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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Persistent Elevated Soot Emissions Induced by Clustered Stochastic Preignition Events

Stochastic Preignition (SPI) is an abnormal combustion phenomenon that can occur in spark-ignition engines particularly under high-load operation. SPI is characterized by uncontrolled initiation of combustion prior to spark discharge, an abnormal combustion process that can lead to severe knock events and significant engine damage. SPI has been associated with fuel properties, lubricant composition, and engine design and operation. Here, in this work, a single-cylinder test engine with a dry-sump oil system was utilized to study the SPI response of E10 and E25 fuels with a range of Reid Vapor Pressure (RVP). An automated test procedure was employed, consisting of ten square-waved load profile segments, with each segment composed of 5 min of low-load operation followed by 25 min of sustained high-load operation. These tests were replicated across multiple days of testing including a lubricant triple flush between tests, and an online Fuel in Oil diagnostic measurement. Exhaust particulate emissions were continuously measured by an AVL microsoot sensor (MSS). Elevated particulate matter emissions were observed to occur concurrently with SPI events as blooms of soot. Particularly after clustered events (i.e., multiple SPI cycles occurring within 10 consecutive engine cycles), high soot emissions were observed to persist over several days of sequential operation despite daily lubricant changes, a complete warm-up procedure, and sustained low-load operation between test segments. This result implies that the particulate emissions trends may be dominated by deposit-based effects, where higher load operation is needed to alter deposition and formation processes. The observed soot blooms were also found to correspond to a reduction in the engine fueling and the fuel engine oil dilution rate despite the engine exhaust remaining at stoichiometric exhaust operation. These observations suggest that post-SPI events, pathways for lubricant migration and consumption into the combustion chamber may occur until these pathways are closed from deposit formation or ring dynamics during extended operation. These observed sooting propensity persisted with all fuels tests, but a linear correlation was observed between the summation of soot and particulate matter index (PMI) value for each fuel as well as SPI events, proving that PMI is a crucial fuel property for reducing SPI.

Splitter, Derek [Oak Ridge National Laboratory (OR↗
DOE OSTI2023

Detectors and diagnostics for multiprobe radiography using high-energy short-pulse lasers

Multiprobe radiography requires the following diagnostic capabilities at minimum: radiographic source diagnostics, spectroscopy, imaging, and tomography diagnostics. Depending on the repetition rate of the radiation sources, the diagnostics may be a single-shot diagnostic, such as photographic (radiochromic and X-ray films for high energy photons) films, or a multiple-shot diagnostic for repetitive source operations, such as a high-speed framing camera. Due to the drastically different detector physics of electrons, photons at different energies (keV to 10s of MeV in the radiography context), heavy ions such as protons, alphas, and neutrons, see, for example, Ref. [1, 2] for an overview, different types or configurations of detectors and constructions may be required for multiprobe radiography applications. Some of the common detector metricsinclude, independent of the particle/photon species, sensitivities or efficiency, energy resolution, spatial or temporal resolutions and others. Some unique detection scenarios arise in a multiprobe radiography setting, for example, crosstalk mitigation and particle identification (ID) when X-ray and higher energy photons, relativistic electrons, neutrons, other hadrons, and heavy particles coexist at the detector location.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Lean-Stratified Combustion System with Miller Cycle for Downsized Boosted Application - Part I

Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio, and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. A high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the first to two papers describing the development of a combustion system combining lean-stratified combustion with Miller cycle for downsized boosted applications. The work was completed under a multi-year US DOE project. The goal was to define a light-duty engine package capable of achieving a 35% fuel economy improvement at US Tier 3 emission standards over a naturally aspirated stoichiometric baseline vehicle. A multi-mode combustion system was developed enabling highly efficient lean-stratified operation at light-load and stoichiometric Miller-cycle operation at mid- to highloads. Some of the unique challenges in synergistically combining the two concepts are highlighted in this paper. Here, a central direct-injection four-valve layout was designed with high-tumble ports and a bowl-in-piston capable of stable operation under highly dilute (lean plus EGR) mixtures when properly matched to fuel spray characteristics, a multiple-injection strategy, and a high-energy ignition system. Other challenges specific to meeting exhaust emissions requirements with a high-efficiency engine are also explored in this study. In this Part 1 of the paper, the single-cylinder combustion system design, analysis, and testing is described. Multicylinder engine system design, analysis and development is described in Part 2 of the paper.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Multiplicity and rapidity dependence of $\textrm{K}^{*}(\mathrm {{\textbf {892}}})^{0}$ and $\mathrm {\phi ({\textbf {1020}})}$ production in p–Pb collisions at $\sqrt{s_{\textrm{NN}}} =$ 5.02 TeV

The transverse-momentum (p T ) spectra of K*(892) 0 and Φ(1020) measured with the ALICE detector up to p T = 16 GeV/c in the rapidity range -1.2 < y < 0.3, in p–Pb collisions at the center-of-mass energy per nucleon–nucleon collision $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV are presented as a function of charged particle multiplicity and rapidity. The measured p T distributions show a dependence on both multiplicity and rapidity at low p T whereas no significant dependence is observed at high p T . A rapidity dependence is observed in the p T -integrated yield (dN/dy), whereas the mean transverse momentum ($\langle$p T $\rangle$) shows a flat behavior as a function of rapidity. The rapidity asymmetry (Y asym ) at low p T (< 5 GeV/c) is more significant for higher multiplicity classes. At high p T , no significant rapidity asymmetry is observed in any of the multiplicity classes. Both K*(892) 0 and Φ(1020) show similar Y asym . The nuclear modification factor (Q CP ) as a function of p T shows a Cronin-like enhancement at intermediate p T , which is more prominent at higher rapidities (Pb-going direction) and in higher multiplicity classes. At high p T (> 5 GeV/c), the Q CP values are greater than unity and no significant rapidity dependence is observed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Navigating Economies of Scale and Multiples for Nuclear-Powered Data Centers and Other Applications with High Service Availability Needs

Nuclear energy is increasingly being considered for such targeted energy applications as data centers in light of their high capacity factors and low carbon emissions. This paper focuses on assessing the tradeoffs between economies of scale versus mass production to identify promising reactor sizes to meet data center demands. A framework is then built using the best cost estimates from the literature to identify ideal reactor power sizes for the needs of the given data center. Results should not be taken to be deterministic but highlight the variability of ideal reactor power output against the required demand. While certain advocates claim that with the gigawatts of clean, firm energy needed, large plants are ideal, others advocate for SMRs that can be deployed in large quantities and reap the benefits from learning effects. The findings of this study showcase that identifying the optimal size for a reactor is likely more nuanced and dependent on the application and its requirements. Overall, the study does show potential economic promise for coupling nuclear reactors to data centers and industrial heat applications under certain key conditions and assumptions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

High-throughput spin-bath characterization of spin defects in semiconductors

Detailed knowledge of the local environments of spin defects in semiconductors, such as nitrogenvacancy (NV) centers in diamond or divacancies in silicon carbide, is crucial for optimizing control and entanglement protocols in quantum sensing and information applications. However, at present a direct experimental characterization of individual defect environments is not scalable, as conventional spin-bath measurements are time consuming and difficult to automate. Achieving high-throughput characterization requires short experiments to probe the spin bath. However, with fewer and noisier measurements, the inverse problem of recovering spin-bath properties from measured data becomes ill posed, with multiple spin baths having a high likelihood of yielding the same data. In this work, we present a set of computational tools to resolve the ill-posed inverse problem of recovering the atomic positions and hyperfine couplings of random nuclei surrounding spin defects from sparse, noisy experimental coherence data, which can be obtained in hours. Here, we use a trans-dimensional Bayesian approach that incorporates ab initio data to yield full posterior distributions over nuclear spin environments, enabling robust recovery from limited data. We also provide practical tools and guidelines to determine the limits of detectability for hyperfine couplings under specific dynamical decoupling sequences and sampling conditions. In addition, we demonstrate how the tools developed here, in combination with ab initio simulations of spin baths, can guide the design of efficient experimental protocols for application-specific high-throughput screening. To showcase the utility of our approach, we apply it to design fast dynamical decoupling experiments to characterize the spin baths often individual NV centers in diamond. While the primary focus is on accelerating spin-bath characterization of spin defects, this Bayesian approach also lays the foundation for digital-twin studies of spin defects, where a virtual model of the spin-defect system evolves in real time with ongoing experimental measurements. Together, the set of tools we designed and applied paves the way for scalable deployment of spin defects in semiconductors for quantum sensing and information applications.

Bayesian methods↗
DOE OSTI2021

Multiple Reaction Pathways for the Oxygen Evolution Reaction May Contribute to IrO 2 (110)’s High Activity

Density functional theory calculations in conjunction with statistical mechanical arguments are performed on the rutile IrO 2 (110) facet in order to characterize multiple reaction pathways on the surface at the highest active limit (the stoichiometric surface with all metal sites available) and at the lowest active limit (the oxygen-terminated surface). Alternative pathways to the oxygen evolution reaction (OER) are found, with multiple pathways determined at each step of the four proton-coupled electron transfer reaction. Of particular interest is the detailed characterization of a co-adsorption pathway utilizing neighboring, adsorbed O, OH species in order to evolve oxygen; activation energies of this pathway are <0.5 eV and therefore easily surmountable at the high operating potentials of OER. We also determined that surface Ir atoms can potentially participate in deprotonating an OOH* intermediate; the activation energy to this is 0.67 eV on the oxygen-terminated surface. These theoretical findings explain in part the high activity present in iridium oxide catalysts and also provide insight into the mechanistic pathways available on metal oxide catalysts, which may require the concerted interaction of nearest neighbor co-adsorbates to produce chemicals of interest.

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

CommBench: Micro-Benchmarking Hierarchical Networks with Multi-GPU, Multi-NIC Nodes

Modern high-performance computing systems have multiple GPUs and network interface cards (NICs) per node. The resulting network architectures have multilevel hierarchies of subnetworks with different interconnect and software technologies. These systems offer multiple vendor-provided communication capabilities and library implementations (IPC, MPI, NCCL, RCCL, OneCCL) with APIs providing varying levels of performance across the different levels. Understanding this performance is currently difficult because of the wide range of architectures and programming models (CUDA, HIP, OneAPI). We present CommBench, a library with cross-system portability and a high-level API that enables developers to easily build microbenchmarks relevant to their use cases and gain insight into the performance (bandwidth & latency) of multiple implementation libraries on different networks. We demonstrate CommBench with three sets of microbenchmarks that profile the performance of six systems. Our experimental results reveal the effect of multiple NICs on optimizing the bandwidth across nodes and also present the performance characteristics of four available communication libraries within and across nodes of NVIDIA, AMD, and Intel GPU networks.

Hidayetoglu, Mert↗
DOE OSTI2020

Sulfurized Polyacrylonitrile for High-Performance Lithium–Sulfur Batteries: In-Depth Computational Approach Revealing Multiple Sulfur’s Reduction Pathways and Hidden Li + Storage Mechanisms for Extra Discharge Capacity

Like no other sulfur host material, polyacrylonitrile-derived sulfurized carbon (SPAN) promises improved electrochemical performance for lithium–sulfur batteries, based on its compatibility with carbonate solvents and ability to prevent self-discharge and shuttle effect. However, a complete understanding of the SPAN’s lithiation mechanism is still missing because its structural features vary widely with synthesis conditions, and its electrochemical performance deviates from elemental sulfur. This study continues our research on the elucidation of the SPAN’s structural characteristics and lithiation mechanisms via computational approaches. Here, our models reproduce most experimental data regarding carbon’s graphitization level and conjugated ordering, sulfur–carbon covalent bonding, sulfur loading, and elemental composition. Our simulations emulate the discharge voltage observed in experiments for the first discharge, which reveals that sulfur follows multiple reduction pathways based on its interaction with the carbon backbone. Sulfur reduction takes place above 1.0 V vs Li/Li + mostly in the SPAN-like material, with no long-chain lithium polysulfide formation. Below 1.0 V vs Li/Li + , the backbone’s electrochemical activity occurs via multiple C–Li and N–Li interactions, mostly with edge carbon atoms and pyridinic nitrogen. Moreover, we identify Li + binding sites throughout the graphitized backbone that might lead to prohibited energy costs for Li + deintercalation, which may explain the irreversible capacity loss between the first and second discharges. This work improves understanding of lithiation mechanisms in sulfurized carbon, which is useful for rationally designing SPAN synthesis pathways tailored to increase sulfur loading and enhanced electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2020

Accelerated Climate Model for Energy (ACME): Ocean and Sea-Ice Processes

The primary goal of this project was to understand the role of the ocean and sea-ice components in the evolution of the climate in both a high-resolution fully-coupled 1850 preindustrial control and present day transient climate simulations run using the Energy Exascale Earth System Model (E3SM), formerly known as the Accelerated Climate Model for Energy (ACME). Two distinct approaches to the initialization of the present day transients were tested: in the first, an ensemble of three transients used atmospheric reanalysis forced 0.1-degree ocean/sea-ice states, while a fourth transient was branched off the preindustrial control. Biases from the control were inherited by its successor transient, in particular, sea surface temperatures (SSTs) at high latitudes were too warm and too much northward meridional heat transport occurred in the North Atlantic Ocean. SSTs in the Northern Hemisphere and Atlantic meridional heat transport increased in the transients initialized from the ocean/sea-ice simulation over a 40-50 year period to largely resemble the transient branched off the control simulation. Excessive absorbed solar radiation (ASR) is considered to be responsible for the SST biases as well as the formation of mode waters in lighter density classes than in reality both in the Southern Ocean and the North Atlantic Ocean subtropical gyre. These mode waters ventilate the thermocline waters to the north of their formation sites explaining the excessive Atlantic meridional heat transport and some of the warming in the high-latitude North Atlantic Ocean after multiple decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Material Architectures to Integrate Multiple Reactor Functions for Fission Batteries

It is necessary for Advanced Reactors to have highly advanced engineered material systems that can combine multiple functions to save weight and cost. Metamaterial structures can be used to achieve this function. Material properties that could feasibly be combined were identified and explored in the literature. They were then proposed for future studies gauging the effectiveness of these proposals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advanced Multiscale Microscopy Characterization of High Burnup LWR UO 2 Before and After LOCA Testing

Previous microscopy work within the campaign has observed increased porosity coupled with subgrain formation in the mid-radial region of the fuel. However, examinations of high burnup fuel taken from multiple reactors with different operating conditions have shown that this structure can move radially inward depending on the fuel operating conditions. It is currently theorized that inter- and intragranular fission gas bubble nucleation is precursory to the grain subdivision observed in the mid-radial and central regions of the fuel. Characterization of samples after loss-of-coolant accident (LOCA) testing has revealed that these restructured regions with a high density of bubbles and subgrains pulverize during the transient test. It appears that the increase in fission gas bubbles coupled with grain subdivision renders the fuel mechanically weaker during a LOCA transient and thus susceptible to fuel fragmentation relocation and dispersal (FFRD). Work this past fiscal year has prioritized understanding this behavior by using advanced microscopy to investigate fission gas behavior in the as-irradiated and post-LOCA state. Additional work has been performed to verify the theory described above by analyzing multiple post-LOCA optical micrographs and comparing that to as-irradiated microstructural data. This document reports progress in the post-irradiation characterization of high burnup nuclear fuel with emphasis on the restructured fuel regions, particularly how microstructural features influence FFRD and fission gas release behavior in LOCA conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Climate Vulnerability Assessment and Resilience Planning for Idaho National Laboratory

Idaho National Laboratory’s (INL’s) mission is to discover, demonstrate, and secure innovative nuclear energy solutions, other clean energy options, and critical infrastructure. This INL’s Climate Vulnerability Assessment and Resilience Plan (VARP) was developed to enable and sustain that mission while ensuring the viability of operations considering expected climate change impacts. The VARP was developed according to the narrative requirements from the “Vulnerability Assessment and Resilience Planning Guidance, Version 1.2” document issued in February 2022. A prescribed process was used to identify mission-critical systems and components, determine historical and expected climate impacts, and develop resilient solutions. Experts from across INL, including operations staff, researchers, and climate scientists supplied input to the process. Analyses of climate modeling sources revealed that under scenarios of higher and lower greenhouse gas emissions (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5), INL anticipates an increase in climate hazards, including drought, heat waves, wildfire, and precipitation. Increased frequency and duration of climatic hazards forecasts high impacts on certain mission-critical asset and infrastructure types. Utilizing the VARP Risk Assessment Tool, projected high climate hazard impacts across multiple asset and infrastructure types at the INL include energy generation and distribution systems, Site buildings, specialized or mission-critical equipment, and transportation and fleet infrastructure. Some of these mission-critical asset and infrastructure types maintain high adaptive capacity to climatic changes; however, others may need additional adaptive capacity to withstand increased frequency and duration of climate hazards. INL identified close to 300 resilient solutions that were consolidated into 11 solution categories to be tracked in the Department of Energy Sustainability Dashboard. The identified solutions are a starting point for future project development and analysis. These data are intended to inform decision makers on climate issues and potential solutions across INL and associated communities. The VARP is not intended to be a budget tool or project decision document on its own, but rather one of many tools used by decision makers to establish resilient priorities. This initial document provides the framework and foundation to resilient solutions. In the coming years, each solution needs to be fully developed, costed, and prioritized based on mission-critical risk and funding priorities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-resolution ion mobility based on traveling wave structures for lossless ion manipulation resolves hidden lipid features

Abstract High-resolution ion mobility (resolving power > 200) coupled with mass spectrometry (MS) is a powerful analytical tool for resolving isobars and isomers in complex samples. High-resolution ion mobility is capable of discerning additional structurally distinct features, which are not observed with conventional resolving power ion mobility (IM, resolving power ~ 50) techniques such as traveling wave IM and drift tube ion mobility (DTIM). DTIM in particular is considered to be the “gold standard” IM technique since collision cross section (CCS) values are directly obtained through a first-principles relationship, whereas traveling wave IM techniques require an additional calibration strategy to determine accurate CCS values. In this study, we aim to evaluate the separation capabilities of a traveling wave ion mobility structures for lossless ion manipulation platform integrated with mass spectrometry analysis (SLIM IM-MS) for both lipid isomer standards and complex lipid samples. A cross-platform investigation of seven subclass-specific lipid extracts examined by both DTIM-MS and SLIM IM-MS showed additional features were observed for all lipid extracts when examined under high resolving power IM conditions, with the number of CCS-aligned features that resolve into additional peaks from DTIM-MS to SLIM IM-MS analysis varying between 5 and 50%, depending on the specific lipid sub-class investigated. Lipid CCS values are obtained from SLIM IM ( TW(SLIM) CCS) through a two-step calibration procedure to align these measurements to within 2% average bias to reference values obtained via DTIM ( DT CCS). A total of 225 lipid features from seven lipid extracts are subsequently identified in the high resolving power IM analysis by a combination of accurate mass-to-charge, CCS, retention time, and linear mobility-mass correlations to curate a high-resolution IM lipid structural atlas. These results emphasize the high isomeric complexity present in lipidomic samples and underscore the need for multiple analytical stages of separation operated at high resolution. Graphical abstract

Reardon, Allison R. (ORCID:0000000165830134)↗
DOE OSTI2023

Integrated Research Infrastructure Architecture Blueprint Activity (Final Report 2023)

The complexity of scientific pursuits is increasing rapidly with aspects that require dynamic integration of experiment, observation, theory, modeling, simulation, visualization, machine learning (ML), artificial intelligence (AI), and analysis. Research projects across the Department of Energy (DOE) are increasingly data and compute intensive. Innovative research teams are accelerating the pace of discovery by using high-performance computational and data tools in their research workflows and leveraging multiple research infrastructures. Additionally, several recent high-level U.S. government reports underscore the necessity of a new advanced computing ecosystem for international competitiveness and national security. International competitors are moving forward with major research infrastructure integration efforts that seek to capture a competitive advantage in the global innovation race. Owing to its unparalleled constellation of world-class experimental and observational facilities and high-performance and extreme-scale computational, data, and networking infrastructure, DOE is positioned to be a global leader in this new era of integrated science. However, this new integration paradigm will demand continuing evolution to ensure the U.S. remains a global leader in research and innovation. The DOE Office of Science (SC) has seized on the strategic importance of integration and has adopted a vision for Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. To respond to the evolving computational requirements of research and the competitive international innovation landscape, experimental facilities could be connected with high performance computing resources for near real-time analysis, and resources should be provided for merging enormous and diverse data for AI/ML techniques and analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Low-Frequency Correlated Charge-Noise Measurements Across Multiple Energy Transitions in a Tantalum Transmon

Transmon qubits fabricated with tantalum metal have been shown to possess energy relaxation times greater than 400 𝜇⁢s and, as such, present an attractive platform for high precision, correlated noise studies across multiple higher-energy transitions. Tracking the multilevel fluctuating qudit frequencies with a precision enabled by the high coherence of the device allows us to extract the charge offset and quasiparticle dynamics. We observe qualitatively different charge-offset behavior in the tantalum device than those measured in previous low-frequency charge-noise studies. In particular, we find the charge-offset dynamics are dominated by rare, discrete jumps between a finite number of quasistationary charge configurations, a previously unobserved charge-noise process in superconducting qubits.

3-dimensional systems↗
DOE OSTI2022

Mechanochemically Assisted Synthesis of High-Entropy Layer-Structured Dittmarite Analogues

High-entropy solid-solution materials, especially layered ones incorporating five or more near-equimolar components into single-phase crystal structures, may spark functional synergism toward the electrochemistry area because of their unique antisite disordering structures and the synergistic effect of multiple active sites. Herein, high-entropy dittmarite analogues (HEDAs) were synthesized via a mechanochemistry-assisted hydrothermal method. Furthermore, the as-prepared HEDAs have single dittmarite phases with five homogeneously distributed metal elements, exhibiting enhanced activities in oxygen evolution catalysis compared to the single metal counterparts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The temperature-dependent conformational ensemble of SARS-CoV-2 main protease (M pro )

The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or M pro , is a promising target for the development of novel antiviral therapeutics. Previous X-ray crystal structures of M pro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded M pro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these data sets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a perturbation-dependent conformational landscape for M pro , including a mobile zinc ion interleaved between the catalytic dyad, mercurial conformational heterogeneity at various sites including a key substrate-binding loop, and a far-reaching intramolecular network bridging the active site and dimer interface. Our results may inspire new strategies for antiviral drug development to aid preparation for future coronavirus pandemics.

59 BASIC BIOLOGICAL SCIENCES↗