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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Towards provision of regularly updated climate data from the Coupled Model Intercomparison Project

The Coupled Model Intercomparison Project (CMIP) is a flagship of the World Climate Research Programme (WCRP). CMIP has become a recognised ‘brand’ in climate circles evolving over the last thirty years from a targeted research activity by a small number of climate modelling centres intercomparing their Earth System Model (ESM) simulations to a broad international coordinated research effort (Durack et al, 2025). CMIP is organized as a research activity leveraging funded and in-kind contributions from experts within modelling centres and the broader scientific community supported more recently by a fully-funded International Project Office. Within CMIP, Model Intercomparison Projects (MIPs) are community-designed to understand past, present and future climate. CMIP data provides a valuable resource for climate research and is routinely used to assess model representation of climate processes and test scientific hypotheses in the context of model uncertainty and (forced and internal) variability as evident from its prolific use in scientific publications1 . The impact relies on enabling infrastructure (most prominently via the Earth System Grid Federation (ESGF)), which allows sharing of simulation output, provision of the boundary conditions used in each simulation, and definition of the data standards that are essential to facilitating wide use of the data. The impact is supplemented by the wide-ranging scrutiny to which model simulations are subjected. Beyond its use in research, CMIP data is a key resource for communities producing derived climate information from downscaling and impact studies, such as the Coordinated Regional Downscaling Experiment (CORDEX; Gutowski et al., 2016) and the Intersectoral Impacts MIP (ISIMIP; Frieler et al., 2024). Government, academic and commercial entities also increasingly rely on CMIP and its downstream data for climate risk assessments and climate services (for example, Copernicus Climate Change Service and World Bank portal). This means that, although CMIP is a research activity, it increasingly serves a secondary and very relevant role as a provider of climate data – a long-recognised dichotomy (Stevens, 2024). Research and applications have distinct needs, with the former requiring flexibility and generality and the latter consistency. Here we explain how the design of the research activity has been adapted to reduce the burdens imposed by applications and how the research infrastructure might evolve to further enable scientific inquiry. We propose one possible approach to consistently providing model information and projections for applications in the future.

Environmental sciences↗
DOE OSTI2020

Information Products & Communication Materials for SSEB, SGA, SLC and Partners [Slides]

Contents include the following: 1) Southeastern Regional Carbon Sequestration Partnership (SECARB)–Southern States Energy Board's 48th Annual Meeting, August 8, 2008; 2) Southern States Energy Board Carbon Management Program SSEB Associate Members Meeting, August 21, 2009; 3) Carbon Capture and Sequestration (CCS) Demonstration Project, August 21, 2009; 4) Clean Energy in the Southern Region, August 27, 2010; 5) Carbon Management–Southern Leadership of a Regional Partnership, October 17, 2011; 6) Southeastern Regional Carbon Sequestration Partnership "Knowledge Sharing", August 10, 2012; 7) Southeastern Regional Carbon Sequestration Partnership; 8) Site Visit by Southern Legislative Group, July 30, 2013; 9) SECARB Awards Anthropogenic Test, March 4, 2014; 10) Southern Company/MHI Ltd. 500 TPD CCS Demonstration; 11) SECARB Anthropogenic Test Project Assessment, March 4-5, 2014; 12) Advanced Monitoring Technologies SECARB Phase III CO 2 Storage Citronell, Alabama, March 4, 2014; 13) Geomechanics at Cranfield, March 5, 2014; 14) Gulf Coast Carbon Center Near-Surface Update, March 4-5, 2014; 15) Monitoring Design Best Practices, March 5, 2014; 16) Special Projects–Carbon Management Program, 2015; 17) Special Projects, November 2-3, 2016; 18) Carbon Management Program Carbon Capture & Storage Projects, September 24, 2017; 19) Remarks Before the 58th Annual Meeting of the Executive Committee, September 16, 2018; 20) Annual Business Session, September 24, 2019; and 21) Recent Activities & 2019-2020 Elections Insights, February 7, 2020.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Future energy infrastructure, energy platform and energy storage

Today fossil energy dominates energy consumption across the world. There has been an increasing momentum to reduce fossil energy consumption and increase renewable energy utilization to more than 70%. Such high penetrations of distributed renewable resources bring large uncertainty and complexity that cannot be easily handled by the current infrastructure. For the last two decades, telecommunication industry has gone through a similar transition from centralized to distributed systems, and more recently to platform approaches, which become the corner stone of today’s vibrant platform economy. Based on telecommunication history, we believe that a platform-based approach, called the energy platform, is a viable solution for addressing the renewable energy challenges. The energy platform consists of an array of computational algorithms, sensing and control technologies for key industry, energy generators and users to jointly manage and control the complex energy infrastructure. It includes the following key components: (1) the hardware and software to generate, store, control and transmit electricity/data (the energy cloud), (2) the digital platforms and tools for key energy producers, digital, service and communication industry to share the assets, participate in and manage the complex infrastructure, and for customers to participate in energy transactions, (3) the transaction platform for new service and business models. Additionally, the energy platform requires breakthroughs in large scale energy storage and many other areas including efficient power electronics, sensors and controls, new mathematical and computational tools, and deep integration of energy technologies and information sciences to control and stabilize such complex chaotic systems.

25 ENERGY STORAGE↗
DOE OSTI2021

The 2021 quantum materials roadmap

In recent years, the notion of ‘Quantum Materials’ has emerged as a powerful unifying concept across diverse fields of science and engineering, from condensed-matter and coldatom physics to materials science and quantum computing. Beyond traditional quantum materials such as unconventional superconductors, heavy fermions, and multiferroics, the field has significantly expanded to encompass topological quantum matter, two-dimensional materials and their van der Waals heterostructures, Moiré materials, Floquet time crystals, as well as materials and devices for quantum computation with Majorana fermions. In this Roadmap collection we aim to capture a snapshot of the most recent developments in the field, and to identify outstanding challenges and emerging opportunities. The format of the Roadmap, whereby experts in each discipline share their viewpoint and articulate their vision for quantum materials, reflects the dynamic and multifaceted nature of this research area, and is meant to encourage exchanges and discussions across traditional disciplinary boundaries. It is our hope that this collective vision will contribute to sparking new fascinating questions and activities at the intersection of materials science, condensed matter physics, device engineering, and quantum information, and to shaping a clearer landscape of quantum materials science as a new frontier of interdisciplinary scientific inquiry. We stress that this article is not meant to be a fully comprehensive review but rather an up-to-date snapshot of different areas of research on quantum materials with a minimal number of references focusing on the latest developments.

2D materials↗
DOE OSTI2025

Building hypotheses to understand the synergistic effects of heat and pollution exposure in a changing climate

The increasing intensity, frequency, and duration of extreme weather events due to climate change poses a broad range of health risks, and the synergistic effects of extreme temperature co-occurring with other hazardous exposures such as air pollution may result in higher risks of all-cause mortality and cardiovascular and respiratory morbidity than exposure to either event alone. There are a number of hypothesized mechanisms for this interaction effect, including increased susceptibility to heat effects on chronic conditions affected by air pollution exposure, exacerbation of pollution effects due to temperature-induced stress, and shared pathophysiological pathways (e.g., systemic inflammation), but specific physiological mechanisms are not well understood. In this editorial, the authors discuss this aspect of a recently published study examining ambient formaldehyde combined with high temperature exposure and respiratory disease admissions among children. Here, the observation that the health effects of pollutants such as formaldehyde are amplified following periods of high temperature can help inform risk warning systems even without knowledge of the underlying physiological mechanisms, but a deeper biological understanding of the interaction effects of heat and ambient air pollution may better inform interventions. This is even more important in view of increases in both extreme temperature and pollution events tied to climate change.

Chambliss, Sarah [University of Texas at Austin, T↗
DOE OSTI2023

Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Complete spectroscopy in the attosecond regime

Harnessing light waveforms at attosecond time scales provides information of the structure and dynamics of matter on it's natural time scales. For this reason attosecond metrology has been at the forefront of the optical sciences for more than a decade, and it represents the latest time-domain frontier of the quantum world. Attosecond light pulses are commonly generated using higher-order harmonic generation (HHG) , a process capable of generating XUV coherent pulses. In addition to generate attosecond pulses, HHG can be used to study the structure and dynamics of atoms and molecules by analyzing the spectral content of the XUV pulses. This approach is known as HHG spectroscopy and it provides a coherent, time-dependent approach to study structure and dynamics in the quantum world. In this proposal we will generate harmonics from two optical foci produced by a system of a two-dimensional spatial light modulator (SLM) and a lens. In the far eld the train of attosecond pulses will interfere creating harmonic-dependent fringes. The position of such fringes is a direct measurement of the relative phase between the two foci and they also carry information about the quantum state of the target atom or molecule. Therefore, by measuring the amplitude and relative phase of the emitted harmonics we will have access to both, the amplitude and phase of the dipole moments of the studied target. Because the two beams are completely indistinguishable from each other up to a few millimeters from the focus, both driving pulses share the exact beam path. So far we have measured a jitter of 700 zeptoseconds with a 12.5 attosecond resolution in the delay control of the two foci. These two time scales represent some of the best time controls ever achieved to date.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Describing patterns of familial cancer risk in subfertile men using population pedigree data

STUDY QUESTION Can we simultaneously assess risk for multiple cancers to identify familial multicancer patterns in families of azoospermic and severely oligozoospermic men? SUMMARY ANSWER Here, distinct familial cancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in familial cancer risk by both type of subfertility and within subfertility type. WHAT IS KNOWN ALREADY Subfertile men and their relatives show increased risk for certain cancers including testicular, thyroid, and pediatric. STUDY DESIGN, SIZE, DURATION A retrospective cohort of subfertile men (N = 786) was identified and matched to fertile population controls (N = 5674). Family members out to third-degree relatives were identified for both subfertile men and fertile population controls (N = 337 754). The study period was 1966–2017. Individuals were censored at death or loss to follow-up, loss to follow-up occurred if they left Utah during the study period. PARTICIPANTS/MATERIALS, SETTING, METHODS Azoospermic (0 × 10 6 /mL) and severely oligozoospermic (<1.5 × 10 6 /mL) men were identified in the Subfertility Health and Assisted Reproduction and the Environment cohort (SHARE). Subfertile men were age- and sex-matched 5:1 to fertile population controls and family members out to third-degree relatives were identified using the Utah Population Database (UPDB). Cancer diagnoses were identified through the Utah Cancer Registry. Families containing ≥10 members with ≥1 year of follow-up 1966–2017 were included (azoospermic: N = 426 families, 21 361 individuals; oligozoospermic: N = 360 families, 18 818 individuals). Unsupervised clustering based on standardized incidence ratios for 34 cancer phenotypes in the families was used to identify familial multicancer patterns; azoospermia and severe oligospermia families were assessed separately. MAIN RESULTS AND THE ROLE OF CHANCE Compared to control families, significant increases in cancer risks were observed in the azoospermia cohort for five cancer types: bone and joint cancers hazard ratio (HR) = 2.56 (95% CI = 1.48–4.42), soft tissue cancers HR = 1.56 (95% CI = 1.01–2.39), uterine cancers HR = 1.27 (95% CI = 1.03–1.56), Hodgkin lymphomas HR = 1.60 (95% CI = 1.07–2.39), and thyroid cancer HR = 1.54 (95% CI = 1.21–1.97). Among severe oligozoospermia families, increased risk was seen for three cancer types: colon cancer HR = 1.16 (95% CI = 1.01–1.32), bone and joint cancers HR = 2.43 (95% CI = 1.30–4.54), and testis cancer HR = 2.34 (95% CI = 1.60–3.42) along with a significant decrease in esophageal cancer risk HR = 0.39 (95% CI = 0.16–0.97). Thirteen clusters of familial multicancer patterns were identified in families of azoospermic men, 66% of families in the azoospermia cohort showed population-level cancer risks, however, the remaining 12 clusters showed elevated risk for 2-7 cancer types. Several of the clusters with elevated cancer risks also showed increased odds of cancer diagnoses at young ages with six clusters showing increased odds of adolescent and young adult (AYA) diagnosis [odds ratio (OR) = 1.96–2.88] and two clusters showing increased odds of pediatric cancer diagnosis (OR = 3.64–12.63). Within the severe oligozoospermia cohort, 12 distinct familial multicancer clusters were identified. All 12 clusters showed elevated risk for 1–3 cancer types. An increase in odds of cancer diagnoses at young ages was also seen in five of the severe oligozoospermia familial multicancer clusters, three clusters showed increased odds of AYA diagnosis (OR = 2.19–2.78) with an additional two clusters showing increased odds of a pediatric diagnosis (OR = 3.84–9.32). LIMITATIONS, REASONS FOR CAUTION Although this study has many strengths, including population data for family structure, cancer diagnoses and subfertility, there are limitations. First, semen measures are not available for the sample of fertile men. Second, there is no information on medical comorbidities or lifestyle risk factors such as smoking status, BMI, or environmental exposures. Third, all of the subfertile men included in this study were seen at a fertility clinic for evaluation. These men were therefore a subset of the overall population experiencing fertility problems and likely represent those with the socioeconomic means for evaluation by a physician. WIDER IMPLICATIONS OF THE FINDINGS This analysis leveraged unique population-level data resources, SHARE and the UPDB, to describe novel multicancer clusters among the families of azoospermic and severely oligozoospermic men. Distinct overall multicancer risk and familial multicancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in cancer risk by type of subfertility and within subfertility type. Describing families with similar cancer risk patterns provides a new avenue to increase homogeneity for focused gene discovery and environmental risk factor studies. Such discoveries will lead to more accurate risk predictions and improved counseling for patients and their families. STUDY FUNDING/COMPETING INTEREST(S) This work was funded by GEMS: Genomic approach to connecting Elevated germline Mutation rates with male infertility and Somatic health (Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): R01 HD106112). The authors have no conflicts of interest relevant to this work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

In Vivo Assay Reveals Microbial OleA Thiolases Initiating Hydrocarbon and β-Lactone Biosynthesis

Microbially produced β-lactones are found in antibiotic, antitumor, and antiobesity drugs. Long-chain olefinic membrane hydrocarbons have potential utility as fuels and specialty chemicals. The metabolic pathway to both end products share bacterial enzymes denoted as OleA, OleC, and OleD that transform acyl-CoA cellular intermediates into β-lactones. Bacteria producing membrane hydrocarbons via the Ole pathway additionally express a β-lactone decarboxylase, OleB. Both β-lactone and olefin biosynthesis pathways are initiated by OleA enzymes that define the overall structure of the final product. There is currently very limited information on OleA enzymes apart from the single representative from Xanthomonas campestris . In this study, bioinformatic analysis identified hundreds of new, putative OleA proteins, 74 proteins were screened via a rapid whole-cell method, leading to the identification of 25 stably expressed OleA proteins representing seven bacteria phyla.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Low-Temperature Geothermal Geospatial Datasets: An Example from Alaska

This project is a component of a broader effort focused on geothermal heating and cooling (GHC) with the aim of illustrating the numerous benefits of incorporating GHC and geothermal heat exchange (GHX) into community energy planning and national decarbonization strategies. To better assist private sector investment, it is currently necessary to define and assess the potential of low-temperature geothermal resources. For shallow GHC/GHX fields, there is no formal compilation of subsurface characteristics shared among industry practitioners that can improve system design and operations. Alaska is specifically noted in this work, because heretofore, it has not received a similar focus in geothermal potential evaluations as the contiguous United States. The methodology consists of leveraging relevant data to generate a baseline geospatial dataset of low-temperature resources (less than 150 degrees C) to compare and analyze information accessible to anyone trying to understand the potential of GHC/GHX and small-scale low-temperature geothermal power in Alaska (e.g., energy modelers, communities, planners, and policymakers). Importantly, this project identifies data related to (1) the evaluation of GHC/GHX in the shallow subsurface, and (2) the evaluation of low-temperature geothermal resource availability. Additionally, data is being compiled to assess repurposing of oil and gas wells to contribute co-produced fluids toward the geothermal direct use and heating and cooling resource potential. In this work we identified new data from three different datasets of isolated geothermal systems in Alaska and bottom-hole temperature data from oil and gas wells that can be leveraged for evaluation of low-temperature geothermal resource potential. The goal of this project is to facilitate future deployment of GHC/GHX analysis and community-led programs and update the low-temperature geothermal resources assessment of Alaska. A better understanding of shallow potential for GHX will improve design and operations of highly efficient GHC systems. The deployment and impact that can be achieved for low-temperature geothermal resources will contribute to decarbonization goals and facilitate widespread electrification by shaving and shifting grid loads.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

MAPSTER: Automated Geospatial Data Sharing – Version 1.4.0

The US Department of Energy’s (DOE) Oak Ridge National Laboratory (ORNL) developed MAPSTER which is a geospatial data management tool that aggregates, organizes, and shares data from dispersed sources such as unmanned aerial systems (UAS). Built specifically for use in environments where communications may be limited, MAPSTER utilizes two key technologies to effectively manage data in the field and enable easy data sharing with authorized partners: Observer and Checkpoint. Observer is a lightweight software package on an edge device, such as a laptop, that automatically detects newly processed UAS data and sends to a central server called Checkpoint. Checkpoint is a centralized server at ORNL that receives and manages data from all Observer instances. Even in a very low bandwidth environment, Observer can still send information about the UAS data product almost instantly as it generates its own metadata package on the size of KB (kilobytes). MAPSTER is not only for UAS data but for any geospatial data collected at the austere edge and dispersed sources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Lateral Beam Shifts and Depolarization Upon Oblique Reflection from Dielectric Mirrors

Abstract Dielectric mirrors comprising thin‐film multilayers are widely used in optical experiments because they can achieve substantially higher reflectance compared to metal mirrors. Here, potential problems are investigated that can arise when dielectric mirrors are used at oblique incidence, in particular for focused beams. It is found that light beams reflected from dielectric mirrors can experience lateral beam shifts, beam‐shape distortion, and depolarization, and these effects have a strong dependence on wavelength, incident angle, and incident polarization. Because vendors of dielectric mirrors typically do not share the particular layer structure of their products, several dielectric‐mirror stacks are designed and simulated, and then the lateral beam shift from two commercial dielectric mirrors and one coated metal mirror is also measured. This paper brings awareness of the tradeoffs between dielectric mirrors and front‐surface metal mirrors in certain optics experiments, and it is suggested that vendors of dielectric mirrors provide information about beam shifts, distortion, and depolarization when their products are used at oblique incidence.

Physics↗
DOE OSTI2020

The Study of Environmental Arctic Change (SEARCH) Arctic Futures 2050 Conference. Final Report

The Arctic Futures 2050 Conference was designed as a novel convening of Arctic scientists, Indigenous people, and decision makers, including policy makers at all levels of government. The conference was held 4–6 September 2019 in Washington, D.C. and gathered nearly 400 participants to explore six questions: What do we know, and what do we need to know about the Arctic—and why does it matter? What challenges confront policy makers in the rapidly changing Arctic? What basic research is needed to inform responses to Arctic change? What applied research is needed to inform responses to change? What tools can facilitate informing policy making with science and Indigenous knowledge? What opportunities exist for partnerships between policy makers and scientists? A conference report (see: https://www.searcharcticscience.org/arctic-2050/conference-2019/products) detailed all conference discussions. The main conference conclusion was that holistic understanding and useful adaptation to rapid Arctic change requires bringing together scientists, Indigenous Knowledge holders, and policy makers in all phases of defining the problems, conducting research, and sharing knowledge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

"Russians in the Grid" Enrichment Process

Threat intelligence sources are numerous, and the quality of their intelligence is equally variable. The need for quality, actionable, and shareable intelligence is becoming increasingly important as cyber-threats continue to increase. In this paper, we describe the process we used to enrich U.S. CERT’s Technical Alert entitled “Russian Government Cyber-Activity Targeting Energy and Other Critical Infrastructure Sectors,” affectionately referred to as “Russians In the Grid,” from a series of separate but related reports to a final, actionable, unified Structured Threat Information Expression (STIX) v2 representation of the report. In the process, we detail the tools and procedures we used, some of which are automated and others highly manual. We identify some of the limitations of current STIX enrichment tools and techniques, and propose enhancements to allow for more effective enrichment and better overall threat intelligence to be used for more effective threat data-sharing, as well as machine learning-based predictive threat work being conducted at Idaho National Laboratory.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

A Double-Edged Sword: The Role of Prior Knowledge in Memory Aging

People accumulate knowledge throughout their lifespan and the accumulated knowledge influences how we encode and retrieve information in memory processing. This study aims to investigate the role of knowledge in associative memory across the adult lifespan, and specifically examines the effects of two material properties that interact with prior knowledge: congruency – whether the material is congruent with people’s prior knowledge, and ambiguity – whether the material is ambiguous to interpret based on prior knowledge. 273 participants (aged 22–70 years old) completed an incidental memory task online. Participants were shown pictures depicting an object in a scene and judged if the object was likely or unlikely to be in the particular scene. Later, in the recognition test, participants were asked to identify if the exact picture was presented earlier. The pictures were manipulated to have varying levels of congruency, meaning that some depicted likely object–scene pairs and some unlikely. We also measured how different the likely/unlikely judgment for each object–scene pair was across all participants to determine the ambiguity level of the object–scene pair: some were more likely to receive diverse responses across people, whereas others are unambiguously consistent (or inconsistent) with common knowledge shared by most people. We used mixed-effects logistic regressions to predict memory outcome for each trial as a function of age, age 2 , congruency/ambiguity, and their interactions. The object–scene pairs perceived as congruent had higher hit rates than incongruent ones, as well as higher false alarm rates, especially in middle-aged and older people. Higher ambiguity was also related to both greater true and false memory, independent of age. Finally, the effect of ambiguity only emerged when the object–scene pair was perceived incongruent. The results suggest that people rely on prior knowledge to process new information and that this reliance improves hit responses, but also induces false memories particularly for middle-aged and older people, suggesting a double-edged role of knowledge in associative memory and its disproportionate influence on memory aging. Over-reliance on knowledge in older adults, which has been suspected in other cognitive processes, may be one of the mechanisms underlying associative memory decrease in aging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Bulk Glassy GeTe 2 : A Missing Member of the Tetrahedral GeX 2 Family and a Precursor for the Next Generation of Phase-Change Materials

Vitreous germanium disulfide GeS 2 and diselenide GeSe 2 belong to canonical chalcogenide glasses extensively studied over the past half century. Their high-temperature orthorhombic polymorphs are congruently melting compounds, and the tetrahedral crystal and glass structure is largely preserved in the melt. In contrast, the ditelluride counterpart is absent in the Ge-Te phase diagram, which shows only a single compound, monotelluride GeTe. Phase-change materials based on GeTe have become a technologically important class of solids, and their structure and properties are also widely studied. Surprisingly, very scarce information is available for alloys having GeTe 2 stoichiometry. Using a fast quenching procedure in silica capillaries, high-energy X-ray diffraction, and Raman spectroscopy supported by first-principles simulations, we show that bulk glassy GeTe 2 differs substantially from the lighter GeX 2 members, revealing 46% of trigonal germanium, 31% of three-fold coordinated tellurium, and only 20% of edge-sharing tetrahedra or pyramids. The fraction of homopolar Ge-Ge bonds is low; however, the population of dominant Te-Te dimers and Te n oligomers, n <= 10, appears to be significant. The complex structural and chemical topology of g-GeTe 2 is directly related to the thermodynamic metastability of germanium ditelluride, schematically represented by the following reaction: GeTe 2 $\rightleftarrows$ GeTe + Te. Disproportionation is complete above liquidus in the temperature range of semiconductor-metal transition, and the dense metallic GeTe 2 liquid, mostly consisting of five-fold coordinated Ge species, exhibits high fluidity, strong fragility (m = 99 ± 5), and presumably a fast structural transformation rate combined with low atomic mobility in the vicinity of the glass transition temperature, favorable for reliable long-term data retention in nonvolatile memories. The observed and predicted characteristic features make GeTe 2 a promising precursor for the next generation of phase-change materials, especially coupled with additional metal doping, depolymerizing the tetrahedral interconnected glass network and accelerating (sub)nanosecond crystallization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression

Lossy compression techniques have demonstrated promising results in significantly reducing the scientific data size while guaranteeing the compression error bounds. However, one important yet often neglected side effect of lossy scientific data compression is its impact on the performance of parallel I/O. Our key observation is that the compressed data size is often highly skewed across processes in lossy scientific compression. To understand this behavior, we conduct extensive experiments where we apply three lossy compressors MGARD, ZFP, and SZ, which are specifically designed and optimized for scientific data, to three real-world scientific applications Gray-Scott simulation, WarpX, and XGC. Our analysis result demonstrates that the size of the compressed data is always skewed even if the original data is evenly decomposed among processes. Such skewness widely exists in different scientific applications using different compressors as long as the information density of the data varies across processes. We then systematically study how this side effect of lossy scientific data compression impacts the performance of parallel I/O. We observe that the skewness in the sizes of the compressed data often leads to I/O imbalance, which can significantly reduce the efficiency of I/O bandwidth utilization if not properly handled. In addition, writing data concurrently to a single shared file through MPI-IO library is more sensitive to the unbalanced I/O loads. Therefore, we believe our research community should pay more attention to the unbalanced parallel I/O caused by lossy scientific data compression.

Wang, Xinying↗