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DOE OSTI2026

Exploring life’s hidden majority: microbial dark matter symposium highlights

The Microbial Dark Matter Symposium held on August 28–29, 2025, in Laguna Beach, Orange County, CA, convened a multidisciplinary group of scientists to address the vast unknowns in microbial life—from uncultured taxa and uncharacterized proteins to elusive viruses and spacefaring microbes. Set against a scenic coastal backdrop, the symposium highlighted advances in single-cell genomics, proximity ligation sequencing, and artificial intelligence-ready bioinformatics, while also probing the limits of microbial persistence, metabolism, and ecological distribution. Sessions explored microbial dark matter from multiple dimensions: cultivability, where new strategies are enabling recovery of elusive microbes; functional ambiguity, where metagenomic dark zones are illuminated by computational annotation; and genomic representation, where single-cell methods bridge gaps left by shotgun community sequencing. Researchers shared breakthroughs in identifying atmospheric microbiomes, “dark oxygen” production in groundwater ecosystems, and microbial survival on the International Space Station. The symposium emphasized integration of methods, disciplines, and ecosystems, advancing a collective push to illuminate the microbial dark matter on Earth and beyond. By highlighting emerging tools, pressing questions, and cross-domain insights, the symposium underscored the need for collaborative, open, and adaptive approaches to study the microbial unknown. The meeting marks a pivotal moment in microbiology, where cultivating knowledge of the uncultivated promises transformative understanding of life, everywhere.

Podar, Mircea [ORNL] (ORCID:0000000327760205)↗

DOE OSTI2024

Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain. As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO 2 e yr -1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO 2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Case-based reasoning for space applications: Utilization of prior experience in knowledge-based systems

The goal is to explain Case-Based Reasoning as a vehicle to establish knowledge-based systems based on experimental reasoning for possible space applications. This goal will be accomplished through an examination of reasoning based on prior experience in a sample domain, and also through a presentation of proposed space applications which could utilize Case-Based Reasoning techniques.

King, James A.↗

DOE OSTI2024

Opportunities for retrieval and tool augmented large language models in scientific facilities

Upgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of materials across the spectrum of the physical sciences, from life sciences to microelectronics. However, these facility and instrument upgrades come with a significant increase in complexity. Driven by more exacting scientific needs, instruments and experiments become more intricate each year. This increased operational complexity makes it ever more challenging for domain scientists to design experiments that effectively leverage the capabilities of and operate on these advanced instruments. Large language models (LLMs) can perform complex information retrieval, assist in knowledge-intensive tasks across applications, and provide guidance on tool usage. Using x-ray light sources, leadership computing, and nanoscience centers as representative examples, we describe preliminary experiments with a Context-Aware Language Model for Science (CALMS) to assist scientists with instrument operations and complex experimentation. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can conversationally operate scientific instruments. By making information more accessible and acting on user needs, LLMs could expand and diversify scientific facilities’ users and accelerate scientific output.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1974

The impact of space electric field research on atmospheric studies

Space measurements of electric fields have provided instrumentation for measuring atmospheric parameters and a better basis for understanding the electrical coupling between the magnetosphere and the atmosphere. Applications of an incoherent scatter radar (developed for ionospheric electric field research) to the measurement of atmospheric winds and turbulence and of Langmuir double probes (also developed for space research) for measurement of atmospheric electric fields are described. The increased knowledge of magnetospheric electric fields has focused attention on the electrical coupling between the magnetosphere and the atmosphere with conclusions that should considerably modify previous physical concepts in both domains.

Mozer, F. S.↗

NASA NTRS1992

Automating the design of scientific computing software

SINAPSE is a domain-specific software design system that generates code from specifications of equations and algorithm methods. This paper describes the system's design techniques (planning in a space of knowledge-based refinement and optimization rules), user interaction style (user has option to control decision making), and representation of knowledge (rules and objects). It also summarizes how the system knowledge has evolved over time and suggests some issues in building software design systems to facilitate reuse.

Kant, Elaine↗

NASA NTRS2005

Characterization of Meta-Materials Using Computational Electromagnetic Methods

An efficient and powerful computational method is presented to synthesize a meta-material to specified electromagnetic properties. Using the periodicity of meta-materials, the Finite Element Methodology (FEM) is developed to estimate the reflection and transmission through the meta-material structure for a normal plane wave incidence. For efficient computations of the reflection and transmission over a wide band frequency range through a meta-material a Finite Difference Time Domain (FDTD) approach is also developed. Using the Nicholson-Ross method and the Genetic Algorithms, a robust procedure to extract electromagnetic properties of meta-material from the knowledge of its reflection and transmission coefficients is described. Few numerical examples are also presented to validate the present approach.

Deshpande, Manohar↗

NASA NTRS2011

Time Domain Simulations of Arm Locking in LISA

Arm locking is a technique that has been proposed for reducing laser frequency fluctuations in the Laser Interferometer Space Antenna (LISA). a gravitational-wave observatory sensitive' in the milliHertz frequency band. Arm locking takes advantage of the geometric stability of the triangular constellation of three spacecraft that comprise LISA to provide a frequency reference with a stability in the LISA measurement band that exceeds that available from a standard reference such as an optical cavity or molecular absorption line. We have implemented a time-domain simulation of arm locking including the expected limiting noise sources (shot noise, clock noise. spacecraft jitter noise. and residual laser frequency noise). The effect of imperfect a priori knowledge of the LISA heterodyne frequencies and associated "pulling" of an arm locked laser is included. We find that our implementation meets requirements both on the noise and dynamic range of the laser frequency.

Thorpe, J. I.↗

NASA NTRS2014

A Microfabricated 8-40 GHz Dual-Polarized Reflector Feed

Planar antennas based on tightly coupled dipole arrays (also known as a current sheet antenna or CSA) are amenable for use as electronically scanned phased arrays. They are capable of performance nearing a decade of bandwidth. These antennas have been demonstrated in many implementations at frequencies below 18 GHz. This paper describes the implementation using a relatively new multi-layer microfabrication process resulting in a small, 6x6 element, dual-linear polarized array with beamformer that operates from 8 to 40 GHz. The beamformer includes baluns that feed the dual-polarized differential antenna elements and reactive splitter networks that also cover the full frequency range of operation. This antenna array serves as a reflector feed for a multi-band instrument designed to measure snow water equivalent (SWE) from airborne platforms. The instrument has both radar and radiome try capability at multiple frequencies. Scattering-parameter and time-domain measurements have been used to characterize the array feed. Radiation patterns of the antenna have been measured and are compared to simulation. To the best of the authors' knowledge, this work represents the most integrated multi-octave millimeter-wave antenna feed fabricated to date.

current sheet antenna↗

NASA NTRS2020

The Friendly Argument Notation (FAN)

This document defines and explains through examples the Friendly Argument Notation (FAN). FAN builds on previous work investigating text-based ways to express arguments [2, 3]. Its primary intended use is for creating and evaluating arguments about safety-critical systems, especially the types of arguments common within safety and assurance cases [4], but nothing in its design constrains its use to that domain. Compared to existing notations commonly used within this domain (for example [6]), FAN corresponds more closely to traditional argument concepts (for example [1]), allows greater flexibility in expression, provides for including counter-arguments, and requires less knowledge of computer-science-specific concepts. Only time and use will determine how beneficial these differences are in practice. This paper concentrates on showing how FAN looks to someone who is using it manually to develop or assess arguments. A later document will concentrate on providing the information necessary for software tools to be created for FAN.

arugment↗

NASA NTRSDate not supplied

Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗

DOE OSTI2024

Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES): a method for populating knowledge bases using zero-shot learning

Abstract Motivation Creating knowledge bases and ontologies is a time consuming task that relies on manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases, but current approaches rely on extensive training data, and are not able to populate arbitrarily complex nested knowledge schemas. Results Here we present Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES), a Knowledge Extraction approach that relies on the ability of Large Language Models (LLMs) to perform zero-shot learning and general-purpose query answering from flexible prompts and return information conforming to a specified schema. Given a detailed, user-defined knowledge schema and an input text, SPIRES recursively performs prompt interrogation against an LLM to obtain a set of responses matching the provided schema. SPIRES uses existing ontologies and vocabularies to provide identifiers for matched elements. We present examples of applying SPIRES in different domains, including extraction of food recipes, multi-species cellular signaling pathways, disease treatments, multi-step drug mechanisms, and chemical to disease relationships. Current SPIRES accuracy is comparable to the mid-range of existing Relation Extraction methods, but greatly surpasses an LLM’s native capability of grounding entities with unique identifiers. SPIRES has the advantage of easy customization, flexibility, and, crucially, the ability to perform new tasks in the absence of any new training data. This method supports a general strategy of leveraging the language interpreting capabilities of LLMs to assemble knowledge bases, assisting manual knowledge curation and acquisition while supporting validation with publicly-available databases and ontologies external to the LLM. Availability and implementation SPIRES is available as part of the open source OntoGPT package: https://github.com/monarch-initiative/ontogpt.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗

DOE OSTI2023

Real-time correlation of crystallization and segmental order in conjugated polymers

Modulating the segmental order in the morphology of conjugated polymers is widely recognized as a crucial factor for achieving optimal electronic properties and mechanical deformability. However, it is worth noting that the segmental order is typically associated with the crystallization process, which can result in rigid and brittle long-range ordered crystalline domains. To precisely control the morphology, a comprehensive understanding of how highly anisotropic conjugated polymers form segmentally ordered structures with ongoing crystallization is essential, yet currently elusive. To fill this knowledge gap, we developed a novel approach with a combination of stage-type fast scanning calorimetry and micro-Raman spectroscopy to capture the series of specimens with a continuum in the polymer percent crystallinity and detect the segmental order in real-time. Through the investigation of conjugated polymers with different backbones and side-chain structures, we observed a generally existing phenomenon that the degree of segmental order saturates before the maximum crystallinity is achieved. This disparity allows the conjugated polymers to achieve good charge carrier mobility while retaining good segmental dynamic mobility through the tailored treatment. Moreover, the crystallization temperature to obtain optimal segmental order can be predicted based on T g and T m of conjugated polymers. In conclusion, this in-depth characterization study provides fundamental insights into the evolution of segmental order during crystallization, which can aid in designing and controlling the optoelectronic and mechanical properties of conjugated polymers.

36 MATERIALS SCIENCE↗

DOE OSTI2024

XFEL SASE pulses can enhance time-dependent observables

Abstract X-ray free electron lasers (XFELs) have emerged as powerful sources of short and intense x-ray pulses. We propose a simple and robust procedure which takes advantage of the inherent stochasticity of self-amplified stimulated emission (SASE) pulses to enhance the time-resolution and signal strength of the recorded data. Notably, the proposed method is able to enhance the average signal without knowledge of the signal strength of individual shots. Simple metrics for the probe pulses are introduced, such as an effective pulse duration applicable to SASE pulses characterised in the time domain using e.g. an X-band transverse cavity. The approach is evaluated using simulated and real pulse data in the context of ultrafast electron dynamics in a molecule. Utilising H 2 as a model system, we demonstrate the efficacy of the method theoretically, successfully enhancing the predicted nonresonant ultrafast x-ray scattering signal associated with electron dynamics. The method presented is broadly applicable and offers a general strategy for enhancing time-dependent observables at XFELs.

data analysis↗

DOE OSTI2020

Empirical Study of Effect of Dynamic Travel Time Information on Driver Route Choice Behavior

The objective of this paper is to study the effect of travel time information on day-to-day driver route choice behavior. A real-world experimental study is designed to have participants repeatedly choose between two alternative routes for five origin-destination pairs over multiple days after providing them with dynamically updated travel time information (average travel time and travel time variability). The results demonstrate that historical travel time information enhances behavioral rationality by 10% on average and reduces inertial tendencies to increase risk seeking in the gain domain. Furthermore, expected travel time information is demonstrated to be more effective than travel time variability information in enhancing rational behavior when drivers have limited experiences. After drivers gain sufficient knowledge of routes, however, the difference in behavior associated with the two information types becomes insignificant. The results also demonstrate that, when drivers lack experience, the faster less reliable route is more attractive than the slower more reliable route. However, with cumulative experiences, drivers become more willing to take the more reliable route given that they are reluctant to become risk seekers once experience is gained. Furthermore, the effect of information on driver behavior differs significantly by participant and trip, which is, to a large extent, dependent on personal traits and trip characteristics.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1972

Plasma entry into the earth's magnetosphere

Both high- and low-altitude measurements are used to establish the salient features of the three regions presently thought to be the best candidates for the entry of magnetosheath plasma into the magnetosphere, and hence the primal sources of charged particles for the plasma sheet and its earthward termination in the ring current. These three regions are (1) the polar cusps and their extensions into the nighttime magnetosphere, (2) the downstream flanks of the magnetosphere at geocentric radial distances approximately equal to 10 to 50 earth radii along the plasma sheet-magnetosheath interface, and (3) the distant magnetotail at radial distances greater than or approximately equal to 50 earth radii. Present observational knowledge of each of these regions is discussed critically as to evidences for charged particle entry into the magnetosphere from the magnetosheath. The possibility that all three of these magnetospheric domains share an intimate topological relationship is also examined.

Frank, L. A.↗

NASA NTRS1977

Motion cue effects on human pilot dynamics in manual control

Two experiments were conducted to study the motion cue effects on human pilots during tracking tasks. The moving-base simulator of National Aerospace Laboratory was employed as the motion cue device, and the attitude director indicator or the projected visual field was employed as the visual cue device. The chosen controlled elements were second-order unstable systems. It was confirmed that with the aid of motion cues the pilot workload was lessened and consequently the human controllability limits were enlarged. In order to clarify the mechanism of these effects, the describing functions of the human pilots were identified by making use of the spectral and the time domain analyses. The results of these analyses suggest that the sensory system of the motion cues can yield the differential informations of the signal effectively, which coincides with the existing knowledges in the physiological area.

Washizu, K.↗