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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Three-Dimensional Mass Spectrometric Imaging of Biological Structures Using a Vacuum-Compatible Microfluidic Device

Three-dimensional (3D) molecular imaging of biological structures is important for a wide range of research. In recent decades, secondary ion mass spectrometry (SIMS) has been recognized as a powerful technique for both two-dimensional (2D) and 3D molecular imaging. Sample fixations (e. g., chemical fixation and cryogenic fixation methods) are necessary to adapt biological samples to the vacuum condition in the SIMS chamber, which has been demonstrated to be non-trivial and less controllable, thus limiting the wider application of SIMS on 3D molecular analysis of biological samples. Our group recently developed in situ liquid SIMS that offers great opportunities for the molecular study of various liquids and liquid interfaces. In this work, we demonstrate that a further development of the vacuum-compatible microfluidic device used in in situ liquid SIMS provides a convenient freeze-fixation of biological samples and leads to more controllable and convenient 3D molecular imaging. The special design of this new vacuum-compatible liquid chamber allows an easy determination of sputter rates of ice, which is critical for calibrating the depth scale of frozen biological samples. Sputter yield of a 20 keV Ar 1800 + ion on ice has been determined as 1500 (± 8%) water molecules per Ar 1800 + ion, consistent with our results from molecular dynamics simulations. Moreover, using the information of ice sputter yield, we successfully conduct 3D molecular imaging of frozen homogenized milk and observe network structures of interesting organic and inorganic species. Finally, taken together, our results will significantly benefit various research fields relying on 3D molecular imaging of biological structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Screening the complex biological behavior of late lanthanides through genome-wide interactions

Abstract Despite their similar physicochemical properties, recent studies have demonstrated that lanthanides can display different biological behaviors. Hence, the lanthanide series can be divided into three parts, namely early, mid, and late lanthanides, based on their interactions with biological systems. In particular, the late lanthanides demonstrate distinct, but poorly understood biological activity. In the current study, we employed genome-wide functional screening to help understand biological effects of exposure to Yb(III) and Lu(III), which were selected as representatives of the late lanthanides. As a model organism, we used Saccharomyces cerevisiae, since it shares many biological functions with humans. Analysis of the functional screening results indicated toxicity of late lanthanides is consistent with disruption of vesicle-mediated transport, and further supported a role for calcium transport processes and mitophagy in mitigating toxicity. Unexpectedly, our analysis suggested that late lanthanides target proteins with SH3 domains, which may underlie the observed toxicity. This study provides fundamental insights into the unique biological chemistry of late lanthanides, which may help devise new avenues toward the development of decorporation strategies and bio-inspired separation processes.

Pallares, Roger M. (ORCID:0000000174238706)↗
DOE OSTI2022

Precursor prioritization for p-cymene production through synergistic integration of biology and chemistry

Abstract The strategy of synergistic application of biological and chemical catalysis is an important approach for efficiently converting renewable biomass into chemicals and fuels. In particular, the method of determining the appropriate intermediate between the two catalytic methods is critical. In this work, we demonstrate p -cymene production through the integration of biosynthesis and heterogenous catalysis and show how a preferred biologically derived precursor could be determined. On the biological side, we performed the limonene and 1,8-cineole production through the mevalonate pathway. Titers of 0.605 g/L and a 1.052 g/L were achieved, respectively. This difference is in agreement with the toxicity of these compounds toward the producing microorganisms, which has implications for subsequent development of the microbial platform. On the heterogeneous catalysis side, we performed the reaction with both biological precursors to allow for direct comparison. Using hydrogenation/dehydrogenation metals on supports with acid sites, both limonene and 1,8-cineole were converted to p -cymene with similar yields under equivalent reaction conditions. Thus, we could determine that the most promising strategy would be to target 1,8-cineole, the higher titer and lower toxicity bio-derived precursor with subsequent catalytic conversion to p -cymene. We further optimized the biological production of 1,8-cineole via fed-batch fermentation and reached the titer of 4.37 g/L which is the highest known 1,8-cineole titer from microbial production. This work provides a valuable paradigm for early stage considerations to determine the best route for the high-efficiency production of a target biobased molecule using an integration of biology and chemistry.

09 BIOMASS FUELS↗
DOE OSTI2024

New Opportunities for Neutrons in Environmental and Biological Sciences

The use of neutron methods in environmental and biological sciences is rapidly emerging and accelerating with the development of new instruments at neutron user facilities. This article, based on a workshop held at Oak Ridge National Laboratory (ORNL), offers insights into the application of neutron techniques in environmental and biological sciences. Here we highlight recent advances and identify key challenges and potential future research areas. These include soil and rhizosphere processes, root water dynamics, plant-microbe interactions, structure and dynamics of biological systems, applications in synthetic biology and enzyme engineering, next-generation bioproducts, biomaterials and bioenergy, nanoscale structure, and fluid dynamics of porous materials in geochemistry. We provide an outlook on emerging opportunities with an emphasis on new capabilities that will be enabled at the Spallation Neutron Source Second Target Station currently under design at ORNL. The mission of scientific neutron user facilities worldwide is to enable science using state-of-the-art neutron capabilities. We aim to encourage researchers in the environmental and biological research community to explore the unique capability afforded by neutrons at these facilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Advancing biological processing for valorization of plastic wastes

We report the useful applications of plastics are as significant as the problems associated with their disposal. Current waste management strategies are ineffective at preventing the flow of plastics into landfills, wastewater treatment, and the environment. Despite the importance of recycling technologies, most plastics are used for consumables and are discarded after limited usage. Moreover, only certain plastics are recycled, and those that are generally yield lower value products. Discovering alternative routes for valorizing plastic wastes is essential. Emerging research involves the use of biocatalysts (i.e., enzymes and microorganisms) to produce valuable products like specialty polymers, biosurfactants, and drug precursors from these feedstocks. These bioprocesses commonly integrate physio-chemical pretreatments (to generate biologically reactive intermediates) and biological upgrading (to convert intermediates to products). Herein, publications that explore plastic deconstruction technologies and bioprocesses are reviewed with an emphasis on plastic waste valorization. Understanding how microorganisms metabolize the intermediates of plastic degradation and manage their inhibitory effects is a prerequisite for engineering bioprocesses. For these heterogeneous wastes, a paradigm shift from axenic cultivation of microorganisms to cultivation of microbial consortia may benefit conversion efficiency and stress resilience. Thus, a summary is provided for metabolic pathways and constituent enzymes required to synthesize biofuels, biomaterials, and chemicals from biologically reactive intermediates. Colossal challenges associated with the use of plastics as feedstocks for direct biological processing highlight the need for integrating physical, chemical, and biological technologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Flow matching meets biology and life science: a survey

Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Biological Response Models: Predicting Injury and Mortality of Fish During Downstream Passage through Hydropower Facilities

This report describes the U.S. Department of Energy’s HydroPASSAGE project efforts to develop and collect biological response models for integration into the Biological Performance Assessment (BioPA) toolset and the Hydropower Biological Evaluation Toolset (HBET). These models help understand how fish are likely to respond during dam passage when exposed to hydraulic and physical stressors associated with turbines and other hydropower structures. When fish pass through hydropower facilities, they may encounter several stressors, of which the three most common are collision, rapid decompression, and fluid shear. Specialized equipment has been used to develop 99 biological response models for exposure to blade strike, rapid decompression, or fluid shear. The models were gathered from the literature or developed as part of this effort and include models for 31 different species of fish that have various predicted endpoints (i.e., injury or mortality). Among these models, considerable variation in susceptibility to the stressors has been observed from one species to another, and a species’ susceptibility to one stressor does not necessarily indicate similar susceptibility to another. Although several species have been examined, it is still unclear how many other species, which may have different morphological traits, may respond to these stressors, so further examination of the different species is needed. These models can and have been applied in several different cases, often using the BioPA toolset and HBET, to better understand the potential for injury and mortality that may occur during fish passage at hydropower facilities, including specific applications, such as turbine replacement, the installation of new turbines, or changing operations of currently installed turbines. As hydropower is continually developed to meet the electricity needs of society, tools such as HBET and BioPA, used with the integrated biological response models, will aid in the development of technologies and strategies that avoid, minimize, mitigate, or manage environmental effects.

13 HYDRO ENERGY↗
DOE OSTI2020

Application of Systems Engineering Principles and Techniques in Biological Big Data Analytics: A Review

In the past few decades, we have witnessed tremendous advancements in biology, life sciences and healthcare. These advancements are due in no small part to the big data made available by various high-throughput technologies, the ever-advancing computing power, and the algorithmic advancements in machine learning. Specifically, big data analytics such as statistical and machine learning has become an essential tool in these rapidly developing fields. As a result, the subject has drawn increased attention and many review papers have been published in just the past few years on the subject. Different from all existing reviews, this work focuses on the application of systems, engineering principles and techniques in addressing some of the common challenges in big data analytics for biological, biomedical and healthcare applications. Specifically, this review focuses on the following three key areas in biological big data analytics where systems engineering principles and techniques have been playing important roles: the principle of parsimony in addressing overfitting, the dynamic analysis of biological data, and the role of domain knowledge in biological data analytics.

dynamic analysis↗
DOE OSTI2022

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Biological Upcycling of Plastics Waste

Plastic wastes accumulate in the environment, impacting wildlife and human health and representing a significant pool of inexpensive waste carbon that could form feedstock for the sustainable production of commodity chemicals, monomers, and specialty chemicals. Current mechanical recycling technologies are not economically attractive due to the lower-quality plastics that are produced in each iteration. Thus, the development of a plastics economy requires a solution that can deconstruct plastics and generate value from the deconstruction products. Biological systems can provide such value by allowing for the processing of mixed plastics waste streams via enzymatic specificity and using engineered metabolic pathways to produce upcycling targets. We focus on the use of biological systems for waste plastics deconstruction and upcycling. We highlight documented and predicted mechanisms through which plastics are biologically deconstructed and assimilated and provide examples of upcycled products from biological systems. Additionally, we detail current challenges in the field, including the discovery and development of microorganisms and enzymes for deconstructing non–polyethylene terephthalate plastics, the selection of appropriate target molecules to incentivize development of a plastic bioeconomy, and the selection of microbial chassis for the valorization of deconstruction products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Predictive links between microbial communities and biological oxygen utilization in the Arctic Ocean

Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.

Chamberlain, Emelia J. [Univ. of San Diego, San Di↗
DOE OSTI2022

Biological underpinnings for lifelong learning machines

Biological organisms learn from interactions with their environment throughout their lifetime. For artificial systems to successfully act and adapt in the real world, it is desirable to similarly be able to learn on a continual basis. This challenge is known as lifelong learning, and remains to a large extent unsolved. In this Perspective article, we identify a set of key capabilities that artificial systems will need to achieve lifelong learning. We describe a number of biological mechanisms, both neuronal and non-neuronal, that help explain how organisms solve these challenges, and present examples of biologically inspired models and biologically plausible mechanisms that have been applied to artificial systems in the quest towards development of lifelong learning machines. We discuss opportunities to further our understanding and advance the state of the art in lifelong learning, aiming to bridge the gap between natural and artificial intelligence. It is an outstanding challenge to develop intelligent machines that can learn continually from interactions with their environment, throughout their lifetime. Kudithipudi et al. review neuronal and non-neuronal processes in organisms that address this challenge and discuss pathways to developing biologically inspired approaches for lifelong learning machines.

Kudithipudi, Dhireesha↗
DOE OSTI2022

PDB‐101: Molecular Explorations through Biology and Medicine

PDB‐101 is an online portal for teachers, students, and the general public to promote exploration of the structural biology of proteins and nucleic acids ( pdb101.rcsb.org ). Learning about the diverse shapes and functions of these biological macromolecules helps to understand all aspects of biomedicine and agriculture, from protein synthesis to health and disease to biological energy. Why PDB‐101? Researchers around the world are studying these molecules at the atomic level. These 3D structures are freely available at the Protein Data Bank (PDB), the central storehouse of biomolecular structures. This website builds introductory materials to help beginners get started in the basics of biomolecular structure and function (“101”, as in an entry level course) as well as resources for extended learning. Since 2011, PDB‐101 has been developed by the RCSB PDB , a global resource for the advancement of research and education in biology and medicine. Along with our Worldwide PDB collaborators, RCSB PDB curates, annotates, and makes publicly available the PDB data deposited by scientists around the globe. The RCSB PDB then provides a window to these data through a rich online resource with powerful searching, reporting, and visualization tools for researchers. This information is then streamlined for students and teachers at PDB‐101. Features include the ongoing Molecule of the Month series, educational materials such as paper models, posters, molecular animations, educational curricula and more. The section “Guide to Understanding PDB Data” is a primer for detailed PDB‐specific information: PDB Data, Visualizing Structures, Reading Coordinate Files, scientific methods for structure determination, and more. PDB‐101 also runs annual Video Challenges for high school students. Participants create short videos that tell molecular stories that connect structural biology and medicine. Previous topics have included HIV/AIDS, diabetes, and antimicrobial resistance. The 2022 challenge will focus on Molecular Mechanisms of Cancer. PDB‐101 activities are evaluated using user surveys, feedback from in‐person activities, and website analytics. In 2020, PDB‐101 hosted >850,000 users and >2.6 million page views.

Zardecki, Christine↗
DOE OSTI2021

Essential oils used in dermocosmetics: Review about its biological activities

Abstract Introduction Currently, the demand for the use of constituents of natural origin in cosmetic formulations in detriment of synthetic compounds is noticeable. Several studies assess the potential of essential oils when incorporated into various cosmetic formulations and study their biological activities. This work intends to prepare a literature review on essential oils tested in dermocosmetic formulations and whose biological activities were evaluated through in vitro and/or in vivo tests. The main objectives for this study were as follows: to identify the essential oils that have been used in cosmetic formulations; and compile information on the main biological activities tested in cosmetic formulations. Methods A search was carried out until 2021 in the scientific databases PubMed and Web of Science, using different search terms, and several scientific articles from in vitro and in vivo studies in animals and clinical trials were selected and analyzed of involving development dermocosmetic formulations containing essential oils and the analysis of their biological activities. Results These studies demonstrate that the antimicrobial activity (antibacterial and antifungal) is the one most studied, mainly through in vitro tests. In vivo studies were also carried out either in animals or in clinical studies showing different effects, such as repellent action, inhibition of hair growth, and action against migraine. Regarding formulations, it was evident that creams are the most used. Conclusions There is enormous potential for the use of essential oils in future formulations in the cosmetic and pharmaceutical industry, in particular as preservatives, exploring their other biological activities.

Cunha, Cassandra↗
DOE OSTI2023

Seven governing principles in biology

In physical science such as physics and chemistry, there are governing principles that are universal and applicable to all relevant systems, including energy conservation, entropy increase, uncertainty principle in quantum mechanics, and chemical equilibrium. However, what are governing principles in biology that are unique to all living systems? After collecting opinions and thoughts from diverse scientists and engineers all over the world, I summarize seven governing principles or laws in biology: central dogma, evolution, biological robustness, regeneration, reproduction, development, and causality. Some of these are not necessarily unique in biological systems from a reductionist’s point of view (e.g., causality), and others are applicable predominantly to eukaryotes (e.g., reproduction and development). Notably, many engineering systems have mimicked biological systems to enhance their performance. In this perspective article, I discuss these principles to better understand the rules of life and help construct improved engineering systems that we can use and control in an ethical, safe, and rational way.

Moon, Tae Seok↗
DOE OSTI2020

Modeling biological nitrogen fixation in global natural terrestrial ecosystems

Biological nitrogen fixation plays an important role in the global nitrogen cycle. However, the fixation rate has been usually measured or estimated at a particular observational site. To quantify the fixation amount at the global scale, process-based models are needed. This study develops a biological nitrogen fixation model to quantitatively estimate the nitrogen fixation rate by plants in a natural environment. The revised nitrogen module better simulates the nitrogen cycle in comparison with our previous model that has not considered the fixation effects. The new model estimates that tropical forests have the highest fixation rate among all ecosystem types, which decreases from the Equator to the polar region. The estimated nitrogen fixation in global terrestrial ecosystems is 61.5 Tg N yr-1 with a range of 19.8–107.9 Tg N yr-1 in the 1990s. Our estimates are relatively low compared to some early estimates using empirical approaches but comparable to more recent estimates that involve more detailed processes in their modeling. Furthermore, the contribution of nitrogen made by biological nitrogen fixation depends on ecosystem type and climatic conditions. This study highlights that there are relatively large effects of biological nitrogen fixation on ecosystem nitrogen cycling. and the large uncertainty of the estimation calls for more comprehensive understanding of biological nitrogen fixation. More direct observational data for different ecosystems are in need to improve future quantification of fixation and its impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images

Images are increasingly becoming the currency for documenting biodiversity on the planet, providing novel opportunities for accelerating scientific discoveries in the field of organismal biology, especially with the advent of large vision-language models (VLMs). We ask if pre-trained VLMs can aid scientists in answering a range of biologically relevant questions without any additional fine-tuning. In this paper, we evaluate the effectiveness of 12 state-of-the-art (SOTA) VLMs in the field of organismal biology using a novel dataset, VLM4Bio, consisting of 469K question8 answer pairs involving 30K images from three groups of organisms: fishes, birds, and butterflies, covering five biologically relevant tasks. We also explore the effects of applying prompting techniques and tests for reasoning hallucination on the performance of VLMs, shedding new light on the capabilities of current SOTA VLMs in answering biologically relevant questions using images

Maruf, M [Virginia Tech, Blacksburg]↗