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At least 379 records · Page 21

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DOE OSTI2025

Microfluidic droplets with amended culture media cultivate a greater diversity of soil microorganisms

ABSTRACT Uncultivated but abundant soil microorganisms have untapped potential for producing broad ranges of natural products, as well as for bioremediation. However, cultivating soil microorganisms while maintaining a broad microorganism diversity to enable phenotyping and functional analysis of as diverse individual isolates as possible remains challenging. In this study, we developed and tested the ability of several culture media formulations that contain defined soil metabolites or soil extracts to maintain microorganism diversity during culture. We also assessed their performance in microfluidic droplet cultivation where single-soil microorganism isolates were encapsulated and cultivated in picoliter-volume water-in-oil emulsion droplets to enable clonal growth needed for downstream functional analyses. Our results show that droplet cultivation with media supplemented by soil extract or soil metabolites enables the recovery of soil microorganisms with higher diversity (up to 1.5-fold higher richness) compared to bulk cultivation methods. Importantly, 1.7-fold more of less abundant (<1%) phyla and 11-fold more of unique genera were recovered, demonstrating the utility of this method for interrogating highly diverse soil microorganisms for broad ranges of applications. IMPORTANCE Although soil microorganisms hold a significant value in bioproduction and bioremediation, only a small fraction—less than 1%—can be cultured under specific media and cultivation conditions. This indicates that there are ample opportunities in harvesting the diverse environmental microorganisms if isolating and recovering these uncultured microorganisms are possible. This paper presents a new cultivation technique composed of isolating single-soil microorganism cell from anin situsoil microorganism community in microfluidic droplets and conducting in-droplet cultivation in media supplemented by soil extract or soil metabolites. This method enables the recovery of a broader diversity of the original microorganism community, laying the groundwork for a high-throughput phenotyping of these diverse microorganisms from their natural habitats.

Biotechnology & Applied Microbiology↗

DOE OSTI2026

Digital-Threat Bias and Psychological Distance: Barriers to Foundational Digital-Security Improvement

Modern life is held together by a web of digital dependencies that enable and provide delivery of critical services and functions—think the provision of utilities such as electricity and water, as well as our dependency on digital services for social and economic services (internet, communication, etc.). As this dependency grows, the complexity related to the delivery of these critical services increases as well. As complexity increases, the understanding of the risk and impact associated with potential disruption, degradation, or destruction—due to either malicious or non-malicious events of those digitally enabled functions—decreases. One potential explanation for the difficulty to 1) understand the risks faced and 2) address them appropriately and effectively is the abstractness and psychological distance assigned to “digital threat.” The complexity of these digitally enabled services creates a perceived complicatedness; as a result, digital threats are treated differently than similarly devasting (but more easily understood) kinetic or physical threats. How we categorize these threats also matters. Acts of cyber-enabled sabotage to critical infrastructure need to be defined as irregular warfare. By inadequately defining the threat, we compound the problem. Acknowledging this digital-threat bias is foundational to improving the ability to protect critical infrastructure. Using construal-level theory and psychological-distance concepts provides an intriguing starting point to address these issues, to reframe the challenges faced, and pursue more effective critical infrastructure security and defense policy.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2018

An Exchange-Correlation Functional Capturing Bulk Surface and Confinement Physics

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Robust extraction of the proton charge radius from electron-proton scattering data

Background: Extracting the proton charge radius from electron scattering data requires determining the slope of the charge form factor at Q 2 15 of zero. But as experimental data never reach that limit, numerous methods for making the extraction have been proposed, though often the functions are determined after seeing the data which can lead to confirmation bias. Purpose: To find functional forms that will allow for a robust extraction of the input radius for a wide variety of functional forms in order to have confidence in the extraction from upcoming low Q 2 experimental data such as the Jefferson Lab PRad experiment. Method: We create a general framework for inputting form-factor functions as well as various fitting functions. The input form factors are used to generate pseudo-data with fluctuations intended to mimic the binning and random uncertainty of a given set of real data. All combinations of input functions and fit functions can then be tested repeatedly against regenerated pseudo-data. Since the input radius is known, this allows us to find those functions that are robust for radius extractions in an objective fashion. Results: For the range and uncertainty of the PRad data, we find that a two-parameter rational function, a two-parameter continued fraction and the second order polynomial expansion of z can extract the input radius regardless of the input charge form factor function that is used. Conclusions: We have created an easily expandable framework to search for functional forms that allow for a robust extraction of the radius from a given binning and uncertainty of pseudo-data generated from a wide variety of trial functions. This method has enabled a successful search for the best functional forms to extract the radius from the upcoming PRad data, and can be used for other experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

spec-org/gfcc

Green's Function Coupled Cluster Library SPEC GFCC library enables calculations for spectral functions and binding energies of molecular systems using highly scalable implementation of the Green's function coupled cluster (GFCC) approach

Panyala, Ajay↗

DOE OSTI2024

Initial Testing of an In Situ Load Retention Aging Vessel

A thermal aging vessel instrumented with load cells was fabricated. The primary function of the vessel is to continuously monitor the in situ load retention of up to three compressed polymer coupons undergoing thermally accelerated aging under nitrogen. A secondary function is to enable gas sampling of the vessel headspace during thermal aging. Heating of the vessel is achieved using a custom heater jacket. To improve upon our conventional aging study methods which require periodic interruption of aging to perform load testing in an Instron machine at room temperature, this technology aims to automate/facilitate data acquisition/analysis, improve data quality, and enable uninterrupted compression of the polymer which represents the service condition. As an example case to assess functionality of the in situ vessel, the load retention of a siloxane elastomer material additively manufactured by direct-ink-writing (DIW) was measured at three different isothermal aging temperatures for ~1 month. Initial compression of the coupons while near the aging temperature was achieved by temporarily opening the heated vessel to access the interior chamber and manually tightening four nuts to drive the heated compression plate down onto the heated coupons. Initial testing demonstrated achievement of the primary load retention monitoring function. Unfortunately, the vessel leaked which prevented gas sampling; an active purge was used to maintain a nitrogen atmosphere. Welded or otherwise sealed joints, which could be implemented in a future design, would likely eliminate leak paths. To apply time-temperature superposition (TTS), a technique used to provide long-term prediction of the load retention from short-term isothermal data, the load retention needed to be calculated relative to the load at an estimated “equilibrium” time, after most of the transient viscoelastic physical relaxation occurred. The peak load immediately after compression could not be used as the load retention basis for two reasons: (1) age-related changes must be isolated from non-age-related physical relaxation before applying TTS and (2) the manual mechanism used to compress the specimens at the aging temperature was neither smooth nor repeatable which affected the peak load value. To better understand the effect of the mode of initial compression on the measured load, and possibly better estimate “equilibrium” physical relaxation times, systematic stress relaxation experiments were performed using an Instron machine with a thermal chamber. At a given temperature, the DIW polymer was compressed to a fixed strain in either a stepped or continuous manner at two different rates, then held at that strain for 24 hrs. The results indicated that, at a given temperature, the different stress relaxation curves appeared to converge to the same curve at some “equilibrium” time when the non-age-related physical relaxation was mostly complete. Though this observation suggests that the discontinuous manual compression employed by the vessel is feasible, a compression mechanism that is rapid, smooth, and repeatable would enhance its use.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A machining digital twin for hybrid manufacturing

Hybrid manufacturing consisting of metal additively manufactured preforms and computer numerical control (CNC) machining has been established to be an effective method for high material use rates. However, hybrid manufacturing introduces unique challenges. Near-net shape designs are typically selected, which result in a smaller margin for part placement within the stock and stringent requirements for work coordinate system identification. Additionally, less stock material reduces the preform stiffness, which limits the material removal rates during machining. This paper demonstrates a digital twin for CNC machining of a wire arc additively manufactured preform that implements: 1) structured light scanning for stock model identification and tool path generation; 2) a fused filament fabrication apparatus to attach temporary fiducials and scan targets to the preform that enable coordinate system definition for both the CAM and CNC machine; 3) preform and tool tip frequency response function measurements to enable stable milling parameter selection; and 4) post-manufacturing measurements of geometry, surface finish, and structural dynamics to confirm designer intent. These efforts define key components of the machining digital twin for hybrid manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Semi-local Density Functional Approximations for Bulk, Surface, and Confinement Physics

Due to its balance of accuracy and computational cost, density functional theory has become the method of choice for computing the electronic structure and related properties of materials. However, present-day semi-local approximations to the exchange-correlation energy of density functional theory break down for materials containing d and f electrons. In this report we summarize the results of our research efforts within the LDRD 200202 titled "Making density functional theory work for all materials" in addressing this issue. Our efforts are grouped into two research thrusts. In the first thrust, we develop an exchange-correlation functional (BSC functional) within the subsystem functional formalism. It enables us to capture bulk, surface, and confinement physics with a single, semi-local exchange-correlation functional in density functional theory calculations. We present the analytical properties of the BSC functional and demonstrate that the BSC functional is able to capture confinement physics more accurately than standard semi-local exchange-correlation functionals. The second research thrust focusses on developing a database for transition metal binary compounds. The database consists of materials properties (formation energies, ground-state energies, lattice constants, and elastic constants) of 26 transition metal elements and 89 transition metal alloys. It serves as a reference for benchmarking computational models (such as lower-level modeling methods and exchange-correlation functionals). We expect that our database will significantly impact the materials science community. We conclude with a brief discussion on the future research directions and impact of our results.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Solving differential equations with unknown constitutive relations as recurrent neural networks

We solve a system of ordinary differential equations with an unknown functional form of a sink (reaction rate) term. We assume that the measurements (time series) of state variables are partially available, and use a recurrent neural network to “learn” the reaction rate from this data. This is achieved by including discretized ordinary differential equations as part of a recurrent neural network training problem. We extend TensorFlow’s recurrent neural network architecture to create a simple but scalable and effective solver for the unknown functions, and apply it to a fedbatch bioreactor simulation problem. Use of techniques from recent deep learning literature enables training of functions with behavior manifesting over thousands of time steps. Our networks are structurally similar to recurrent neural networks, but differ in purpose, and require modified training strategies.

deep learning↗

DOE OSTI2026

Functional characterization of glycosyltransferases in duckweed to enable predictive biology

Glycosyltransferases (GTs) catalyze the formation of glycosidic linkages to produce almost all complex carbohydrates. This project used a multi-disciplinary, high-throughput (HTP) biochemical and computational biology approach focused on duckweed as a model energy crop, to study carbohydrate metabolic processes. To achieve this, developed and carried out out high-throughput (HTP) functional characterization of plant glycosyltransferases (GTs) role of enzymatic microenvironments be assessed through a combined proteomic and computational biology approach, and the combined data was used to populate deep-learning frameworks to predict plant GT function. Functional validation achieved through this research is being used to assign gene function and study plant processes at the systems level to efficiently link the genome sequence with gene function. Together, the combined approaches used within this study provide a foundation for how computational prediction, in combination with high-throughput functional validation, can be used to study plant processes at the systems level and translate knowledge gained to efficiently link genome sequence with gene function in a species agnostic manner.

09 BIOMASS FUELS↗

DOE OSTI2024

High entropy ceramics for applications in extreme environments

Abstract Compositionally complex materials have demonstrated extraordinary promise for structural robustness in extreme environments. Of these, the most commonly thought of are high entropy alloys, where chemical complexity grants uncommon combinations of hardness, ductility, and thermal resilience. In contrast to these metal–metal bonded systems, the addition of ionic and covalent bonding has led to the discovery of high entropy ceramics (HECs). These materials also possess outstanding structural, thermal, and chemical robustness but with a far greater variety of functional properties which enable access to continuously controllable magnetic, electronic, and optical phenomena. In this experimentally focused perspective, we outline the potential for HECs in functional applications under extreme environments, where intrinsic stability may provide a new path toward inherently hardened device design. Current works on high entropy carbides, actinide bearing ceramics, and high entropy oxides are reviewed in the areas of radiation, high temperature, and corrosion tolerance where the role of local disorder is shown to create pathways toward self-healing and structural robustness. In this context, new strategies for creating future electronic, magnetic, and optical devices to be operated in harsh environments are outlined.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Functional Requirements for the WEIS Toolset to Enable Controls Co-Design of Floating Offshore Wind Turbines

The goal of the new Wind Energy with Integrated Servo-control (WEIS) toolset under development is to provide the offshore wind industry and research communities with an open-source, user-friendly, flexible tool to enable true controls co-design (CCD) of the physical design of a floating offshore wind turbine together with the controller. WEIS will use a multifidelity library of models built on the foundations of WISDEM® and OpenFAST formerly known as FAST). This paper presents the WEIS development plan, including the functional requirements of WEIS (including improvements to WISDEM and OpenFAST) together with associated rationale for their establishment and a qualitative description of the modeling approaches that will be implemented to address these functional requirements. The development of WEIS is a project under the Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control program funded by the U.S. Department of Energy Advanced Research Projects Agency – Energy.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2020

Functional Requirements for the WEIS Toolset to Enable Controls Co-Design of Floating Offshore Wind Turbines: Preprint

The goal of the new Wind Energy with Integrated Servo-control (WEIS) toolset under development is to provide the offshore wind industry and research communities with an open-source, user-friendly, and flexible tool to enable true Controls Co-Design (CCD) of the physical design of a floating offshore wind turbine (FOWT) together with the controller. WEIS will utilize a multifidelity library of models built upon the foundations of WISDEM and OpenFAST (formerly known as FAST). This paper presents the WEIS development plan, including the functional requirements of WEIS (including improvements to WISDEM and OpenFAST) together with associated rationale for their establishment, and a qualitative description of the modeling approaches that will be implemented to address these functional requirements. The development of WEIS is a project under the Aerodynamic Turbines, Lighter and Afloat, with Nautical Technologies and Integrated Servo-control (ATLANTIS) program funded by the U.S. Department of Energy (DOE) Advanced Research Projects Agency - Energy (ARPA-E).

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2022

funcX: Federated Function as a Service for Science

Here, funcX is a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. Unlike centralized FaaS systems, funcX decouples the cloud-hosted management functionality from the edge-hosted execution functionality. funcX's endpoint software can be deployed, by users or administrators, on arbitrary laptops, clouds, clusters, and supercomputers, in effect turning them into function serving systems. funcX's cloud-hosted service provides a single location for registering, sharing, and managing both functions and endpoints. It allows for transparent, secure, and reliable function execution across the federated ecosystem of endpoints-enabling users to route functions to endpoints based on specific needs. funcX uses containers (e.g., Docker, Singularity, and Shifter) to provide common execution environments across endpoints. funcX implements various container management strategies to execute functions with high performance and efficiency on diverse funcX endpoints. funcX also integrates with an in-memory data store and Globus for managing data that may span endpoints. We motivate the need for funcX, present our prototype design and implementation, and demonstrate, via experiments on two supercomputers, that funcX can scale to more than 130000 concurrent workers. We show that funcX's container warming-aware routing algorithm can reduce the completion time for 3,000 functions by up to 61% compared to a randomized algorithm and the in-memory data store can speed up data transfers by up to 3x compared to a shared file system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Effects of O 2 plasma and UV-O 3 assisted surface activation on high sensitivity metal oxide functionalized multiwalled carbon nanotube CH 4 sensors

We present a comparative analysis of UV-O 3 (UVO) and O 2 plasma-based surface activation processes of multi-walled carbon nanotubes (MWCNTs) enabling highly effective functionalization with metal oxide nanocrystals (MONCs). Experimental results from transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy show that by forming COOH (carboxyl), C-OH (hydroxyl), and C=O (carbonyl) groups on the MWCNT surface that act as active nucleation sites, O 2 plasma and UVO-based dry pre-treatment techniques greatly enhance the affinity between MWCNT surface and the functionalizing MONCs. MONCs, such as ZnO and SnO 2 , deposited by atomic layer deposition (ALD) technique, were implemented as the functionalizing material following UVO and O 2 plasma activation of MWCNTs. In conclusion, a comparative study on the relative resistance changes of O 2 plasma and UVO activated MWCNT functionalized with MONC in the presence of 10 ppm methane (CH 4 ) in air, is presented as well.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Controlling the metal to semiconductor transition of MoS 2 and WS 2 in solution

Lithiation-exfoliation produces single to few-layered MoS 2 and WS 2 sheets dispersible in water. However, the process transforms them from the pristine semiconducting 2H phase to a distorted metallic phase. Recovery of the semiconducting properties typically involves heating of the chemically exfoliated sheets at elevated temperatures. Therefore, it has been largely limited to sheets deposited on solid substrates. We report the dispersion of chemically exfoliated MoS 2 sheets in high boiling point organic solvents enabled by surface functionalization and the controllable recovery of their semiconducting properties directly in solution. Ultimately, this process connects the scalability of chemical exfoliation with the simplicity of solution processing, enabling a facile method for tuning the metal to semiconductor transitions of MoS 2 and WS 2 within a liquid medium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Phylogenetic organization in the assimilation of chemically distinct substrates by soil bacteria

Soils are among the most biodiverse habitats on earth and while the species composition of microbial communities can influence decomposition rates and pathways, the functional significance of many microbial species and phylogenetic groups remains unknown. If bacteria exhibit phylogenetic organization in their function, this could enable ecologically meaningful classification of bacterial clades. We show non-random phylogenetic organization in the rates of relative carbon assimilation for both rapidly mineralized substrates (amino acids and glucose) assimilated by many microbial taxa and slowly mineralized substrates (lipids and cellulose) assimilated by relatively few microbial taxa. When mapped onto bacterial phylogeny using ancestral character estimation this phylogenetic organization enabled the identification of clades involved in the decomposition of specific soil organic matter substrates. Phylogenetic organization in substrate assimilation could provide a basis for predicting the functional attributes of uncharacterized microbial taxa and understanding the significance of microbial community composition for soil organic matter decomposition.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Strain Enhanced Functionality in a Bottom-Up Approach Enabled 3D Super-Nanocomposites

The ability to control nanoparticle size, concentration, and distribution in epitaxial nanocomposite films has been a formidable challenge in the synthesis of nanostructured composite materials. In this paper, a novel 3D super-nanocomposite (3D-sNC) architecture is successfully demonstrated by integrating superlattice and vertically aligned nanocomposite structures. In the 3D-sNC architecture, the feature size and distribution of the nanocylinders such as the height/lateral dimension and the vertical/lateral spacing of nanocylinders can be precisely controlled. The microstructure parameters such as nanocylinder height and spacing modulated interfacial area control the lattice strain, which further tunes the magnetotransport property. These results demonstrate that 3D-sNC is a simple and yet effective architecture to achieve controlled functionalities via the precise control of nanocylinder size, spacing, concentration, and distribution. Lastly, such a 3D-sNC structure can be used to design advanced nanostructures with desired physical properties for a variety of material systems.

36 MATERIALS SCIENCE↗