SEARCH · Engineering Papers

Results for “Virtualization”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,189 records · Page 66

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Chemoselective and Site-Selective Reductions Catalyzed by a Supramolecular Host and a Pyridine–Borane Cofactor

Supramolecular catalysts emulate the mechanism of enzymes to achieve large rate accelerations and precise selectivity under mild and aqueous conditions. While significant strides have been made in the supramolecular host-promoted synthesis of small molecules, applications of this reactivity to chemoselective and site-selective modification of complex biomolecules remain virtually unexplored. We report here a supramolecular system where coencapsulation of pyridine-borane with a variety of molecules including enones, ketones, aldehydes, oximes, hydrazones, and imines effects efficient reductions under basic aqueous conditions. Furthermore, upon subjecting unprotected lysine to the host-mediated reductive amination conditions, we observed excellent ε-selectivity, indicating that differential guest binding within the same molecule is possible without sacrificing reactivity. Inspired by the post-translational modification of complex biomolecules by enzymatic systems, we then applied this supramolecular reaction to the site-selective labeling of a single lysine residue in an 11-amino acid peptide chain and human insulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Diffractive Imaging of Conical Intersections Amplified by Resonant Infrared Fields

The fate of virtually all photochemical reactions is determined by conical intersections. These are energetically degenerate regions of molecular potential energy surfaces that strongly couple electronic states, thereby enabling fast relaxation channels. Their direct spectroscopic detection relies on weak features that are often buried beneath stronger, less interesting contributions. For azobenzene photoisomerization, a textbook photochemical reaction, we demonstrate how a resonant infrared field can be employed during the conical intersection passage to significantly enhance its coherence signatures in time-resolved Xray diffraction while leaving the product yield intact. Furthermore, this transition-state amplification holds promise to bring signals of conical intersections above the detection threshold.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Framework-Topology-Controlled Singlet Fission in Metal–Organic Frameworks

Singlet fission (SF) has been explored as a viable route to improve photovoltaic performance by producing more excitons. Efficient SF is achieved through a high degree of interchromophoric coupling that facilitates electron super exchange to generate triplet pairs. However, strongly coupled chromophores often form excimers that can serve as an SF intermediate or a low-energy trap site. The succeeding decoherence process, however, requires an optimum electronic coupling to facilitate the isolation of triplet production from the initially prepared correlated triplet pair. Conformational flexibility and dielectric modulation can provide a means to tune the SF mechanism and efficiency by modulating the interchromophoric electronic interaction. Such a strategy cannot be easily adopted in densely stacked traditional organic solids. Here, we show that the assembly of the SF-active chromophores around well-defined pores of solution-stable metal-organic frameworks (MOFs) can be a great platform for a modular SF process. A series of three new MOFs, built out from 9,10-bis(ethynylenephenyl)anthracene-derived struts, show a topology-defined packing density and conformational flexibility of the anthracene core to dictate the SF mechanism. Various steady-state and transient spectroscopic data suggest that the initially prepared singlet population can prefer either an excimer-mediated SF or a direct SF (both through a virtual charge-transfer (CT) state). Finally, these solution-stable frameworks offer the tunability of the dielectric environment to facilitate the SF process by stabilizing the CT state. Given that MOFs are a great platform for various photophysical and photochemical developments, generating a large population of long-lived triplets can expand their utilities in various photon energy conversion schemes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization

High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to 10 elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation

High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of large-scale computational discovery carried through experimental validation remain scarce, especially for materials with product applicability. In this paper, we demonstrate how this vision became reality by first combining state-of-the-art artificial intelligence (AI) models and traditional physics-based models on cloud high performance computing (HPC) resources to quickly navigate through more than 32 million candidates and predict around half a million potentially stable materials. Focusing on solid-state electrolytes for battery applications, our discovery pipeline further identified 18 promising candidates with new compositions and rediscovered a decade’s worth of collective knowledge in the field as a byproduct. By employing around one thousand virtual machines in the cloud, this process took less than 80 hours. We then synthesized and experimentally characterized the structures and conductivities of our top candidates, the Na x Li 3-x YCl 6 (0.5 ≤ x ≤ 2.5) series, demonstrating the potential of these compounds to serve as solid electrolytes. Additional candidate materials are currently under experimental investigation that could offer more examples of the computational discovery of new phases of Li- and Na-conducting solid electrolytes. We believe this unprecedented approach of synergistically integrating AI models and cloud HPC not only accelerates materials discovery but also showcases the potency of AI-guided experimentation in unlocking transformative scientific breakthroughs with real-world applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Structure and Synthesizability of Iron–Sulfur Metal–Organic Frameworks

Sulfur-based metal–organic frameworks (MOFs) and coordination polymers (CPs) are an emerging class of hybrid materials that have received growing attention due to their magnetic, conductive, and catalytic properties with potential applications in electrocatalysis and energy storage. In this work, we report a high-throughput virtual screening protocol to predict the synthesizability of candidate metal–sulfur MOFs/CPs by computing the thermodynamically stable structures resulting from a particular combination of metal cluster, linker, cation, and synthetic conditions. Free energies are computed by using all-atom classical mechanical thermodynamic integration. Low-free-energy structures are refined using ab initio density functional theory, and pair distribution functions and powder X-ray diffraction patterns are calculated to complement and guide experimental structure determination. We validate the computational approach by retrospective predictions of the stable structure produced by experimental syntheses, and a subsequent screen predicts Fe 4 S 4 -BDT–TPP as a new thermodynamically stable one-dimensional (1D) CP comprising a redox-active Fe 4 S 4 cluster, a 1,4-benzenedithiolate (BDT) linker, and a tetraphenylphosphonium (TPP) countercation. Furthermore, this material is experimentally synthesized, and the 1D chain structure of the crystal is confirmed using microcrystal electron diffraction. The computational screening pipeline is generically transferable to neutral and ionic MOFs/CPs comprising arbitrary metal clusters, linkers, cations, and synthetic conditions, and we make it freely available as an open source tool to guide and accelerate the discovery and engineering of novel porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Shell Thickness and Heterogeneity Dependence of Triplet Energy Transfer between Core–Shell Quantum Dots and Adsorbed Molecules

Quantum dot (QD)-sensitized triplet energy transfer (TET) has found promising applications in photon upconversion and photocatalysis. However, the underlying mechanism of TET in the QD-acceptor complex remains unclear despite the well-developed TET theory for the molecular donor–acceptor systems. Herein, the coupling strength of TET from CdSe/CdS core–shell QDs to 9-anthracene carboxylic acid (ACA) was studied by measuring the TET rate as a function of shell thickness with time-resolved photoluminescence. The change of TET-coupling strength with increasing shell thickness was further compared to those of electron and hole transfers from QDs so that we could test whether QD-sensitized TET is mediated by the charge transfer virtual state and can be considered as simultaneous electron and hole transfers as in molecular donor–acceptor systems. The measured coupling strength of TET from the CdSe/CdS QD decreases exponentially with the CdS shell thickness r: |V|(r) = |V|(0)e –βr , with an exponential decay factor β of 0.19 Å –1 , which is smaller than the sum of the measured decay factors for electron transfer to methyl viologen (0.18 Å –1 ) and hole transfer to phenothiazine (0.29 Å –1 ) from the same QD. This inconsistency is explained by the broadening of QD shell thicknesses in the distance dependence study, which significantly modifies the TET-coupling strength and driving force, resulting in a shallower distance dependence of the TET rate constants. This study sheds light on the fundamental mechanisms of QD-sensitized TET reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Evolution of Mass Spectrometers for High m / z Biological Ion Formation, Transmission, Analysis and Detection: A Personal Perspective

Mass spectrometry (MS) has become an essential tool in virtually all academic, pharmaceutical, and biopharmaceutical analytical laboratories. The specialized and bespoke area of MS research and application of high m / z ion (> m / z 6000 and high mass, >150 kDa) formation, transmission, analysis, and detection is a relatively new area of focus for MS that has seen dramatic acceleration in interest over the last two decades. Herein we delve into this exciting aspect of MS, discussing how MS instrumentation has been refined and evolved for native-MS analysis. We cover the early groundbreaking experiments showing high m / z ion formation, transmission, and preservation of protein structure in the gas phase. Additionally, we discuss specific instrument optimizations and modifications that have advanced high m / z ion generation, transmission, analysis, and detection, contributing to the research area known as gas-phase structural biology. Native-MS sample introduction methods, emerging technologies, and future perspectives are also examined. Finally, we share personal opinions, observations, and experiences that are new to the community or previously unpublished.

collisions↗

DOE OSTI2021

Improving Convection Trigger Functions in Deep Convective Parameterization Schemes Using Machine Learning

Abstract Deficiencies in convection trigger functions, used in deep convection parameterizations in General Circulation Models (GCMs), have critical impacts on climate simulations. A novel convection trigger function is developed using the machine learning (ML) classification model XGBoost. The large‐scale environmental information associated with convective events is obtained from the long‐term constrained variational analysis forcing data from the Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) and Manaus (MAO) sites representing, respectively, continental mid‐latitude and tropical convection. The ML trigger is separately trained and evaluated per site, and jointly trained and evaluated at both sites as a unified trigger. The performance of the ML trigger is compared with four convective trigger functions commonly used in GCMs: dilute convective available potential energy (CAPE), undilute CAPE, dilute dynamic CAPE (dCAPE), and undilute dCAPE. The ML trigger substantially outperforms the four CAPE‐based triggers in terms of the F 1 score metric, widely used to estimate the performance of ML methods. The site‐specific ML trigger functions can achieve, respectively, 91% and 93% F 1 scores at SGP and MAO. The unified trigger also has a 91% F 1 score, with virtually no degradation from the site‐specific training, suggesting the potential of a global ML trigger function. The ML trigger alleviates a GCM deficiency regarding the overprediction of convection occurrence, offering a promising improvement to the simulation of the diurnal cycle of precipitation. Furthermore, to overcome the black box issue of the ML methods, insights derived from the ML model are discussed, which may be leveraged to improve traditional CAPE‐based triggers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Role of Ocean and Atmosphere Variability in Scale-Dependent Thermodynamic Air-Sea Interactions

This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air-sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy-resolving high-resolution (HR) and eddy-parameterized low-resolution (LR) ocean components. Here, in this work, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co-variability over scales between 50 and 10,000 km and 60 days to 80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper-ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ~2,000–2,500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R 1 , ~600–2,000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean forcing also induces oscillations in SST and THF with periods ranging from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that driven by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Hydrologic Connectivity and Patch‐To‐Hillslope Scale Relations in Dryland Ecosystems

Abstract In drylands, runoff during storms redistributes water and nutrients from bare soil areas to vegetated patches, subsidizing vegetation with additional resources. The extent of this redistribution depends on the interplay between surface roughness and permeability; greater permeability in vegetated patches promotes run‐on to vegetation, but greater surface roughness diverts runoff, producing tortuous flow paths that bypass vegetation. Here, this interplay is examined in virtual experiments using the 2D Saint Venant Equations to measure runoff connectivity. Flowpaths are delineated using tracers advected by the flow. Distances between tracer sources and sinks along flowpaths measure hydrologic connectivity at two lengthscales: connectivity to the hillslope outlet and within‐slope source‐sink connectivity. Differences between these connectivity lengthscales indicate how flow may “by‐pass” vegetated patches within hillslopes. At the hillslope scale, a derived power‐law relation between the runoff coefficient and outlet connectivity describes hillslope water losses, providing a foundation for identifying landscapes likely to shed water.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Understanding the Cascade: Removing GCM Biases Improves Dynamically Downscaled Climate Projections

Polarization surrounding bias correction (BC) in creating climate projections arises from its lack of physicality. Here, we perform and analyze 18 dynamical downscaling simulations (with and without BC) to better understand the physical impacts of BC, applied before downscaling, on regional climate output across the western United States. Without BC, downscaled precipitation is systematically and unrealistically wet biased compared to a hierarchy of observationally based datasets over the 1980–2014 period due to cascading mean–state Global Climate Model (GCM) biases: (a) overly strong lower–tropospheric lapse rates (5 K/km), (b) overly cold (2 K) tropospheric temperatures, and (c) anomalous mid–tropospheric cyclonic vorticity advection. With BC, downscaled precipitation (snow) biases are virtually eliminated (halved). Identified GCM biases are common to the broader Coupled Model Intercomparison Project ensemble. Physical effects of BC on the quality of the regionalized projections, pending an evaluation of BC's distortion of the downscaled climate response, may motivate its broader application by dynamical downscalers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Velocity Dependence of Rate‐And‐State Friction in Granular Fault Gouge and Implications for Slow‐Slip Events

Abstract The standard rate‐and‐state friction (RSF) has extensively captured frictional behaviors, but it fails to explain the velocity dependence of frictional stability transition and widespread slow‐slip events (SSEs) in experiments and nature adequately. An alternative microphysical Chen‐Niemeijer‐Spiers (CNS) model can well describe the velocity dependence of frictional behaviors of granular gouges. Using the original CNS model, standard RSF parameters can be quantified microphysically. However, some micro‐parameters are not easy to estimate quantitatively, making it difficult to extrapolate to natural and experimental conditions. Here, we simplify the microphysically‐derived RSF parameters including direct effect a , evolution effect b , and critical slip distance D c , as well as equivalent values ( a eq , b eq , and D eq ). The simplified friction parameters directly illustrate their velocity dependence, namely the essentially constant a , a eq , and D c , negatively velocity‐dependent b and b eq , as well as varying D eq for different laws. They are roughly consistent with experimental results in various fault gouges. A modified CNS model is further derived from the original CNS model, establishing a direct link between the standard RSF and CNS models. The modified CNS model exhibits virtually identical frictional behaviors to the original CNS, but differs from the standard RSF at large velocity perturbations. Moreover, the linearized stability analysis indicates that the critical stiffness for the modified CNS model is velocity‐dependent. Compared with the standard RSF, the modified CNS model not only explains the velocity dependence of frictional stability transition, but also exhibits a more gradual transition for SSEs with a broader range of stiffness ratios.

Geochemistry & Geophysics↗

DOE OSTI2025

Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models

Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a “sequential precipitation input tagging” (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, $\overline{T_{V}}$, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes δ 18 O and δ 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year's F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated $\overline{T_{V}}$ ranged 179–923 days and F yw 0.6%–23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of $\overline{T_{V}}$ and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.

fraction of young water↗

DOE OSTI2020

Universal slow plasmons and giant field enhancement in atomically thin quasi-two-dimensional metals

Plasmons depend strongly on dimensionality: while plasmons in three-dimensional systems start with finite energy at wavevector q = 0, plasmons in traditional two-dimensional (2D) electron gas disperse as ω p ∼ q . However, besides graphene, plasmons in real, atomically thin quasi-2D materials were heretofore not well understood. Here we show that the plasmons in real quasi-2D metals are qualitatively different, being virtually dispersionless for wavevectors of typical experimental interest. This stems from a broken continuous translational symmetry which leads to interband screening; so, dispersionless plasmons are a universal intrinsic phenomenon in quasi-2D metals. Moreover, our ab initio calculations reveal that plasmons of monolayer metallic transition metal dichalcogenides are tunable, long lived, able to sustain field intensity enhancement exceeding 10 7 , and localizable in real space (within ~20 nm) with little spreading over practical measurement time. This opens the possibility of tracking plasmon wave packets in real time for novel imaging techniques in atomically thin materials.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Octave bandwidth photonic fishnet-achromatic-metalens

Planar structured interfaces, also known as metasurfaces, are continuously attracting interest owing to their ability to manipulate fundamental attributes of light, including angular momentum, phase, or polarization. However, chromatic aberration, limiting broadband operation, has remained a challenge for metasurfaces-based optical components and imagers. The limitation stems from the intrinsic dispersion of existing materials and design principles. Here we report and experimentally demonstrate polarization-independent fishnet-achromatic-metalenses with measured average efficiencies over 70% in the continuous band from the visible (640 nm) to the infrared (1200 nm). Results of the scalable platform are enabling for applications requiring broad bandwidth and high efficiency including energy harvesting, virtual reality and information processing devices, or medical imaging.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Complete polarization of electronic spins in OLEDs

At low temperatures and high magnetic fields, electron and hole spins in an organic light-emitting diode become polarized so that recombination preferentially forms molecular triplet excited-state species. For low device currents, magnetoelectroluminescence perfectly follows Boltzmann activation, implying a virtually complete polarization outcome. As the current increases, the magnetoelectroluminescence effect is reduced because spin polarization is suppressed by the reduction in carrier residence time within the device. Under these conditions, an additional field-dependent process affecting the spin-dependent recombination emerges, possibly related to the build-up of triplet excitons and their interaction with free charge carriers. Suppression of the EL alone does not prove electronic spin polarization. We therefore probe changes in the spin statistics of recombination directly in a dual singlet-triplet emitting material, which shows a concomitant rise in phosphorescence intensity as fluorescence is suppressed. Finite spin-orbit coupling in these materials gives rise to a microscopic distribution in effective g-factors of electrons and holes, Δg, i.e., a distribution in Larmor frequencies. This Δg effect in the pair, which mixes singlet and triplet, further suppresses singlet-exciton formation at high fields in addition to thermal spin polarization of the individual carriers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

PlasmidMaker is a versatile, automated, and high throughput end-to-end platform for plasmid construction

Abstract Plasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute ( Pf Ago)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate 101 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments. PlasmidMaker should greatly expand the potential of synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗