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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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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding Laser Powder Bed Fusion Surface Roughness

Abstract Surface roughness is a well-known consequence of additive manufacturing methods, particularly powder bed fusion processes. To properly design parts for additive manufacturing, a comprehensive understanding of the inherent roughness is necessary. While many researchers have measured different surface roughness resultant from a variety of parameters in the laser powder bed fusion process, few have succeeded in determining causal relationships due to the large number of variables at play. To assist the community in understanding the roughness in laser powder bed fusion processes, this study explored several studies from the literature to identify common trends and discrepancies amongst roughness data. Then, an experimental study was carried out to explore the influence of certain process parameters on surface roughness. Through these comparisons, certain local and global roughness trends have been identified and discussed, as well as a new framework for considering the effect of process parameters on surface roughness.

Engineering↗
DOE OSTI2020

Systems-level investigation of aqueous batteries for understanding the benefit of water-in-salt electrolyte by synchrotron nanoimaging

Water-in-salt (WIS) electrolytes provide a promising path toward aqueous battery systems with enlarged operating voltage windows for better safety and environmental sustainability. In this work, a new electrode couple, LiV 3 O 8 -LiMn 2 O 4 , for aqueous Li-ion batteries is investigated to understand the mechanism by which the WIS electrolyte improves the cycling stability at an extended voltage window. Operando synchrotron transmission x-ray microscopy on the LiMn 2 O 4 cathode reveals that the WIS electrolyte suppresses the mechanical damage to the electrode network and dissolution of the electrode particles, in addition to delaying the water decomposition process. Because the viscosity of WIS is notably higher, the reaction heterogeneity of the electrodes is quantified with x-ray absorption spectroscopic imaging, visualizing the kinetic limitations of the WIS electrolyte. This work furthers the mechanistic understanding of electrode–WIS electrolyte interactions and paves the way to explore the strategy to mitigate their possible kinetic limitations in three-dimensional architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Toward a Better Understanding of Species Interactions through Network Biology

Within the last decade, there has been an explosion of multi-omics data generated for several microbial systems. At the same time, new methods of analysis have emerged that are based on inferring networks that link features both within and between species based on correlation in abundance. These developments prompt two important questions. What can be done with network approaches to better understand microbial species interactions? What challenges remain in applying network approaches to query the more complex systems of natural settings? Here, I briefly describe what has been done and what questions still need to be answered. Over the next 5 to 10 years, we will be in a strong position to infer networks that contain multiple kinds of omic data and describe systems with multiple species. These applications will open the door for a better understanding and use of microbiomes across a variety of fields.

Microbiology↗
DOE OSTI2018

Understanding Microbiome Stability in a Changing World

Microbiomes underpin biogeochemical processes, sustain the bases of food webs, and recycle carbon and nutrients. Hence, microbes are frontline players in determining ecosystem responses to environmental change. My research team and I investigate the causes and consequences of microbiome stability. Our primary objective is to understand the responses of complex microbiomes to stressors associated with environmental change. This work is important because Earth is changing rapidly and drastically, and these changes are expected to have serious consequences for ecosystems, their inhabiting organisms, and their microbiomes. Therefore, we aim to understand the repercussions of alterations to microbiome structure and functions and to use this information to predict the responses of microbiomes to stressors. This research is critical to prepare for, respond to, and potentially moderate environmental change. We anticipate that the results of our research will contribute toward these goals and will broadly inform management or manipulation of microbiomes toward desired functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Progress in Understanding Short-Range Structure in Nuclei: An Experimental Perspective

High-energy electron scattering is a clean, precise probe for measurements of hadronic and nuclear structure and plays a key role in understanding the role of high-momentum nucleons (and quarks) in nuclei. Jefferson Lab has dramatically expanded our knowledge of the high-momentum nucleons generated by short-range correlations, providing sufficient insight to model much of their impact on nuclear structure in neutron stars and in low- to medium-energy scattering observables, including neutrino oscillation measurements. These short-range correlations also seem related to the modification of the quark distributions in nuclei, and efforts to improve our understanding of the internal structure of these short-distance and high-momentum configurations in nuclei will provide important input on a wide range of high-energy observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Understanding and Enhancing Silicon Nanoparticle Distribution during Electrode Processing

Silicon-dominant anodes are of great interest because of their potential to boost the cell-level energy of state-of-the-art Li-ion batteries. While silicon materials have been extensively studied, understanding interactions at the electrode level has recieved little attention, especially the coating process of Si particles, which plays an equally important role in unlocking the full potential of silicon anodes. Herein, the electrode processing of a Si-dominated anode (52.8 wt%, 3.5–4.5 mAh cm −2 ) is being investigated to understand the relationship of processing on the morphology and properties of Si anodes at the electrode level. It has been found that almost-undetectable Si agglomerates easily form during electrode processing, which grow into largeprotrusions after lithiation and trigger potential internal shorting and self-discharge problems. A facile slurry filtration step is proposed to homogenize the particle distribution within Si-dominant electrodes which improves the electrochemical performance and storage stability of Si-based Li ion batteries.

Wu, Bingbin↗
DOE OSTI2025

Understanding Redox Organic Behavior in Deep Eutectic Solvents: Considerations for Molecular Design

Electrolytes based on deep eutectic solvents (DESs) coupled with redox active organic molecules have shown potential as a versatile and energy dense electrochemical energy storage system. However, progress in these systems has been held back by a lack of understanding of the irregular behavior displayed when redox active organic molecules are transitioned from other solvent systems. In this work, the hydrogen bonding characteristics of a series of redox organic molecules were investigated through infrared spectroscopy and molecular modeling. New understanding of these interactions was then used to explain their electrochemical behavior in a DES electrolyte. A model was used to predict the behavior of new derivatives towards the design of an optimized redox organic-DES system. Hydrogen bonding between the redox molecules and the solvent was found to significantly shift the potential of a redox reaction more positive when a hydrogen bond forms at the redox active site. It was predicted that functionalizing a molecule with electron withdrawing groups to lower the electron density of the redox active functional group lowers the strength of the hydrogen bond and thus alleviates the undesirable potential shift. This hypothesis was demonstrated by the addition of nitro groups to fluorenones.

25 ENERGY STORAGE↗
DOE OSTI2021

An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.

Shen, Xuehao↗
DOE OSTI2019

Theoretical Understanding of the Linear Relationship between Convective Updrafts and Cloud-Base Height for Shallow Cumulus Clouds. Part I: Maritime Conditions

Zheng and Rosenfeld found linear relationships between the convective updrafts and cloud-base height z b using ground-based observations over both land and ocean. The empirical relationships allow for a novel satellite remote sensing technique of inferring the cloud-base updrafts and cloud condensation nuclei concentration, both of which are important for understanding aerosol–cloud–climate interactions but have been notoriously difficult to retrieve from space. In Part I of a two-part study, a theoretical framework is established for understanding this empirical relationship over the ocean. Part II deals with continental cumulus clouds. Using the bulk concept of mixed-layer (ML) model for shallow cumulus, I found that this relationship arises from the conservation law of energetics that requires the radiative flux divergence of an ML to balance surface buoyancy flux. Given a certain ML radiative cooling rate per unit mass Q, a deeper ML (higher z b ) undergoes more radiative cooling and requires stronger surface buoyancy flux to balance it, leading to stronger updrafts. The rate with which the updrafts vary with z b is modulated by Q. The cooling rate Q manifests strong resilience to external large-scale forcing that spans a wide range of climatology, allowing the slope of the updrafts– z b relationship to remain nearly invariant. This causes the relationship to manifest linearity. The physical mechanism underlying the resilience of Q to large-scale forcing, such as free-tropospheric moisture and sea surface temperature, is investigated through the lens of the radiative transfer theory (two-stream Schwarzschild equations) and an ML model for shallow cumulus.

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

How to engineer the unknown: Advancing a quantitative and predictive understanding of plant and soil biology to address climate change

Our basic understanding of carbon cycling in the biosphere remains qualitative and incomplete, precluding our ability to effectively engineer novel solutions to climate change. How can we attempt to engineer the unknown? This challenge has been faced before in plant biology, providing a roadmap to guide future efforts. We use examples from over a century of photosynthesis research to illustrate the key principles that will set future plant engineering on a solid footing, namely, an effort to identify the key control variables, quantify the effects of systematically tuning these variables, and use theory to account for these observations. The main contributions of plant synthetic biology will stem not from delivering desired genotypes but from enabling the kind of predictive understanding necessary to rationally design these genotypes in the first place. Only then will synthetic plant biology be able to live up to its promise.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Towards a more general understanding of the algorithmic utility of recurrent connections

Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such “tag propagation” algorithms perform repeated, local propagation of information and were originally introduced in the context of detecting connectedness, a task that is challenging for feedforward networks. Here, we advance the understanding of the utility of lateral and recurrent computation by first performing a large-scale empirical study of neural architectures for the computation of connectedness to explore feedforward solutions more fully and establish robustly the importance of recurrent architectures. In addition, we highlight a tradeoff between computation time and performance and construct hybrid feedforward/recurrent models that perform well even in the presence of varying computational time limitations. We then generalize tag propagation architectures to propagating multiple interacting tags and demonstrate that these are efficient computational substrates for more general computations of connectedness by introducing and solving an abstracted biologically inspired decision-making task. Our work thus clarifies and expands the set of computational tasks that can be solved efficiently by recurrent computation, yielding hypotheses for structure in population activity that may be present in such tasks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion

Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”

Surface water and pore water samples were collected at five sites along a shoreline transect of the Columbia River, southeastern WA, USA in 2017. This dataset is comprised of (1) high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) and (2) a metadata csv file. The FTICR-MS files are .xml, and the data package includes instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user’s specific needs. The data are associated with the publication “Using community assembly metrics from metacommunity ecology to understand environmental metabolomes” that will be published in Nature Communications (Danczak et al.). The study aimed to investigate gaps in understanding the spatiotemporal organization of environmental metabolomes to improve the ability to predict ecosystem function. Associated sequencing data will be published via NCBI. The access information for NCBI and the publication DOI will be added to this abstract when they are available. Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces

These data are from Bandopadhyay et al., "Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces". This study aims to understand the soil microbial ecology along terrestrial-aquatic interfaces of a freshwater and estuarine region and how it relates to organic matter. We analyzed soil microbial (16S rRNA gene) and organic matter (Fourier-transform ion cyclotron resonance mass spectrometry, FTICR-MS) composition from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie (freshwater) and Chesapeake Bay (estuarine) regions. This dataset includes 16S rRNA gene amplicon data (only processed file types included here) and organic matter composition from FTICR-MS data (raw and processed files included here) from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie and Chesapeake Bay regions. These sites are part of the COMPASS-FME project (https://compass.pnnl.gov/FME/COMPASSFME). File formats and software needed to access files: 16S rRNA gene amplicon data: These files follow the format reported here https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format#updates-in-v1.0.1. As per this format, there are four file types reported: 1. Taxon tables (also called sequence-by-sample or OTU (operational taxonomic unit)/ESV (exact sequence variant) tables) : available in a .txt file format and accessible using TextEdit or MS Excel. 2. Representative sequences (also called consensus sequences) : available in a .fasta format and accessible using TextEdit. 3. Sequencing metadata : available in a MS Excel workbook file format and CSV file format 4. Bioinformatic metadata : available in a MS Excel workbook file format and CSV file format FTICR-MS data: 1. Raw data converted to a processed file with intensities of the peaks in the given samples : available in a MS Excel CSV file format 2. Processed file used in analyses and visualizations (appended as icr_long_) : available in a MS Excel CSV file format 3. Metadata file for ICR features (appended as icr_meta) : available in a MS Excel CSV file format

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Characterization and Understanding of Thermal Transport in Stationary and Moving Particle Beds for Concentrating Solar Power

Concentrating solar power (CSP) coupled with thermal energy storage (TES) is being considered as an appealing solution to deliver stable, dispatchable, and inexpensive electricity generation from renewable solar energy. The heat from the HTF is stored in a TES system that is significantly less expensive and more scalable than electrochemical storage, enabling electricity generation when the sunlight is unavailable. The general concentrating solar thermal technologies are being pushed to higher temperature for higher efficiency and lower cost in a diverse range application in electricity generation (in CSP), industrial heating, and thermochemical fuel productions. Inert and abundant solid particles are becoming increasingly more important for these emerging applications. Heat transfer in both stationary and moving particle beds have been studied for many decades, revealing a great deal of insights on the mechanisms. Yet, there are still several unresolved problems from both fundamental understanding and technological applications points of view. In this Chapter, we will attempt to provide an up-to-date picture of thermal transport in stationary and moving particle beds. In both cases, we will review historical and contemporary developments in the theoretical, computational, and experimental aspects of heat transfer and related behaviors in particle beds. Here, we will discuss both the advancements and limitations of the existing studies and point to future developments towards deeper fundamental understandings and better engineering applications.

14 SOLAR ENERGY↗
DOE OSTI2022

Strengthening the Security of Operational Technology: Understanding Contemporary Bill of Materials

The evolution of cyber-physical infrastructure has made its security more challenging. The last few years have witnessed a convergence of hardware and software segments in various domains, including operational technology (OT) which is responsible for carrying out critical tasks such as monitoring and controlling power grids, nuclear plants, transportation, and emergency services. Both hardware and software encapsulate numerous open source and proprietary subcomponents, making it crucial for end-users to understand the composition of the products they are using. For example, wind turbines incorporate thousands of lines of code (software) used for the turbine's design, planning, operation, and analytics in addition to the numerous hardware subcomponents that construct it. Due to the highly complex nature of software and hardware, knowledge of the components and subcomponents is required to mitigate cyber vulnerabilities and defend against cyberattacks. There has also been a transformation from a traditional linear supply chain into a global, dynamic, diverse, and interconnected system. The digitization of the supply chain makes it easier to find and exploit vulnerabilities. Critical infrastructures (e.g., power grids, oil, natural gas, water, and wastewater) rely on OT to function, and if the OT is compromised, equipment damage and potential interruption of services could result. A significant security measure to protect OT systems from disruption is to develop a supply chain bill of materials (BoM) corresponding to the software and hardware used in OT, along with attestations amongst vendors and asset owners. A supply chain BoM is a proactive way to understand the inherent vulnerabilities in the system and mitigate them in advance of being exploited. BoMs bolster the trust placed in the digital infrastructure and enhance software supply chain security by sustaining the management of component obsolescence and compliance, along with the seclusion of unsafe segments of a specific product. Adopting BoM tools is becoming increasingly important across various government sectors, as evidenced by the recent U.S. executive order on cybersecurity (NIST 2021). This paper aims to classify BoMs based on structure, functionality, component type, and architecture. The work also discusses case studies to further highlight the benefits of BoMs. In addition, it identifies missing pieces in existing BoM implementations so that future research may identify bounds on where it could expect to make improvements and directly enable researchers to identify promising areas for exploration. Further, the authors provide valuable recommendations to tool developers, researchers, and standardizing organizations (policymakers), additionally benefitting critical infrastructure owners and government executives. This aids in paving a path for future work, thereby, providing suggestions to determine a tool for consumers that best suit their needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The East River, Colorado, Watershed: A Mountainous Community Testbed for Improving Predictive Understanding of Multiscale Hydrological–Biogeochemical Dynamics

Core Ideas Development of a 300‐km 2 mountainous headwater testbed began in 2016 in the East River. The testbed can be used to explore how watershed changes impact downgradient water availability and quality. System‐of‐system, scale‐adaptive approaches can potentially improve watershed dynamics simulation. We have new approaches to monitor and simulate water partitioning and system responses. The East River watershed has been developed as a “community” testbed. Extreme weather, fires, and land use and climate change are significantly reshaping interactions within watersheds throughout the world. Although hydrological–biogeochemical interactions within watersheds can impact many services valued by society, uncertainty associated with predicting hydrology‐driven biogeochemical watershed dynamics remains high. With an aim to reduce this uncertainty, an approximately 300‐km 2 mountainous headwater observatory has been developed at the East River, CO, watershed of the Upper Colorado River Basin. The site is being used as a testbed for the Department of Energy supported Watershed Function Project and collaborative efforts. Building on insights gained from research at the “sister” Rifle, CO, site, coordinated studies are underway at the East River site to gain a predictive understanding of how the mountainous watershed retains and releases water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances influence hydrological–biogeochemical watershed dynamics at seasonal to decadal timescales. A system‐of‐systems perspective and a scale‐adaptive simulation approach, involving the combined use of archetypal watershed subsystem “intensive sites” are being tested at the site to inform aggregated watershed predictions of downgradient exports. Complementing intensive site hydrological, geochemical, geophysical, microbiological, geological, and vegetation datasets are long‐term, distributed measurement stations and specialized experimental and observational campaigns. Several recent research advances provide insights about the intensive sites as well as aggregated watershed behavior. The East River “community testbed” is currently hosting scientists from more than 30 institutions to advance mountainous watershed methods and understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Understanding and Controlling Toughening Mechanisms in Nanotube Reinforced Ceramic Coatings

Research in this program is designed to understand mechanical behavior, particularly fracture toughness, in ceramics that are reinforced with carbon nanotubes (CNTs). In the past four years, emphasis was placed on: Synthesizing and characterizing ceramic nanocomposite materials reinforced with both multiwall carbon nanotubes (MWNTs) and single wall nanotubes (SWNTs); and Implementation and analysis of in situ mechanical testing methods to better understand and engineer the critical CNT/ceramic interfaces.

36 MATERIALS SCIENCE↗