices within a global perspective.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Argonne’s women science leaders: Cristina Negri

Argonne’s Director of Environmental Science Cristina Negri inherited her father’s love of nature, inspiring her to pursue a career in the natural sciences. As one of Argonne’s scientific leaders, Negri has learned that steps to improve the lives of women can impact the entire laboratory.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Discussion of “Is reliability a new science?”

I would like to thank the participants of the panel at the 10th International Conference on Mathematical Methods in Reliability (MMR 2017) for their thoughtful and thorough discussion on this topic. In considering the fundamentals of a discipline, it is often possible to gain additional understanding about its strengths, weaknesses, and potential gaps. I confess that my perspective on the topic most closely matches thoughts expressed by William Meeker about the crux of the matter being tied to the choice of definitions. There are a multitude of candidate definitions, and each of the panelists chose to focus on different aspects from different sources. I opted for the Oxford English Dictionary definition of “The intellectual and practical activity encompassing the systematic study of the structure and behaviour of the physical and natural world through observation and experiment.” Based on this definition, I would conclude that reliability can qualify as a science because (1) it shares elements of intellectual and practical activity through the development of methodologies to characterize observed patterns, (2) it considers both the structure and behavior of the systems that it seeks to characterize, and (3) it involves notions of obtaining data (observation) and prioritizes the collection of high-quality data with known pedigree through experimentation. More broadly, however, I think that it has elements that expand beyond just a science and contain elements of engineering. To illustrate this, I present some of the thinking that has recently been occurring related to the distinction between statistical science and statistical engineering.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

MtnSEON and social–ecological systems science in complex mountain landscapes

The Mountain Social Ecological Observatory Network (Mtn SEON ) is a US National Science Foundation‐funded Research Coordination Network that focuses on social–ecological systems ( SES ) science approaches to understanding the vulnerability, resilience, and sustainability of complex mountain landscapes. Papers from members of several Mtn SEON working groups are presented in this Special Issue, with topics ranging from applying an SES conceptual approach to social–ecological observatories to dealing with the human aspects of predator–livestock interactions in the American West. All of these articles portray varying degrees of integration of social and ecological sciences and methodologies in order to better address both complex and “wicked” problems inherent to many coupled natural and human systems. The diversity of approaches presented here reflect the different project histories, disciplines being integrated, fields of expertise, and nature of the environmental problems and issues being addressed.

Alessa, Lilian↗

DOE OSTI2018

Community‐based observing for social–ecological science: lessons from the Arctic

Environmental monitoring and observation by members of local communities have become increasingly common in the US and Canada over the past several decades. During the same period, social–ecological systems ( SES ) science has been developed to explain and predict human and environmental interactions, but empirical methods to generate matched social and ecological datasets are uncommon. Community‐based observing ( CBO ) methodologies were developed in the Arctic to allow for production of environmental data in a social context and are also well suited to provide empirical data for SES science. Community‐based observing networks and systems ( CBONS ) and community observer forums ( COF ) are methodologies developed from collaborations between community members, researchers, and government agencies. Here, we describe CBONS and COF methodologies, provide examples of their usage, and suggest ways in which they can benefit empirical SES science. We conclude by outlining efforts to expand the use of CBO to new knowledge and geographic domains.

Griffith, David L.↗

DOE OSTI2024

The Data Mine model for accessible partnerships in data science

Abstract The Data Mine at Purdue University is a pioneering experiential learning community for undergraduate and graduate students of any background to learn data science. The first data‐intensive experience embedded in a large learning community, The Data Mine had nearly 1300 students in academic year (AY) 2022–2023 and nearly 1700 students for AY 2023–2024. The Data Mine embodies data‐infused education, research, and collaboration. Students learn Python, R, SQL, and shell‐scripting, while working on weekly projects within a high‐performance computing (HPC) cluster. In the Corporate Partners cohort, students work on teams of 5–15 students, led by a paid student team leader. Each cohort follows an Agile approach, working on data‐intensive projects provided by industry partners and mentored by company employees. Students develop professional and data skills throughout the academic year, from August through April. Many students return in subsequent years to the program, increasing their tenure with a Corporate Partner. Student teams are inherently interdisciplinary; students from 133 different majors are involved in the program, ranging from new incoming students through PhD level students. These interdisciplinary teams of students bring new perspectives to challenging problems in which data science is a key part of the solution. The interdisciplinary teams foster an environment of synthesis with ideas and solutions. Students come together with different life experiences, different levels of technical skill, but also varying ways they navigate paths to solutions because of the variety of majors represented, resulting in a more creative and robust solution than a traditional data science program. This article is categorized under: Applications of Computational Statistics > Education in Computational Statistics

Betz, Margaret A.↗

DOE OSTI2021

Science Personality and STEM Ambassador

Dr. Amy Elliott has had unique opportunities to serve as a STEM role model through her various media production projects. Her debut on screen was as a competitor on an engineering reality show competition called “The Big Brain Theory,” aired by The Discovery Channel. Following this competition, Dr. Elliott served as an on-camera host for RoboNation’s water-based, annual collegiate competitions and for The Science Channel’s viral video show, “Outrageous Acts of Science.” Dr. Elliott also serves as volunteer pit-crew for Green Envy Racing, a woman-lead race team that seeks to set and speed records with electric motorcycles. Because of Dr. Elliott’s public exposure, she was selected as an IF/THEN Ambassador by the American Associate for the Advancement of Science (AAAS), a program that seeks to highlight women as STEM role models. Dr. Elliott’s work in 3D printing is frequently a source of inspiration for her.

Elliott, Amy↗

DOE OSTI2024

In situ X-ray and IR probes relevant to Earth science at the Advanced Light Source at Lawrence Berkeley Laboratory

Access to synchrotron X-ray facilities has become an important aspect for many disciplines in experimental Earth science. This is especially important for studies that rely on probing samples in situ under natural conditions different from the ones found at the surface of the Earth. The non-ambient condition Earth science program at the Advanced Light Source (ALS), Lawrence Berkeley National Laboratory, offers a variety of tools utilizing the infra-red and hard X-ray spectrum that allow Earth scientists to probe Earth and environmental materials at variable conditions of pressure, stress, temperature, atmospheric composition, and humidity. These facilities are important tools for the user community in that they offer not only considerable capacity (non-ambient condition diffraction) but also complementary (IR spectroscopy, microtomography), and in some cases unique (Laue microdiffraction) instruments. The availability of the ALS’ in situ probes to the Earth science community grows especially critical during the ongoing dark time of the Advanced Photon Source in Chicago, which massively reduces available in situ synchrotron user time in North America.

58 GEOSCIENCES↗

DOE OSTI2018

Applying the principles of isotope analysis in plant and animal ecology to forensic science in the Americas

Forensic science is an applied science that helps investigators answer questions at the heart of a crime: Who, What, When, Where, and How. As part of that process, forensic practitioners use basic laws of chemistry and physics to examine evidence and theories of origin to interpret said evidence. Ecological research has had an extraordinary impact on forensic science through the development and application of a specialized measurement technique useful for examining evidence that appears chemically and physically identical: stable isotope analysis. In this review, we examine the proven utility of stable isotope analysis in forensic settings from an ecological perspective, concentrating on work from the Americas completed within the last three decades. Our primary focus is on the interpretation of stable isotope ratios using plant and animal physiological models for “source inference,” although we also recognize that sample-to-sample comparison of stable isotope ratios can be useful in many forensic settings. Examples of the forensic application of stable isotope analysis cover the gamut, from cotton used in counterfeit bills to anthrax shipped through the U.S. Postal Service, from beer adulterated with cheap adjuncts to human remains discovered in shallow graves and never identified. Recent methodological developments—including isotope analysis of specific compounds, multiple elements, and radioisotopes—and the generation of isotope landscapes, or isoscapes, approaches for data interpretation promises that stable isotope analysis will continue to be used in forensic settings for another three decades… and beyond.

Chesson, Lesley A.↗

DOE OSTI2018

Science questions and knowledge gaps to study microbial transport and survival in Asian and African dust plumes reaching North America

The Sahara in North Africa and the Gobi and Takla Makan deserts in Asia are the primary sources of mobilized dust in the atmosphere, with regional or global airborne transport estimated at 2 to 5 billion tonnes per year. Annual Asian dust plumes take about 7 to 10 d to cross the Pacific Ocean, and often reach the northwest USA between late February and May. In contrast, the peak season for the movement of African dust storms to the southeastern USA is typically June to August, and dust plumes take about 5 to 7 d to reach Florida. Although studies have documented that a wide range of bacteria, fungi, and viruses in dust plumes reach the USA each year, little is known about temporal and spatial variability in the microbial biodiversity in transoceanic dust plumes, or the effect on the deposition environments. A scoping study (called the Transoceanic Aerobiology Biodiversity Study; TABS) was recently conducted to develop field-based campaigns centered on examining the abundance, diversity, survival, and impact of microorganisms in transoceanic dust plumes arriving in the continental USA from Asia and Africa. This effort identified Science Questions (SQs) and Knowledge Gaps (KGs) that are highly relevant towards an understanding of the microbial diversity, transport, survival and dispersal in transoceanic dusts. Science Questions were defined as broad science topics in transoceanic dust plume microbiology that were underexplored by the aerobiology community. Knowledge Gaps were defined as specific project-level research questions for each SQ that represented important topics in the study of transoceanic aerobiology. Our approach aimed to establish a foundation for future microbiological investigations of Asian and African dust plumes in an international and coordinated manner.

dust aerosol, biological aerosol, microbial aeroso↗

DOE OSTI2020

Developing single-site Pt catalysts for the preferential oxidation of CO: A surface science and first principles-guided approach

Here, we report a comprehensive study combining surface science, Density Functional Theory (DFT) calculations, and catalyst synthesis, characterization, and testing to investigate the preferential oxidation of CO in the presence of H 2 over single-site Pt 1 /Cu x O catalysts. Surface science studies show that while Pt 1 /Cu x O model surfaces enable low-temperature CO oxidation via a Mars-van Krevelen mechanism, there was no evidence for H 2 activation or oxidation. DFT-based calculations explain these results and demonstrate that the H 2 oxidation barrier is high as compared to H 2 desorption from Pt 1 /Cu x O. Inspired by these model catalyst studies, nanoporous Pt 1 /Cu x O catalysts were synthesized and demonstrated to be active and highly selective for the preferential oxidation of CO. This work highlights the potential of combined surface science, theory, and catalyst studies for identifying new catalytic materials, which in this case led to the development of a promising single-site Pt 1 /Cu x O catalyst for the preferential oxidation of CO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Advanced data science toolkit for non-data scientists – A user guide

Emerging modern data analytics attracts much attention in materials research and shows great potential for enabling data-driven design. Data populated from the high-throughput CALPHAD approach enables researchers to better understand underlying mechanisms and to facilitate novel hypotheses generation, but the increasing volume of data makes the analysis extremely challenging. Here in this paper, we introduce an easy-to-use, versatile, and open-source data analytics frontend, ASCENDS (Advanced data SCiENce toolkit for Non-Data Scientists), designed with the intent of accelerating data-driven materials research and development. The toolkit is also of value beyond materials science as it can analyze the correlation between input features and target values, train machine learning models, and make predictions from the trained surrogate models of any scientific dataset. Various algorithms implemented in ASCENDS allow users performing quantified correlation analyses and supervised machine learning to explore any datasets of interest without extensive computing and data science background. The detailed usage of ASCENDS is introduced with an example of experimental high-temperature alloy data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2019

ATLAS probe: Breakthrough science of galaxy evolution, cosmology, Milky Way, and the Solar System

Astrophysics Telescope for Large Area Spectroscopy Probe is a concept for a National Aeronautics and Space Administration probe-class space mission that will achieve ground-breaking science in the fields of galaxy evolution, cosmology, Milky Way, and the Solar System. It is the follow-up space mission to Wide Field Infrared Survey Telescope (WFIRST), boosting its scientific return by obtaining deep 1–4 μm slit spectroscopy for ~70% of all galaxies imaged by the ~2 000 deg 2 WFIRST High Latitude Survey at z > 0.5. Astrophysics Telescope for Large Area Spectroscopy will measure accurate and precise redshifts for ~200 M galaxies out to z < 7, and deliver spectra that enable a wide range of diagnostic studies of the physical properties of galaxies over most of cosmic history. Astrophysics Telescope for Large Area Spectroscopy Probe and WFIRST together will produce a 3D map of the Universe over 2 000 deg 2 , the definitive data sets for studying galaxy evolution, probing dark matter, dark energy and modifications of General Relativity, and quantifying the 3D structure and stellar content of the Milky Way. Astrophysics Telescope for Large Area Spectroscopy Probe science spans four broad categories: (1) Revolutionising galaxy evolution studies by tracing the relation between galaxies and dark matter from galaxy groups to cosmic voids and filaments, from the epoch of reionisation through the peak era of galaxy assembly; (2) Opening a new window into the dark Universe by weighing the dark matter filaments using 3D weak lensing with spectroscopic redshifts, and obtaining definitive measurements of dark energy and modification of General Relativity using galaxy clustering; (3) Probing the Milky Way’s dust-enshrouded regions, reaching the far side of our Galaxy; and (4) Exploring the formation history of the outer Solar System by characterising Kuiper Belt Objects. Astrophysics Telescope for Large Area Spectroscopy Probe is a 1.5 m telescope with a field of view of 0.4 deg 2 , and uses digital micro-mirror devices as slit selectors. It has a spectroscopic resolution of R = 1 000, and a wavelength range of 1–4 μm. The lack of slit spectroscopy from space over a wide field of view is the obvious gap in current and planned future space missions; Astrophysics Telescope for Large Area Spectroscopy fills this big gap with an unprecedented spectroscopic capability based on digital micro-mirror devices (with an estimated spectroscopic multiplex factor greater than 5 000). Astrophysics Telescope for Large Area Spectroscopy is designed to fit within the National Aeronautics and Space Administration probe-class space mission cost envelope; it has a single instrument, a telescope aperture that allows for a lighter launch vehicle, and mature technology (we have identified a path for digital micro-mirror devices to reach Technology Readiness Level 6 within 2 yr). In conclusion, Astrophysics Telescope for Large Area Spectroscopy Probe will lead to transformative science over the entire range of astrophysics: from galaxy evolution to the dark Universe, from Solar System objects to the dusty regions of the Milky Way

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Volcanology, Geochemistry, and Petrology Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is composed of a commentary about the state of Integrated, Coordinated, Open, and Networked (ICON) principles in Volcanology, Geochemistry, and Petrology (VGP), and discussion on the opportunities and challenges of adopting them. VGP encompasses a broad field that addresses volcanic, magmatic, hydrothermal, geomicrobial systems; process investigations that span the physical, geochemical and biological realms, including planetary geology; and one that is extensively supported by state-of-the-art research facilities. We suggest that an open, inclusive, collaborative and evolving model of an international coordinated network is critical to answering the most pressing challenges in VGP. In this commentary piece, we begin to discuss the elements of, challenges to, and path forward in developing such a model. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that potentially contribute to more innovative ways of coordinating and sharing research. It also means bringing more equity to science, by implementing effective measures which consider access to funding, analytical equipment, resources, and mentors. More importantly, ICON to us means having important conversations around what we value in the advancement of science, perhaps exploring outside the idea of meritocracy and evaluating what individual traits can contribute to science outside what has traditionally been considered the norm.

58 GEOSCIENCES↗

DOE OSTI2016

Attosecond science in atomic, molecular, and condensed matter physics

Attosecond science represents a new frontier in atomic, molecular, and condensed matter physics, enabling one to probe the exceedingly fast dynamics associated with purely electronic dynamics in a wide range of systems. This paper presents a brief discussion of the technology required to generate attosecond light pulses and gives representative examples of attosecond science carried out in several laboratories. Attosecond transient absorption, a very powerful method in attosecond science, is then reviewed and several examples of gas phase and condensed phase experiments that have been carried out in the Leone/Neumark laboratories are described.

Leone, Stephen R.↗

DOE OSTI2023

Imaging velocity interferometer system for any reflector (VISAR) diagnostics for high energy density sciences

Two variants of optical imaging velocimetry, specifically the one-dimensional streaked line-imaging and the two-dimensional time-resolved area-imaging versions of the Velocity Interferometer System for Any Reflector (VISAR), have become important diagnostics in high energy density sciences, including inertial confinement fusion and dynamic compression of condensed matter. Here, we give a brief review of the historical development of these techniques, then describe the current implementations at major high energy density (HED) facilities worldwide, including the OMEGA Laser Facility and the National Ignition Facility. We illustrate the versatility and power of these techniques by reviewing diverse applications of imaging VISARs for gas-gun and laser-driven dynamic compression experiments for materials science, shock physics, condensed matter physics, chemical physics, plasma physics, planetary science and astronomy, as well as a broad range of HED experiments and laser-driven inertial confinement fusion research.

47 OTHER INSTRUMENTATION↗