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At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Thermally Activated Delayed Fluorescence Sensitization for Highly Efficient Blue Fluorescent Emitters

Hyperfluorescence is emerging as a powerful strategy to develop optoelectronic devices with high-color purity and enhanced stability. It requires appropriate integration of a sensitizer displaying efficient thermally activated delayed fluorescence (TADF) and an emitter displaying strong, narrow-band fluorescence. Here, through a joint computational and experimental approach, we provide an unprecedented, end-to-end systems level description of the electronic and optical processes that take place in a hyperfluorescent emissive layer composed of a TADF sensitizer, bis(2,5-di(9H-carbazol-9-yl)phenyl)-1,3,4-oxadiazole (4CzDPO), and a fluorescent emitter, 2,5,8,11-tetra-tert-butylperylene (TBPe). We combine the photophysical properties measurement of the emissive layer with the computational determination of the electronic properties, film morphology, and excitation transfer phenomena. The Förster resonance energy transfer rates from 4CzDPO to TBPe are on the order of 1011 s–1, considerably higher than the radiative and non-radiative recombination rates for 4CzDPO. These features ensure nearly complete energy transfer to TBPe, leading to a five-fold increase in the photoluminescence quantum yields in the 4CzDPO:TBPe system in comparison to neat films of 4CzDPO. Furthermore, our approach highlights the factors that can provide efficient energy transfer from TADF molecules to fluorescent emitters, suppress energy transfer among TADF molecules, and avoid the need for a host material within the emissive layer.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Rheological and microstructural characterization of aqueous suspensions of carbon black and reduced graphene oxide

Carbon black is often used as a conductivity enhancer in battery electrodes. Reduced graphene oxide is another conducting material, with a high aspect ratio sheet-like morphology, and offers the possibility of generating a conducting network at loadings that are small compared to carbon black. Suspensions of conducting carbon, active materials and binders are typically coated on current collectors during the formation of electrodes. The rheology of these suspensions is an important indicator of the connectivity of particles in the suspension and impacts the electrical conductivity as well as the thickness of the coated layer. In this work, the rheology and microstructures of aqueous suspensions of para-aminobenzoic acid terminated carbon black (CB) with and without reduced graphene oxide (RGO) were investigated. The CB loading varied between 0.05 wt.% -10 wt.%, while the samples containing RGO had an RGO loading of 0.05 wt.%. The pH of the suspension was varied from 7.5 to 3. The carboxyl groups on the CB surface are deprotonated at pH 7.5, making the particles hydrophilic. Protonation of the carboxylate groups at pH 3 makes the particles partially hydrophobic. Suspensions of CB showed Newtonian behavior at all loadings for pH 7.5, and at loadings below 1.5 wt.% for pH 3. They are shear thinning at loadings between 1.5–10 wt.%. Interestingly, the low shear viscosity is non-monotonic with CB loading, rising up to a CB loading of 7.5 wt.%, and then dropping at 10 wt.%. Cryogenic scanning electron microscopy (SEM) showed CB particles forming aggregates at pH 3 for CB loadings greater than 1.5 wt.%. At pH 3, addition of 0.05 wt.% RGO resulted in a viscosity increase for suspensions containing 0.5 wt.% CB, as the RGO formed connections with CB particles that enhanced network formation. Adding RGO had little effect on suspensions that had 1.5 wt.% CB. The combination of SEM imaging and suspension rheology provides insight into the particle connectivity for the carbon-based materials studied here. These insights will be useful in determining coating conditions for slurries used in rechargeable battery electrodes.

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

Mild and Selective Hydrogenation of Nitrate to Ammonia in the Absence of Noble Metals

Motivated by increased awareness about nitrate contamination of surface waters and its deleterious effects in human and animal health, we sought an alternative, non-noble metal catalyst for the chemical degradation of nitrate. First row transition metal phosphides recently emerged as excellent alternatives for hydrogen evolution and hydrotreating reactions. We demonstrate that a key member of this family, Ni 2 P, readily hydrogenates nitrate (NO 3 – ) to ammonia (NH 3 ) near ambient conditions with very high selectivity (96%). One of the few non-precious metal-based catalysts for this transformation, and among ca. 1% of catalysts with NH 3 selectivity, Ni 2 P can be recycled multiple times with limited loss of activity. Both nitrite (NO 2 – ) and nitric oxide (NO) intermediates are also hydrogenated. Density functional theory (DFT) indicates that—in the absence of a catalyst—nitrite hydrogenation is the reaction bottleneck. A variety of adsorbates (H, O, N, NO) induce surface reconstruction with top-layer Ni-rich surface stoichiometry. Critically, H saturation coverage on Ni 2 P(001) is only ca. 3 nm –2 , significantly less than that on Pd(111) and Ni(111) of ca. 15–18 nm –2 , which may play a key role in allowing coadsorption of NO x – . Here the ability of Earth-abundant, binary metal phosphides such as Ni 2 P to catalyze nitrate hydrogenation could transform and help us to better understand the basic science behind catalytic hydrogenation and, in turn, advance the next generation of oxyanion removal technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2020

The most recent version of these data are available https://doi.org/10.25581/spruce.100/1874948 and supersedes all previous versions. This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2021, with start- and end-of-season phenological transition dates derived through the end of autumn 2020. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). User note: A list of previous versions can be found in the Related Datasets section of the user guide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2021

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2022, with start- and end-of-season phenological transition dates derived through the end of autumn 2021. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). User Note: This dataset supersedes previous versions of SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery. A list of previous versions can be found in the Related Datasets section of the user guide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2022

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2023, with start- and end-of-season phenological transition dates derived through the end of autumn 2022. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step Contains 35 files in *.csv format inside a compressed (*.zip) file. Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) Contains one file in *.csv format Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. Contains three files in HTML format, one for each vegetation type One additional file in HTML format with the transition dates plotted for each vegetation type, by year R files for processing Phenocam files and flags. Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/y7z5mau7. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released phenocam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

SPRUCE Experiment, Marcell Experimental Forest, Sp↗
DOE OSTI2024

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2023

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2024, with start- and end-of-season phenological transition dates derived through the end of autumn 2023. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) • Contains one file in *.csv format (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure • Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type • One additional file in HTML format with the transition dates plotted for each vegetation type, by year (2) R files for processing Phenocam files and flags. • Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released data inclusive of the 2015-2022 data (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

Spruce and Peatland Responses Under Changing Envir↗
DOE OSTI2025

SPRUCE Vegetation Phenology in Experimental Plots from PhenoCam Imagery, 2015-2024

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2025 (2015-08-24 to 2025-03-31), with start- and end-of-season phenological transition dates derived through the end of autumn 2024. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step. • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e., vegetation type). • Contains one file in *.csv format. (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure. • Contains two files in *.csv format, one for snow on trees and one for snow on ground. This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type. • One additional file in HTML format with the transition dates plotted for each vegetation type, by year. (2) R files for processing PhenoCam files and flags. • Contains five files in R file(*.R) format and the components of the phenocamr package (Version 1.1.4) used for calculating transition dates for 2015-2024. These are contained in a compressed (*.zip) file. User Note: All imagery is posted in near-real time to the PhenoCam Project web page (https://phenocam.nau.edu), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. This data set is based on the complete camera record from SPRUCE and supersedes all previously released PhenoCam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

KAZRARSCL-c0-Cloud Boundaries subset

The KAZR-ARSCL VAP provides cloud boundaries and best-estimate time-height fields of radar moments. The VAP merges corrected, but uncalibrated, KAZR moments from all active radar modes with cloud base and cloud mask observations from the micropulse lidar (MPL), cloud base from the ceilometer, as well information from soundings, rain gauge, and microwave radiometer instruments to produce two data streams, one with best-estimate cloud base and cloud layer boundaries, and another which also includes best-estimate time-height fields of radar moments. This DOI is for the data stream that contain cloud layer boundaries only. Please note that the reflectivity used in this level c0 product is uncalibrated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Two decades of DOE investment lays the foundation for TRISO-fueled reactors

Tristructural isotropic (TRISO) coated particle fuel is a robust, microencapsulated fuel form developed originally for use in high-temperature gas-cooled reactors (HTGRs). The particles consist of a spherical fissile kernel surrounded by several layers of pyrocarbon and a silicon carbide (SiC) layer (Figure 1). The particles are formed into cylindrical or spherical fuel forms using a resinated graphite matrix material for insertion into an HTGR. The kernel and coating layers together act to retain fission products within the particle during normal reactor operation and during postulated accidents; TRISO particles can maintain structural integrity at extremely high temperatures, reaching as high as approximately 1,600°C in limiting HTGR accidents. This limits the fission product activity circulating in the helium coolant and the activity released to the environment during accidents. Acceptable performance of TRISO particles is therefore essential for reactor safety.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Synergistic effect of polyaniline on stabilizing Pt nanoparticles in PEMFCs†

The stability of Pt nanoparticles on a carbon support is crucial for the lifespan of polymer electrolyte membrane fuel cells as well as other electrocatalysis systems such as electrolyzers. Here we took the approach of utilizing the covalently grafted polyaniline on carbon to stabilize Pt nanoparticles by simultaneously alleviating the particle migration and mitigating the Ostwald ripening, which are two major mechanisms for loss of the catalyst stability. A comprehensive investigation of the stability and performance of Pt catalyst nanoparticles on these supports reveals that the polyaniline can shift the Pt L edge binding energy and the Pt 4f peak energy, leading to the increased redox potential of the Pt nanoparticles and making them more resistant to oxidation. Interestingly, the highest polyaniline density (50 wt%) does not show the best catalyst stability, rather, the second (33 wt%) demonstrates the best catalyst stability among these catalysts. Combining the XPS, XAS and fuel cell stability studies, we concluded that the locations of the Pt nanoparticles over the polyaniline layer on the carbon surface depend on the surface density of the polyaniline over the carbon surface. The Pt nanoparticles in the 50 wt% polyaniline catalyst are wrapped by the polyaniline polymer but do not sit directly on the carbon surface, while Pt nanoparticles in the 33 wt% polyaniline catalyst sit on the carbon surface and are densely surrounded by the polyaniline polymer. The results show that the mass activity loss is 12.5% while the ECSA (electrochemically active surface area) loss is 37.1% after 30k cycles of accelerating stress test for the 33 wt% polyaniline catalyst, far exceeding the DOE 2020 target for MEA (i.e., mass activity loss < 50%, and ECSA loss < 40%). Overall, the polyaniline has a synergistic effect on mitigating the surface migration and slowing down the Ostwald ripening to stabilize the Pt nanoparticles in fuel cells. The novel strategy to stabilize Pt nanoparticles using polyaniline opens a new pathway in the development of highly stable catalysts: relying on the functionalization group on the carbon support, instead of just focusing on the catalyst itself.

Li, Chenzhao↗
DOE OSTI2026

Understanding the Performance Gap between Polycrystalline and Single-Crystal Nickel-Rich Layered Oxide Cathodes

Singe-crystal (SC) nickel-rich layered oxide cathodes, composed of boundary-free particles with high tap density, offer significant advantages in volumetric energy density and mechanical strength compared with polycrystalline (PC) cathode materials. However, as the nickel content increases (≥80%), SC Ni-rich cathodes often suffer from faster performance degradation than PC cathodes of the same composition, and the underlying causes of this discrepancy remain poorly understood. Herein, we reveal the distinct Ni redox behaviors that govern the electrochemical performance of SC and PC Ni-rich cathodes using multiscale and operando characterization techniques. Our results indicate that the increasingly heterogeneous Ni oxidation process in SC cathodes leads to the additional irreversible oxygen redox activity that deteriorates both the mechanical and chemical structures. In contrast, PC cathodes, despite with more pronounced surface reconstruction, exhibit greater chemomechanical stability due to homogeneous redox reactions during charging. Consequently, we find that bulk degradation, more than surface reactions, ultimately leads to fast capacity decay of SC Ni-rich cathodes during cycling. In conclusion, this work offers a comprehensive view on the impact of Ni redox evolutions on the chemomechanical stability in Ni-rich layered oxide cathodes, providing new insights into the longstanding performance gap between SC and PC cathodes, and guiding the rational design of Ni-rich cathode architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Temporal Analysis and Scene Change Detection in Multispectral Overhead Imagery

Scene change detection can be a tedious and time consuming process especially when concerning large geographical areas, and the process can be even more cumbersome when analyzing changes in an area over large spans of time. Developing a useful way to help analysts recognize at what points in time significant changes to a scene have occurred can allow them to better focus their efforts in characterizing events. Applications include: Facility monitoring, Construction chronology, Monitoring of vehicle/aircraft activity, Characterization of larger sequences of events. In large areas exceeding hundreds to thousands of square kilometers in size, it can be difficult localizing when scene changes have occurred. Analysts can spend hours going through imagery to try to identify new construction, monitor facility activities, monitor vehicle movement, etc. where the object of interest may only be a few square meters. Our goal is to help cut down this time by giving analysts change maps with hot spots of change, allowing them to focus on regions that have experienced actual change in time frames they're interested in. Additionally, by combining these change maps into layers within a data cube, analysts can examine the change maps from a temporal perspective, allowing events to be characterized over spans of time. By opening the data cube in an imaging software capable of separating the layers, we can analyze the change maps sequentially, allowing us to examine scene changes occurring over time. As an example, we examined overhead imagery from Planet Labs of what appears to be a parking lot on Fort Irwin over the course of a year using ENVI, a geospatial satellite imagery analysis software. Using ENVI, we generate a graph of changes over time, and notice a particular segment near the end of our analysis window where no changes are detected. Examination of the actual satellite imagery reveals that during this time span, the parking lot was empty. This could be due to facility shutdown for maintenance or upgrades, or possibly even total workforce/vehicle fleet movement. Information like this could help analysts better characterize events, as well as to help create clearer timelines in larger sequences of events. Workflow steps: - Collect multiple maps of the same AOI (Area of Interest) during a time span of interest; - Generate change maps from AOI maps; - Generate data cube from change maps. An analyst can use the data cube to help inspect an AOI for activities within a time span of interest. If an event of interest is discovered, the analyst can then refer to the maps corresponding to the appropriate dates and times in the data cube to see precisely what is transpiring. The biggest objective being worked on is improving the change detection methodology employed. We currently use PCA-EM (Principal Component Analysis with Expectation Maximization), but we are currently focusing on implementing IR-MAD (Iteratively Reweighted Multivariate Alteration Detection) to be used in conjunction with PCA-EM in an effort to decrease false positivity and noise in the change maps we generate.

42 ENGINEERING↗
DOE OSTI2023

Chiral Perovskite Nanoplatelets with Tunable Circularly Polarized Luminescence in the Strong Confinement Regime

Chiral perovskite nanocrystals have emerged as an interesting chiral excitonic platform that combines both structural flexibility and superior optoelectronic properties. Despite several recent demonstrations of optical activity in various chiral perovskite nanocrystals, efficient circularly polarized luminescence (CPL) with tunable energies remains a challenge. The chirality imprinting mechanism as a function of perovskite nanocrystal dimensionality remains elusive. Here, in this study, atomically thin inorganic perovskite nanoplatelets (NPLs) are synthesized with precise control of layer thickness and are functionalized by chiral surface ligands, serving as a unique platform to probe the chirality transfer mechanism at the organic/perovskite interface. It is found that chirality is successfully imprinted into mono-, bi-, and tri-layer inorganic perovskite NPLs, exhibiting tunable circular dichroism (CD) and CPL responses. However, chirality transfer decreases in thicker NPLs, resulting in decreased CD and CPL dissymmetry factors for thicker NPLs. Aided by large-scale first-principles calculations, it is proposed that chirality transfer is mainly mediated through a surface distortion rather than a hybridization of electronic states, giving rise to symmetry breaking in the perovskite lattice and spin-split conduction bands. The findings described here provide an in-depth understanding of chirality transfer and design principles for distorted-surface perovskites for chiral photonic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Volumetric Additive Manufacturing of Dormant Catalytic Chemistries to Generate Silicone Micro‐ and Millifluidic Devices and Instant Molds

Tomographic volumetric additive manufacturing (T‐VAM) rapidly prints solid objects within minutes, accessing photochemistries that are traditionally challenging for layer‐based additive manufacturing methods. This includes high‐viscosity materials, air‐free chemistries, and solid‐state systems. Catalytic chemistries are appealing as a pathway to engineering advanced materials, including tough thermosets, silicone elastomers, and complex block copolymers. However, photoactivated dormant catalytic chemistries, where the catalyst irreversibly activates upon exposure to light, are incompatible with typical tomographic VAM approaches. To address this limitation, a zero‐dose optimization strategy is devised to preserve dormant catalysts in desired regions by keeping them unexposed to light. VAM printed micro‐ and millifluidic devices and instant molds are successfully produced within minutes in silicones polymerized using photoactivated dormant platinum photohydrosilylation catalysts. The printed channels are programmed to be 500 and 2500 µm for the micro‐ and millifluidic devices, and print fidelity is assessed by X‐ray computed tomography. This work demonstrates the potential of zero‐dose optimization to expand the range of chemistries accessible for VAM, enabling the rapid fabrication of complex devices.

Additive Manufacturing↗
DOE OSTI2020

Effect of TiO x Substrate Interactions on the Electrocatalytic Oxygen Reduction Reaction at Au Nanoparticles

Here, we report a robust model for studying electrocatalytic reactions at metal nanoparticles (NPs) in contact with metal oxide surfaces. The metal oxide layer (TiO x ) is prepared by atomic layer deposition, and it is sufficiently thin that it does not hinder electron transfer from the underlying conductive electrode to the supported AuNP electrocatalysts. In advance of the experiments, density functional theory (DFT) predicted that direct contact between AuNPs and TiO x would lead to enhanced activity for the oxygen reduction reaction (ORR). DFT attributes the observed ORR enhancement to partial charge transfer from oxygen vacancies within the TiO x film to the supported AuNPs and hence formation of anionic Au species. The experimental findings are in near quantitative agreement with the DFT results. Specifically, compared to isolated AuNPs, decreases of ~ 100 and ~ 50 mV in the ORR onset potential are observed experimentally for AuNPs supported on TiO 1.9 and TiO 2.0 films, respectively.

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

Back-Surface Passivation of CdTe Solar Cells Using Solution-Processed Oxidized Aluminum

Although back-surface passivation plays an important role in high-efficiency photovoltaics, it has not yet been definitively demonstrated for CdTe. Here, we present a solution-based process, which achieves passivation and improved electrical performance when very small amounts of oxidized Al 3+ species are deposited at the back surface of CdTe devices. The open circuit voltage (V oc ) is increased and the fill factor (FF) and photoconversion efficiency (PCE) are optimized when the total amount added corresponds to ~1 monolayer, suggesting that the passivation is surface specific. Addition of further Al 3+ species, present in a sparse alumina-like layer, causes the FF and PCE to drop as the interface layer becomes blocking to current flow. The optimized deposit increases the average baseline PCE for both Cu-free devices and devices where Cu is present as a dopant. The greatest improvement is found when the Al 3+ species are deposited prior to the CdCl 2 activation step and Cu is employed. In this case, the best-cell efficiency was improved from 12.6 to 14.4%. Furthermore, time-resolved photoluminescence measurements at the back surface and quantum efficiency measurements performed at the maximum power point indicate that the performance enhancement is due to a reduction in the interface recombination current at the back surface.

14 SOLAR ENERGY↗