Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “label transfer”

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.

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

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improving radiograph analysis throughput through transfer learning and object detection

SIGN Fracture Care International partners with surgeons in low-resource hospitals worldwide to provide access to effective orthopedic care by donating educational materials and innovatively designed surgical implants. Over two decades, SIGN’s Online Surgical Database (SOSD) has grown to contain over 500,000 medical images, with radiographs holding the majority share. One challenge in working with hospitals worldwide is that both the radiographs uploaded to the SOSD and the data entry accompanying the uploads vary in quality. To improve the accuracy of data in the SOSD, we trained a model to detect surgical implants in radiographs. We first developed a tool to automatically detect radiographs, then trained an object detection model to determine the number and placement of surgical implants visible in the radiograph. Active learning was used to generate a training set containing 2,510 radiographs with screws, nails, and plates labeled by bounding boxes. Training a model to simultaneously recognize all three classes of implants gave a low average precision (AP) for the plate class, likely due to the low number of plate instances in our training set and the large variety of surgical plates used by SIGN-partnered surgeons. Applying standard image augmentation techniques to increase the plate count in our training set did not appreciably increase the AP of plate detection. To improve plate detection, we redrew the bounding boxes to account for correlations between the screw and plate classes. Training one model to detect nails and screws and a separate model to detect plates increased the AP of plate detection by 78.8 percentage points. The AP of each class was 80.7% for screws, 93.6% for nails, and 92.6% for plates; meanwhile, the sensitivity was 92% for screws, 86% for nails, and 81% for plates. We show that object detection methods can be used to detect surgical implants in radiographs of varying quality; however, the detection ability is dependent on the type of implant, and some implants, in our case plates, must be treated differently than others. Such tools can improve the throughput of radiograph analysis, assisting physicians and surgeons with the treatment of bone fractures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Artificial intelligence models, photos, and data associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” (v2)

This data package is associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” published in Water Resources Research (Chen et al., 2024). This data package includes the training, validation, testing, and prediction data used by the artificial intelligence (AI) model for automated grain size and hydro-biogeochemistry quantification using streambed photos. The grain size data are extracted for each photo using You Look Only Once (YOLO), a pre-trained object detection model. This data package was originally published in October 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. Please see flmd.csv for a list of all files contained in this data package and descriptions for each. Please see dd.csv for a data dictionary that defines the column headers of .csv files in the data package. This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; and (4) six subfolders. Subfolders 1 to 4 include the training, validation, testing, and prediction data. Subfolder 5_Summary includes the summary results of different combinations of training, validation, testing, and prediction data. Subfolder 6_SupplementalData includes additional data downloaded from public sources (Kaufman et al., 2023a; Kaufman et al., 2023b; Garefalakis et al., 2023; Mair et al., 2024; https://github.com/river-corridors-sfa/Geospatial_variables). In total, the data package includes 110 folders and 44,283 files. These files include 9,047 .jpg photos, 1 .png photo, 3 .tif photos; 26,639 photo labels and individual grain sizes and probability from AI (.txt); 8,447 grain size distribution data (.dat); and 126 CSV files for results summary, and 14 required metadata files (.xlsx). The summary CSV files contain 68 columns and approximately 2,200 rows that represent photo names, site locations, recording time, GPS coordinates, grains sizes (D10, D50, D60, and D84), number of grains, and additional hydro-biogeochemical data such as water depth, flow velocity, Manning’s coefficient, friction factor, hydraulic conductivity, permeability, streambed interstitial velocity magnitude, mass transfer rate, and nitrate uptake velocity. The photos were obtained from 75 sites in the Yakima River Basin and the Columbia River shorelines, and other associated data from samples and sensors obtained when the photos were taken are publicly available (Fulton et al. 2022; Grieger et al. 2023). All files are .csv, .txt, .dat, .jpg, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Cement line staining in undecalcified thin sections of cortical bone

A technique for demonstrating cement lines in thin, undecalcified, transverse sections of cortical bone has been developed. Cortical bone samples are processed and embedded undecalcified in methyl methacrylate plastic. After sectioning at 3-5 microns, cross-sections are transferred to a glass slide and flattened for 10 min. Sections of cortical bone are stained for 20 sec free-floating in a fresh solution of 1% toluidine blue dissolved in 0.1% formic acid. The section is dehydrated in t-butyl alcohol, cleared in xylene, and mounted with Eukitt's medium. Reversal lines appear as thin, scalloped, dark blue lines against a light blue matrix, whereas bone formation arrest lines are thicker with a smooth contour. With this technique cellular detail, osteoid differentiation, and fluorochrome labels are retained. Results demonstrate the applicability of a one-step staining method for cement lines which will facilitate the assessment of bone remodeling activity in thin sections of undecalcified cortical bone.

NASA Discipline Number 40-99↗
NASA NTRS2016

Features of the Upgraded Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Software

The Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) software is used at the NASA Langley Research Center to analyze global aeroheating data on wind tunnel models tested in the Langley Aerothermodynamics Laboratory. One-dimensional, semi-infinite heating data derived from IHEAT are used in the design of thermal protection systems for hypersonic vehicles that are exposed to severe aeroheating loads, such as reentry vehicles during descent and landing procedures. This software program originally was written in the PV-WAVE(Registered Trademark) programming language to analyze phosphor thermography data from the two-color, relative-intensity system developed at Langley. To increase the efficiency, functionality, and reliability of IHEAT, the program was migrated to MATLAB(Registered Trademark) syntax and compiled as a stand-alone executable file labeled version 4.0. New features of IHEAT 4.0 include the options to perform diagnostic checks of the accuracy of the acquired data during a wind tunnel test, to extract data along a specified multi-segment line following a feature such as a leading edge or a streamline, and to batch process all of the temporal frame data from a wind tunnel run. Results from IHEAT 4.0 were compared on a pixel level to the output images from the legacy software to validate the program. The absolute differences between the heat transfer data output from the two programs were on the order of 10(exp -5) to 10(exp -7). IHEAT 4.0 replaces the PV-WAVE(Registered Trademark) version as the production software for aeroheating experiments conducted in the hypersonic facilities at NASA Langley.

Mason, Michelle L.↗
NASA NTRS1985

Polar transport of 45Ca2+ across the elongation zone of gravistimulated roots

The movement of calcium across the elongation zone of gravistimulated primary roots of maize (Zea mays L.) was measured using 45Ca2+. Radioactive calcium was applied to one side of the elongation zone about 4 mm back from the root tip and the distribution of radioactivity across the root in the region of application was determined using scintillation spectrometry. The movement of 45Ca2+ across the elongation zone was non-polar in vertically oriented roots. In gravistimulated roots the movement of label was polarized with about twice as much label moving from top to bottom as from bottom to top. A variety of treatments which interfere with gravitropism was found to eliminate the polar movement of 45Ca2+ across the elongation zone. In maize cultivars which require light for gravitropic competency, dark grown roots exhibited neither gravitropism nor polar movement of 45Ca2+ across the elongation zone. Upon illumination the roots developed but gravitropic competency and gravity-induced polar movement of 45Ca2+ across the elongation zone. Similarly, roots of light-grown seedlings lost both gravitropic competency and 45Ca2+ transport polarity upon transfer to the dark. The results indicate a close correlation between calcium movement and gravitropism in primary roots in maize.

NASA Discipline Number 40-10↗
DOE OSTI2022

13 C ENDOR Characterization of the Central Carbon within the Nitrogenase Catalytic Cofactor Indicates That the CFe 6 Core Is a Stabilizing “Heart of Steel”

Substrates and inhibitors of Mo-dependent nitrogenase bind and react at Fe ions of the active-site FeMo-cofactor [7Fe–9S–C–Mo–homocitrate] contained within the MoFe protein α-subunit. The cofactor contains a CFe 6 core, a carbon centered within a trigonal prism of six Fe, whose role in catalysis is unknown. Targeted 13 C labeling of the carbon enables electron-nuclear double resonance (ENDOR) spectroscopy to sensitively monitor the electronic properties of the Fe–C bonds and the spin-coupling scheme adopted by the FeMo-cofactor metal ions. Here this report compares 13 CFe 6 ENDOR measurements for (i) the wild-type protein resting state (E 0 ; α-Val 70 ) to those of (ii) α-Ile 70 , (iii) α-Ala 70 -substituted proteins; (iv) crystallographically characterized CO-inhibited “hi-CO” state; (v) E 4 (4H) Janus intermediate, activated for N 2 binding/reduction by accumulation of 4[ e– /H + ]; (vi) E 4 (2H)* state containing a doubly reduced FeMo-cofactor without Fe-bound substrates; and (vii) propargyl alcohol reduction intermediate having allyl alcohol bound as a ferracycle to FeMo-cofactor Fe6. All states examined, both S = 1/2 and 3/2 exhibited near-zero 13 C isotropic hyperfine coupling constants, $^Ca$ = [-1.3 ↔ +2.7] MHz. Density functional theory computations and natural bond orbital analysis of the Fe-C bonds show that this occurs because a (3 spin-up/3 spin-down) spin-exchange configuration of CFe 6 Fe-ion spins produces cancellation of large spin-transfers to carbon in each Fe–C bond. Previous X-ray diffraction and DFT both indicate that trigonal-prismatic geometry around carbon is maintained with high precision in all these states. The persistent structure and Fe–C bonding of the CFe 6 core indicate that it does not provide a functionally dynamic (hemilabile) “beating heart”-instead it acts as “a heart of steel”, stabilizing the structure of the FeMo-cofactor-active site during nitrogenase catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

Label-Free Detection of Cardiac Troponin-I Using Carbon Nanofiber Based Nanoelectrode Arrays

A sensor platform based on vertically aligned carbon nanofibers (CNFs) has been developed. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. A carbon nanofiber (CNF) multiplexed array has been fabricated with 9 sensing pads, each containing 40,000 carbon nanofibers as nanoelectrodes. Here, we report the use of vertically aligned CNF nanoelectrodes for the detection of cardiac Troponin-I for the early diagnosis of myocardial infarction. Antibody, antitroponin, probe immobilization and subsequent binding to human cardiac troponin-I were characterized using electrochemical impedance spectroscopy and cyclic voltammetry techniques. Each step of the modification process resulted in changes in electrical capacitance or resistance to charge transfer due to the changes at the electrode surface upon antibody immobilization and binding to the specific antigen. This sensor demonstrates high sensitivity, down to 0.2 ng/mL, and good selectivity making this platform a good candidate for early stage diagnosis of myocardial infarction.

cardiac output↗
NASA NTRS1984

Cosmic Ray Exposure & Linear-Energy-Transfer Evaluations for the COBE Mission

Magnetospherically attenuated, orbit integrated, surface incident cosmic ray fluxes of galactic origin were determined for the COBE mission. All heavy ions up to Nickel (z=28) were considered in this, evaluation. In order to provide worst case approximations, estimates were based on solar minimum conditions. Transport and material shielding calculations were then performed for these vehicle encountered particles, for a simple spherical 3-D aluminum geometry, and the materially attenuated cosmic ray distributions emerging behind selected shield thicknesses were obtained. Finally, Linear-Energy-Transfer (LET) spectra were evaluated for the energy spectra of each ion specie and these were, in turn, integrated into the sum-total LET distribution contained in this report. The results are presented in tabular and graphical form for eight (8) different shield thicknesses from.01 to 10.0 gm/cm2 of aluminum. They show most conclusively, and not unexpectedly, that material shielding has virtually no 'effect on the final LET spectrum, at least not for aluminum shields. This was predictable. Please note that in the LET graphs, two curves were plotted. Of these, please ignore the one labeled "grazing" and use only the one labeled "normal". Again, it should be remembered that the end results contain contributions from all elements up to Nickel (z=28).

Stassinopoulos, E. G.↗
NASA NTRS2024

3D Cloud Masking Across A Broad Swath Using Multi-Angle Polarimetry and Deep Learning

Understanding the 3-dimensional structure of clouds is of crucial importance to modeling our changing climate. Active sensors, such as radar and lidar, provide accurate vertical cloud profiles, but are mostly restricted to along-track sampling. Passive sensors can capture a wide swath, but struggle to see beneath cloud tops. In essence, both types of products are restricted to two dimensions: as a cross-section in the active case, and an image in the passive case. However, multi-angle sensor configurations contain implicit information about 3D structure, due to parallax and atmospheric path differences. Extracting that implicit information can be challenging, requiring computationally expensive radiative transfer techniques. Machine learning, as an alternative, may be able to capture some of the complexity of a full 3D radiative transfer solution with significantly less computational expense. In this work, we make three contributions towards understanding 3D cloud structure from multi-angle polarimetry. First, we introduce a large-scale, publicly available dataset that fuses existing cloud products into a format more amenable to machine learning. This dataset treats multi-angle polarimetry as an input, and radar-based vertical cloud profiles as an output. Second, we describe and evaluate strong baseline machine learning models based that predict these profiles from the passive imagery. Notably, these models are trained only on center-swath labels, but can predict cloud profiles over the entire passive imagery swath. Third, we leverage the information-theoretic nature of machine learning to draw conclusions about the relative utility of various sensor configurations, including spectral channels, viewing angles, and polarimetry. These findings have implications for Earth-observing missions such as NASA’s Plankton, Aerosol, Cloud-ocean Ecosystem (PACE) and Atmosphere Observing System (AOS) missions, as well as in informing future applications of computer vision to atmospheric remote sensing.

clouds↗
DOE OSTI2022

MOOSE Reactor Module Meshing Enhancements to Support Reactor Physics Analysis

The U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program develops an integrated suite of advanced reactor physics tools built upon the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Each code generally requires an input finite element mesh on which the physics solution is calculated, reported, and transferred to other physics codes. The meshing process is often burdensome for the complex geometries present in reactors due to lack of easy-to-use, open-source meshing tools. To address the bottleneck associated with meshing complex geometries found in nuclear reactors, NEAMS initiated the development of the MOOSE Reactor Module starting in FY21. The Reactor Module builds off the existing MOOSE Mesh System to include targeted meshing capabilities such as the ability to generate hexagonal pin cells, assemblies with ducts, rotating control drums, cores, peripheral zones around a core, as well as the automatic labeling (“reporting IDs”) of pin, assembly, and planar zones to simplify post-processing of results. As a Physics Module in MOOSE, the Reactor Module is open-source, available with any MOOSE installation, directly compatible with MOOSE-based tools, and can be invoked from MOOSEbased applications to generate meshes. Functionality from the Reactor Module has been applied to several advanced reactor concepts to demonstrate user workflow improvements and accuracy. The primary objective of the Reactor Module is to improve useability of MOOSEbased tools by streamlining mesh generation and output inspection processes. During FY22, the functionality of the Reactor Module (and accompanying Mesh System) has been expanded based on user needs. First, the Reactor Geometry Mesh Builder capability developed primarily in FY21 has been refactored and merged to the public MOOSE repository. This capability wraps underlying Reactor Module mesh generators into a “Pin – Assembly – Core” workflow appropriate for conventional Cartesian and hexagonal geometries, and notably assigns material IDs during mesh generation stage and generates only the minimal number of blocks needed in order to reduce computational burden. Biasing and boundary layer options have been added to the base mesh generators as required by thermal hydraulics solvers. The reporting ID functionality has been expanded to differentiate ring-wise and azimuthal sectors within a pin for use with depletion algorithms, and VectorPostProcessor and Reporter objects are now available to integrate solution variables across zones based on ID combinations. Functionality to trim hexagonal meshes along the center or periphery has been developed so users may leverage symmetry and reflective boundary conditions to reduce the mesh size. A flexible and powerful tool to fill the space between two sidesets has been introduced to the framework and can be used for transition layers such as stitching two assemblies together with different numbers of pins, or for complex geometries which do not follow conventional Cartesian/hexagonal patterns. Finally, additional verification problems were performed with NEAMS physics tools in complement with existing NEAMS work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Identifying a novel pathway for extracellular electron uptake in Methanosarcina barkeri using shotgun

The overarching goal of this project was to identify the genetic and/or enzymatic basis for extracellular electron uptake in Methanosarcina barkeri—an organism we previously characterized to be capable of this process using poised potential electrodes and a range of electrochemical techniques. In our first aim, we will utilized proteomic techniques that labels extracellular proteins with free amine groups with biotin and perform a selective purification of these proteins from the rest of the proteome. These were identified using mass spectrometry, providing us insight into the identity of the cell surface proteins, including redox active proteins present during extracellular electron uptake. We will also used an isobaric tagging technique (iTRAQ labeling) of proteomes from different experiment conditions to look at differential proteins expression and better understand the total pathway involved in extracellular electron uptake coupled to methanogenesis. In our final aim, we will investigated the electrochemical nature of electron uptake in co-cultures, compared to our pure culture data sets. We predict the process of electron uptake from electrodes replicates what goes on in nature when these organisms for co-cultures with electrogenic microbes such as Geobacter, and to test this hypothesis we have begun to probe co-cultures electrochemically during direct interspecies electron transfer. Our final aim took much longer than expected due to challenges replicating co-cultures between Geobacter metallireducens and Methanosarcina barkeri. We found the major problem with this work was the inability of the M. barkeri strain we used (and we tried strains from three different labs) to successfully grow on acetate in the absence of hydrogen. As such, we began to use the strain Methanosarcina acetivorans—another close relative that specializes on acetate growth. We are currently in the process of comparing electrochemical observations of this microorganism between pure and co-culture experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

FINETUNA: fine-tuning accelerated molecular simulations

Abstract Progress towards the energy breakthroughs needed to combat climate change can be significantly accelerated through the efficient simulation of atomistic systems. However, simulation techniques based on first principles, such as density functional theory (DFT), are limited in their practical use due to their high computational expense. Machine learning approaches have the potential to approximate DFT in a computationally efficient manner, which could dramatically increase the impact of computational simulations on real-world problems. However, they are limited by their accuracy and the cost of generating labeled data. Here, we present an online active learning framework for accelerating the simulation of atomic systems efficiently and accurately by incorporating prior physical information learned by large-scale pre-trained graph neural network models from the Open Catalyst Project. Accelerating these simulations enables useful data to be generated more cheaply, allowing better models to be trained and more atomistic systems to be screened. We also present a method of comparing local optimization techniques on the basis of both their speed and accuracy. Experiments on 30 benchmark adsorbate-catalyst systems show that our method of transfer learning to incorporate prior information from pre-trained models accelerates simulations by reducing the number of DFT calculations by 91%, while meeting an accuracy threshold of 0.02 eV 93% of the time. Finally, we demonstrate a technique for leveraging the interactive functionality built in to Vienna ab initio Simulation Package (VASP) to efficiently compute single point calculations within our online active learning framework without the significant startup costs. This allows VASP to work in tandem with our framework while requiring 75% fewer self-consistent cycles than conventional single point calculations. The online active learning implementation, and examples using the VASP interactive code, are available in the open source FINETUNA package on Github.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

TPCpp-10M: Simulated proton-proton collisions in a time projection chamber for AI foundation models

Scientific foundation models hold great promise for advancing nuclear and particle physics by improving analysis precision and accelerating discovery. Yet, progress in this field is often limited by the lack of openly available large scale datasets, as well as standardized evaluation tasks and metrics. Furthermore, the specialized knowledge and software typically required to process particle physics data pose significant barriers to interdisciplinary collaboration with the broader machine learning community. This work introduces a large, openly accessible dataset of 10 million simulated proton-proton collisions, designed to support self-supervised training of foundation models. To facilitate ease of use, the dataset is provided in a common NumPy format. In addition, it includes 70,000 labeled examples spanning three well defined downstream tasks: track finding, particle identification, and noise tagging, to enable systematic evaluation of the foundation model's adaptability. The simulated data are generated using the Pythia Monte Carlo event generator at a center of mass energy of $\sqrt{s}$ = 200 GeV and processed with Geant4 to include realistic detector conditions and signal emulation in the sPHENIX Time Projection Chamber at the Relativistic Heavy Ion Collider, located at Brookhaven National Laboratory. This dataset resource establishes a common ground for interdisciplinary research, enabling machine learning scientists and physicists alike to explore scaling behaviors, assess transferability, and accelerate progress toward foundation models in nuclear and high energy physics. The complete simulation and reconstruction chain is reproducible with the sPHENIX software stack. All data and code locations are provided under Data Accessibility.

Data Analysis, Statistics and Probability (physics↗
DOE OSTI2020

Single-atom implanted two-dimensional MOFs as efficient electrocatalysts for the oxygen evolution reaction

The exploration of novel electrochemical energy conversion and storage devices has been extensively studied in recent decades for their specific advantages. Therefore, the design of highly efficient, stable, and noble-metal-free electrocatalysts for oxygen-related reactions (OER) is critical but challenging and is still worth improving. Herein, a facile and controllable synthesis strategy for bimetallic electrocatalysts for the OER from a two-dimensional iron-based metal–organic framework (HUST-8, HUST = Huazhong University of Science and Technology) precursor has been reported. The unoccupied porphyrin center has been disposed into the layer structure of HUST-8, which is very facile for the introduction of a second type of metal center via post-modification treatment. Guided by the synthesis strategy, Fe/Ni, Fe/Co, Fe/Zn, Fe/Mn and Fe/Fe species have been fabricated, and their electrocatalytic performance for the OER has been further characterized, among which the Fe/Ni type exhibits the best efficiency and conversion. For Fe/Ni species of HUST-8 (labeled as Ni@HUST-8), in 1 M KOH, the initial potential for OER activity performance is 170 mV (vs. RHE). At 10 mA cm -2 , the corresponding overpotential is 240 mV and the Tafel slope is simulated as 60.8 mV dec -1 . All of these experimental results of Ni@HUST-8 illustrate its better performance than commercial IrO 2 . Compared to the MOF parent and other bimetallic species, the higher electrocatalytic performance of Ni@HUST-8 should be ascribed to the special synergistic effect of Fe and Ni centers, which tends to greatly improve the reaction kinetics and charge transfer efficiency, while increasing the activity of the OER and achieving the best catalytic performances. The systematic investigation clearly manifests the important role of the synergistic effect of bimetallic centers in the OER and provides other insight into fabricating tailored electrocatalysts derived from MOF-based templates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Proton Transfer Dynamics in the Aprotic Proton Accepting Solvent 1-Methylimidazole

The dynamics of proton transfer to the aprotic solvent 1-methylimidazole (MeIm, proton acceptor) from the photoacid 8-hydroxypyrene-1,3,6-trisulfonic acid trisodium salt (HPTS) were investigated using fast fluorescence measurements. The closely related molecule, 8- methoxypyrene-1,3,6-trisulfonic acid trisodium salt (MPTS), which is not a photoacid, was also studied for comparison. Following optical excitation, the wavelength-dependent population dynamics of HPTS in MeIm resulting from the deprotonation process were collected over the entire fluorescence emission window. Analysis of the time-dependent fluorescence spectra revealed four distinct fluorescence bands that appear and decay on different time scales. We label these four states as: protonated (P), associated I (A I ), associated II (A II ), and deprotonated (D). We find that the simple kinetic scheme of P → A I → A II → D is not consistent with the data. Instead, the kinetic scheme that describes the data has P decaying into A I , which mainly goes on to deprotonation (D), but AI can also feed into A II . A II can return to A I or decay to the ground state, but does not deprotonate within experimental error. Finally, quantum chemistry and excitedstate QM/MM Born-Oppenheimer molecular dynamics simulations indicate that A I and A II are two H-bonding conformations of MeIm to the HPTS hydroxyl, axial and equatorial, respectively.

14 SOLAR ENERGY↗
DOE OSTI2022

Hydroporphyrin-Doped Near-Infrared-Emitting Polymer Dots for Cellular Fluorescence Imaging

We report Near-infrared (NIR) fluorescent semiconductor polymer dots (Pdots) have shown great potential for fluorescence imaging due to their exceptional chemical and photophysical properties. This paper describes the synthesis of NIR emitting Pdots with great control and tunability of emission peak wavelength. The Pdots were prepared by doping poly [(9,9-dioctylfluorenyl-2,7-diyl)-altco-(1,4-benzo-(2,1’,3)-thiadiazole)] (PFBT), a semiconducting polymer commonly used as a host polymer in luminescent Pdots, with a series of chlorins and bacteriochlorins with varying functional groups. Chlorins and bacteriochlorins are ideal dopants due to their high hydrophobicity, which precludes their use as molecular probes in aqueous biological media but on the other hand prevents their leakage when doped into Pdots. Additionally, chlorins and bacteriochlorins have narrow deep-red to NIR emission bands and the wide array of synthetic modifications available for modifying their molecular structure enables tuning their emission predictably and systematically. Transmission electron microscopy (TEM) and dynamic light scattering (DLS) measurements show the chlorin and bacteriochlorin-doped Pdots to be nearly spherical with an average diameter of 46±12 nm. Efficient energy transfer between PFBT and the doped chlorins or bacteriochlorins decreases the PFBT donor emission to near baseline level and increases the emission of the doped dyes that serve as acceptors. The chlorin and bacteriochlorindoped Pdots show narrow emission bands ranging from 640 nm to 820 nm depending on the doped dye. The paper demonstrates the utility of the systematic chlorin and bacteriochlorin synthesis approach by preparing Pdots of varying emission peak wavelength, utilizing them to visualize multiple targets using wide field fluorescence microscopy, binding them to secondary antibodies, and determining the binding of secondary antibody-conjugated Pdots to primary antibody-labeled receptors in plant cells. Additionally, the chlorin and bacteriochlorin doped Pdots show a blinking behavior that could enable their use in super resolution imaging methods like STORM.

13C-NMR↗
DOE OSTI2022

On the mechanism of intermolecular nitrogen-atom transfer from a lattice-isolated diruthenium nitride intermediate

Catalyst confinement within microporous media provides the opportunity to site isolate reactive intermediates, enforce intermolecular functionalization chemistry by co-localizing reactive intermediates and substrates in molecular-scale interstices, and harness non-covalent host–guest interactions to achieve selectivities that are complementary to those accessible in solution. As part of an ongoing program to develop synthetically useful nitrogen-atom transfer (NAT) catalysts, we have demonstrated intermolecular benzylic amination of toluene at a Ru 2 nitride intermediate confined within the interstices of a Ru2-based metal–organic framework (MOF), Ru 3 (btc) 2 X 3 (btc = 1,3,5-benzenetricarboxylate, i.e., Ru-HKUST-1 for X = Cl). Nitride confinement within the extended MOF lattice enabled intermolecular C–H functionalization of benzylic C–H bonds in preference to nitride dimerization, which was encountered with soluble molecular analogues. Detailed study of the kinetic isotope effects (KIEs, i.e., k H /k D ) of C–H amination, assayed both as intramolecular effects using partially labeled toluene and as intermolecular effects using a mixture of per-labeled and unlabeled toluene, provided evidence for restricted substrate mobility on the time scale of interstitial NAT. Analysis of these KIEs as a function of material mesoporosity provided approximate experimental values for functionalization in the absence of mass transport barriers. Here, we disclose a combined experimental and computational investigation of the mechanism of NAT from a Ru 2 nitride to the C–H bond of toluene. Computed kinetic isotope effects for a H-atom abstraction (HAA)/radical rebound (RR) mechanism are in good agreement with experimental data obtained for C–H amination at the rapid diffusion limit. These results provide the first detailed analysis of the mechanism of intermolecular NAT to a C–H bond, bolster the use of KIEs as a probe of confinement effects on NAT within MOF lattices, and provide mechanistic insights unavailable by experiment because rate-determining mass transport obscured the underlying chemical kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

NASA Electronic Parts and Packaging (NEPP) Field Programmable Gate Array (FPGA) Single Event Effects (SEE) Test Guideline Update

The following are updated or new subjects added to the FPGA SEE Test Guidelines manual: academic versus mission specific device evaluation, single event latch-up (SEL) test and analysis, SEE response visibility enhancement during radiation testing, mitigation evaluation (embedded and user-implemented), unreliable design and its affects to SEE Data, testing flushable architectures versus non-flushable architectures, intellectual property core (IP Core) test and evaluation (addresses embedded and user-inserted), heavy-ion energy and linear energy transfer (LET) selection, proton versus heavy-ion testing, fault injection, mean fluence to failure analysis, and mission specific system-level single event upset (SEU) response prediction. Most sections within the guidelines manual provide information regarding best practices for test structure and test system development. The scope of this manual addresses academic versus mission specific device evaluation and visibility enhancement in IP Core testing.

Test guidelines↗