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Women in Science: Fermilab Scientific Computing Specialist Krista Majewski

With February 11 marking the International Day of Women and Girls in Science, female physicists, engineers and computer scientists from CERN and Fermilab share their experiences of building careers in science. Krista Majewski came to Fermilab nine years ago as a software developer and now works in an operations role. She is a computing services specialist and part of the grid and cloud operations group, which manages computing clusters for the CMS experiment and other intensity frontier experiments at the lab. "My typical day would be maintaining the services that our group is responsible for and the machines that they run on. So if there are problems with a computing cluster where a user can't run their jobs, or they're trying to run on resources on the grid and they're unable to, then our group would be responsible for helping debug some of those issues," Krista says. Her path to programming at Fermilab has been winding. After receiving a degree in biomedical engineering, she went to work doing web development and programming for a large consulting firm, then moved to the financial industry. But programming called her back, and she earned a master's degree in computer science to start her new career. For Krista, programming is similar to something she enjoyed as child: solving puzzles. "I think it's a skill that you use in a lot of different ways," she says. Credits: Video production - Fermilab Creative Services Music Copyright: Universal Production Music Astral Light Chevalier Idea originally conceived by Tanya Levshina, Fermilab and Maria Dimou, CERN.

99 GENERAL AND MISCELLANEOUS↗

Women in Science: Fermilab computing analyst Margherita Vittone-Wiersma

With February 11 marking the International Day of Women and Girls in Science, female physicists, engineers and computer scientists from CERN and Fermilab share their experiences of building careers in science. Margherita Vittone-Wiersma came to Fermilab as a physicist in February 1985. Together with a group of researchers from Italy's Institute of Nuclear Physics, she began a new experiment called E687. But she soon learned that she preferred working on data acquisition and the many methods to store and access the huge amount of data coming out of science experiments. What was once mere megabytes of data is now terabytes of information - and experimental physicists need to be able to retrieve stored data and monitor data coming from the detectors in real-time. "It's been an incredible change in scale of the amount of data that is handled by computers and has to be analyzed by the physicists," she says. Margherita migrated from physics to her new role in computing through lots of hands-on learning and classes in different programming languages and software development offered at Fermilab. She officially joined the lab's computing division in 1989. "It's a great experience to work with the physicists," she says. Together physicists and computing experts iterate over tools "to make sure that everything is working the way they expect. It's very rewarding." Credits: Video production - Fermilab Creative Services Music Copyright: Universal Production Music Astral Light Chevalier Idea originally conceived by Tanya Levshina, Fermilab and Maria Dimou, CERN.

99 GENERAL AND MISCELLANEOUS↗

Hanford's 100-HX Pump and Treat Project - a Successful Blend of Science, Technology, Construction, and Project Management - 12412

CH2M Hill Plateau Remediation Company (CHPRC) recently completed construction and start-up of the $25 million 100-HX Groundwater Pump and Treat Project for the Department of Energy (DOE) at its Hanford Reservation site in Washington State. From the onset, the 100-HX Project Leadership Team was able to successfully blend the science and technology of a state-of-the-art groundwater pump and treat system with the principles, tools, and techniques of traditional industrial-type construction and project management. From the 1940's through most of the 1980's, the United States used the Hanford Site to produce nuclear material for national defense at reactor sites located along the Columbia River. While the reactors were operational, large volumes of river water were treated with sodium dichromate (to inhibit corrosion of the reactor piping) and used as a coolant for the reactors. After a single pass through the reactor and before being discharged back to the river, the coolant water was sent to unlined retention basins to cool and to allow the short-lived radioactive contaminants to decay. As a result of these operations, hexavalent chromium was introduced to the vadose zone, and ultimately into the groundwater aquifer and the adjacent Columbia River. In addition, numerous leaks and spills of concentrated sodium dichromate stock solution over the lifetime of reactor operations led to higher concentrations of chromate in the vadose zone and groundwater in localized areas. As a result, the 100 Area was included in the National Priorities List sites under the Comprehensive Environmental Response Compensation and Liability Act of 1980 (CERCLA). The mission of the 100-HX Project is to significantly reduce the concentration of hexavalent chromium in the groundwater by treating up to 3.8 billion gallons (14,300 mega-liters) of contaminated water over its first nine years of operations. In order to accomplish this mission, groundwater scientists and geologists using sophisticated scientific modeling optimized the 100-HX's approximately 0.7 square mile (181 hecto-meters) extraction and injection well field to support continuous operation of a maximum of 800 gallons (3,028 liters) per minute, 24 hours per day, and 7 days per week. The use of traditional resin technology for the plant's ion exchange system required a change out of the resin every 12 weeks and shipment to an offsite facility 1,500 miles (2,414 kilometers) away for regeneration. Instead, the project leadership pursued newer technology with a disposable resin that could be disposed of on-site and would require less frequent change outs, reducing the project's life cycle costs by more than $16 million. Constructing the facility had its own challenges. The well field location overlapped ecologically sensitive lands where bald eagles and native wildlife use the land for their mating habitat for nearly half of the year. Building locations had to be planned around historically and culturally sensitive areas, and around another contractor's remediation work zones. Also, the size of the well field required a transfer (pumping) facility and installation of more than 60 miles (97 kilometers) of high-density polypropylene pipe, 23 miles (38 kilometers) of power cable, and 28 miles (46 kilometers) of control cable. Along with schedule and budget constraints typical of any fast-track project, the project team dealt with severe resource constraints due to competing projects across the Hanford Site caused by the influx of American Recovery and Reinvestment Act stimulus funding. In addition, the project team itself was stretched between completing another $25 million dollar construction project while designing and constructing this project. In order to save money, the project schedule was compressed by three months from the original baseline schedule. This was made possible by the strong use of project management principles throughout the design, construction, and testing phases, as well as implementation of many lessons learned from a similar construction project. In summary, the 100-HX Project truly was a unique blend of science, technology, construction and project management. In summary, Hanford's 100-HX Pump and Treat Project was a successful blend of science, technology, construction, and project management. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Science & Technology Review March 2021

At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world.

08 HYDROGEN↗

Science & Technology Review: April/May 2026 R&D 100 Winners Issue

At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world. Each year, the R&D 100 Awards recognize the top 100 innovations from a pool of international entries. Technologies developed at Lawrence Livermore earned four 2025 R&D 100 Awards, raising the Laboratory’s total to 186. A series of articles beginning on p. 4 describes each winning innovation: monolithic telescopes, the flexible imaging diffraction diagnostic for laser experiments, the in-air drop encapsulation apparatus, and the metaoptics-enabled large-scale 3D nanolithography platform.

36 MATERIALS SCIENCE↗

Perspectives on Citizen Science Data Quality

Information about data quality helps potential data users to determine whether and how data can be used and enables the analysis and interpretation of such data. Providing data quality information improves opportunities for data reuse by increasing the trustworthiness of the data. Recognizing the need for improving the quality of citizen science data, we describe quality assessment and quality control (QA/QC) issues for these data and offer perspectives on aspects of improving or ensuring citizen science data quality and for conducting research on related issues.

54 ENVIRONMENTAL SCIENCES↗

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↗

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↗

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↗

Science and Technology at Oak Ridge National Laboratory

ORNL Director Thom Mason explains the groundbreaking work in neutron sciences, supercomputing, clean energy, advanced materials, nuclear research, and global security taking place at the Department of Energy's Office of Science laboratory in Oak Ridge, TN.

36 MATERIALS SCIENCE↗

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↗

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↗

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↗

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.↗

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.↗

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↗

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↗

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.↗