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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The first spectroscopically confirmed brown dwarfs in NGC 2264

ABSTRACT We present spectroscopic follow-up observations of 68 red, faint candidates from our multi-epoch, multiwavelength, previously published survey of NGC 2264. Using near-infrared spectra from VLT/KMOS, we measure spectral types and extinction for 32 young low-mass sources. We confirm 13 as brown dwarfs in NGC 2264, with spectral types between M6 and M8, corresponding to masses between 0.02 and 0.08 M⊙. These are the first spectroscopically confirmed brown dwarfs in this benchmark cluster. 19 more objects are found to be young M-type stars of NGC 2264 with masses of 0.08–0.3 M⊙. 7 of the confirmed brown dwarfs as well as 15 of the M-stars have IR excess caused by a disc. Comparing with isochrones, the typical age of the confirmed brown dwarfs is <0.5–5 Myr. More than half of the newly identified brown dwarfs and very low-mass stars have ages <0.5 Myr, significantly younger than the bulk of the known cluster population. Based on the success rate of our spectroscopic follow-up, we estimate that NGC 2264 hosts 200–600 brown dwarfs in total (in the given mass range). This would correspond to a star-to-brown dwarf ratio between 2.5:1 and 7.5:1. We determine the slope of the substellar mass function as $\alpha = 0.43^{+0.41}_{-0.56}$; these values are consistent with those measured for other young clusters. This points to a uniform substellar mass function across all star-forming environments.

Pearson, Samuel↗
DOE OSTI2023

DataShare Recon Assistant Tool (DSRAT) v.1.0.x

SAND2023-06798O DataShare Recon Assistant Tool (DSRAT) software is used for capturing recon data and information in an emergency response situation on an Android device. Users can capture images, video, item description and spectra information in DSRAT and upload it to DataShare, which is a multi-server application that shares data in real-time to all nodes on the network. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Gilbert, Christina↗
DOE OSTI2021

Automatic Search of Cataclysmic Variables Based on LightGBM in LAMOST-DR7

The search for special and rare celestial objects has always played an important role in astronomy. Cataclysmic Variables (CVs) are special and rare binary systems with accretion disks. Most CVs are in the quiescent period, and their spectra have the emission lines of Balmer series, HeI, and HeII. A few CVs in the outburst period have the absorption lines of Balmer series. Owing to the scarcity of numbers, expanding the spectral data of CVs is of positive significance for studying the formation of accretion disks and the evolution of binary star system models. At present, the research for astronomical spectra has entered the era of Big Data. The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) has produced more than tens of millions of spectral data. the latest released LAMOST-DR7 includes 10.6 million low-resolution spectral data in 4926 sky regions, providing ideal data support for searching CV candidates. To process and analyze the massive amounts of spectral data, this study employed the Light Gradient Boosting Machine (LightGBM) algorithm, which is based on the ensemble tree model to automatically conduct the search in LAMOST-DR7. Finally, 225 CV candidates were found and four new CV candidates were verified by SIMBAD and published catalogs. This study also built the Gradient Boosting Decision Tree (GBDT), Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost) models and used Accuracy, Precision, Recall, the F1-score, and the ROC curve to compare the four models comprehensively. Experimental results showed that LightGBM is more efficient. The search for CVs based on LightGBM not only enriches the existing CV spectral library, but also provides a reference for the data mining of other rare celestial objects in massive spectral data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

Sulfates on Mars: Indicators of Aqueous Processes

Recent analyses by MER instruments at Meridiani Planum and Gusev crater and the OMEGA instrument on Mars Express have provided detailed information about the presence of sulfates on Mars [1,2,3]. We are evaluating these recent data in an integrated multi-disciplinary study of visible-near-infrared, mid-IR and Mossbauer spectra of several sulfate minerals and sulfate-rich analog sites. Our analyses suggest that hydrated iron sulfates may account for features observed in Mossbauer and mid-IR spectra of Martian soils [4]. The sulfate minerals kieserite, gypsum and other hydrated sulfates have been identified in OMEGA spectra in the layered terrains in Valles Marineris and Terra Meridiani [2]. These recent discoveries emphasize the importance of studying sulfate minerals as tracers of aqueous processes. The sulfate-rich rock outcrops observed in Meridiani Planum may have formed in an acidic environment similar to acid rock drainage environments on Earth [5]. Because microorganisms typically are involved in the oxidation of sulfides to sulfates in terrestrial sites, sulfate-rich rock outcrops on Mars may be a good location to search for evidence of past life on that planet. Whether or not life evolved on Mars, following the trail of sulfate minerals will lead to a better understanding of aqueous processes and chemical weathering.

Bishop, Janice L.↗
DOE OSTI2022

Evaluating cloud liquid detection against Cloudnet using cloud radar Doppler spectra in a pre-trained artificial neural network

Detection of liquid-containing cloud layers in thick mixed-phase clouds or multi-layer cloud situations from ground-based remote-sensing instruments still poses observational challenges, yet improvements are crucial since the existence of multi-layer liquid layers in mixed-phase cloud situations influences cloud radiative effects, cloud lifetime, and precipitation formation processes. Hydrometeor target classifications such as from Cloudnet that require a lidar signal for the classification of liquid are limited to the maximum height of lidar signal penetration and thus often lead to underestimations of liquid-containing cloud layers. Here we evaluate the Cloudnet liquid detection against the approach of Luke et al. (2010) which extracts morphological features in cloud-penetrating cloud radar Doppler spectra measurements in an artificial neural network (ANN) approach to classify liquid beyond full lidar signal attenuation based on the simulation of the two lidar parameters particle backscatter coefficient and particle depolarization ratio. We show that the ANN of Luke et al. (2010) which was trained under Arctic conditions can successfully be applied to observations at the mid-latitudes obtained during the 7-week-long ACCEPT field experiment in Cabauw, the Netherlands, in 2014. In a sensitivity study covering the whole duration of the ACCEPT campaign, different liquid-detection thresholds for ANN-predicted lidar variables are applied and evaluated against the Cloudnet target classification. Independent validation of the liquid mask from the standard Cloudnet target classification against the ANN-based technique is realized by comparisons to observations of microwave radiometer liquid-water path, ceilometer liquid-layer base altitude, and radiosonde relative humidity. In addition, a case-study comparison against the cloud feature mask detected by the space-borne lidar aboard the CALIPSO satellite is presented. Three conclusions were drawn from the investigation. First, it was found that the threshold selection criteria of liquid-related lidar backscatter and depolarization alone control the liquid detection considerably. Second, all threshold values used in the ANN framework were found to outperform the Cloudnet target classification for deep or multi-layer cloud situations where the lidar signal is fully attenuated within low liquid layers and the cloud radar is able to detect the microphysical fingerprint of liquid in higher cloud layers. Third, if lidar data are available, Cloudnet is at least as good as the ANN. The times when Cloudnet outperforms the ANN in liquid detections are often associated with situations where cloud dynamics smear the imprint of cloud microphysics on the radar Doppler spectra.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Chlorophyll Fluorescence Emissions of Vegetation Canopies From High Resolution Field Reflectance Spectra

A two-year experiment was performed on corn (Zea mays L.) crops under nitrogen (N) fertilization regimes to examine the use of hyperspectral canopy reflectance information for estimating chlorophyll fluorescence (ChlF) and vegetation production. Fluorescence of foliage in the laboratory has proven more rigorous than reflectance for correlation to plant physiology. Especially useful are emissions produced from two stable red and far-red chlorophyll ChlF peaks centered at 685V10 nm and 735V5 nm. Methods have been developed elsewhere to extract steady state solar induced fluorescence (SF) from apparent reflectance of vegetation canopies/landscapes using the Fraunhofer Line Depth (FLD) principal. Our study utilized these methods in conjunction with field-acquired high spectral resolution canopy reflectance spectra obtained in 2004 and 2005 over corn crops, as part of an ongoing multi-year experiment at the USDA/Agriculture Research Service in Beltsville, MD. A spectroradiometer (ASD-FR Fieldspec Pro, Analytical Spectral Devices, Inc., Boulder, CO) was used to measure canopy radiances 1 m above plant canopies with a 22deg field of view and a 0deg nadir view zenith angle. Canopy and plant measurements were made at the R3 grain fill reproductive stage on 3-4 replicate N application plots provided seasonal inputs of 280, 140, 70, and 28 kg N/ha. Leaf level measurements were also made which included ChlF, photosynthesis, and leaf constituents (photosynthetic pigment, carbon (C), and N contents). Crop yields were determined at harvest. SIF intensities for ChlF were derived directly from canopy reflectance spectra in specific narrowband regions associated with atmospheric oxygen absorption features centered at 688 and 760 nm. The red/far-red S F ratio derived from these field reflectance spectra successfully discriminated foliar pigment levels (e.g., total chlorophyll, Chl) associated with N application rates in both corn crops. This canopy-level spectral ratio was also positively correlated to the foliar C/N ratio (r = 0.89, n = go), as was a leaf-level steady state fluorescence ratio (Fs/Chl, r = 0.92). The latter ratio was inversely correlated with crop grain yield (Kg 1 ha) (r = 0.9). This study has relevance to future passive satellite remote sensing approaches to monitoring C dynamics from space.

Middleton, E. M.↗
NASA NTRS2016

SEEDS Direct Imaging of the RV-Detected Companion to V450 Andromedae, and Characterization of the System

We report the direct imaging detection of a low-mass companion to a young, moderately active star V450 And, that was previously identified with the radial velocity (RV) method. The companion was found in high-contrast images obtained with the Subaru Telescope equipped with the HiCIAO camera and AO188 adaptive optics system. From the public ELODIE and SOPHIE archives we extracted available high-resolution spectra and RV measurements, along with RVs from the Lick planet search program. We combined our multi-epoch astrometry with these archival, partially unpublished RVs, and found that the companion is a low-mass star, not a brown dwarf, as previously suggested. We found the best-fitting dynamical masses to be m(sub 1) = 1.141(sup + 0.037, sub - 0.091) and m(sub 2) = 0.279(sup + 0.023, sub - 0.020) solar mass. We also performed spectral analysis of the SOPHIE spectra with the iSpec code. Hipparcos time-series photometry shows a periodicity of P = 5.743 day, which is also seen in the SOPHIE spectra as an RV modulation of the star A. We interpret it as being caused by spots on the stellar surface, and the star to be rotating with the given period. From the rotation and level of activity, we found that the system is 380(sup + 220, sub -100) Myr old, consistent with an isochrone analysis (220 (sup +2120, sub -90) Myr). This work may serve as a test case for future studies of low mass stars, brown dwarfs, and exoplanets by combination of RV and direct imaging data.

direct imaging detection of a low-mass companion↗
NASA NTRS2002

Subsystem Imaging Performance and Modeling of the Infrared Multi-Object Spectrograph

The Infrared Multi-Object Spectrograph (IRMOS) is a facility instrument for the Kitt Peak National Observatory Mayall Telescope (3.8 meter). IRMOS is a near-IR (0.8 - 2.5 micron) spectrograph with low to mid resolution (R=lambda/delta, lambda = 300 - 3800). The IRMOS spectrograph produces simultaneous spectra of - 100 objects in its 2.8 x 2.0 arc-min field of view using a commercial MEMS multi-mirror array device (MMA). The IRMOS optical design consists of two imaging systems, or "stages." The focal reducer, stage one, images the focal plane of the telescope onto the MMA. The spectrograph, stage two, images the MMA onto the detector. We describe the breadboard alignment method and imaging and scattered light performance for both the focal reducer and spectrograph. This testing provides verification of the optomechanical alignment method, and a measurement of the contribution of scattered light in the system due to mirror small scale surface error. After the stage I and 2 optics are integrated with the instrument, our test results will make it possible to distinguish between scattered light from the mirrors and the MMA. Image testing will be done at four wavelengths in the visible and near-IR. A mercury-argon pencil lamp will provide spectral lines at 546.1 and 1012 nm, and a blackbody radiation source lines at 1600 and 2200 nm. A CCD camera will be used as a detector for the visible wavelengths, and an IR photodiode will be used for the IR wavelengths. We compare our data with a theoretical analysis using a commercial software package. Mirror surface error is modeled by treating each surface as a superposition of various gratings (e.g., diamond turning tool marks, features due to the impurities of Al 6061, and periodic mid-frequency errors due to drift during machining).

Connelly, Joseph A.↗
NASA NTRS2016

Aerogel Hybrid Composite Materials: Designs and Testing for Multifunctional Applications

This webinar will introduce the broad spectrum of aerogel composites and their diverse performance properties such as reduced heat transfer to energy storage, and expands specifically on the aerogel/fiber laminate systems and testing methodologies. The multi-functional laminate composite system, AeroFiber, and its construction is designed by varying the type of fiber (e.g. polyester, carbon, Kevlar®, Spectra® or Innegral(TradeMark) and combinations thereof), the aerogel panel type and thickness, and overall layup configuration. The combination and design of materials may be customized and tailored to achieve a range of desired properties in the resulting laminate system. Multi-functional properties include structural strength, impact resistance, reduction in heat transfer, increased fire resistance, mechanical energy absorption, and acoustic energy dampening. Applications include aerospace, aircraft, automotive, boating, building and construction, lightweight portable structures, liquefied natural gas, cryogenics, transportation and energy, sporting equipment, and military protective gear industries.

Hybrid↗
DOE OSTI2023

The Pristine survey – XX. GTC follow-up observations of extremely metal-poor stars identified from Pristine and LAMOST

Ultra-metal-poor stars (⁠[Fe/H] < –4.0⁠) are very rare, and finding them is a challenging task. Both narrow-band photometry and low-resolution spectroscopy have been useful tools for identifying candidates, and in this work, we combine both approaches. We cross-matched metallicity-sensitive photometry from the Pristine survey with the low-resolution spectroscopic Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) data base, and re-analyzed all LAMOST spectra with ⁠[Fe/H] Pristine < –2.5⁠. We find that ~1/3rd of this sample (selected without ⁠[Fe/H] Pristine quality cuts) also have spectroscopic ⁠[Fe/H] < –2.5⁠. From this sample, containing many low signal-to-noise ratio (S/N) spectra, we selected 11 stars potentially having ⁠[Fe/H] < –4.0 or [Fe/H] < –3.0 with very high carbon abundances, and we performed higher S/N medium-resolution spectroscopic follow-up with the Optical System for Imaging and low Resolution Integrated Spectroscopy (OSIRIS) on the 10.4-m Gran Telescopio Canarias (GTC). We confirm their extremely low metallicities, with a mean of [Fe/H] < –3.4⁠, and the most metal-poor star having [Fe/H] < –3.8⁠. Three of these are clearly carbon-enhanced metal-poor (CEMP) stars with +1.65 < [C/Fe] < +2.45⁠. The two most carbon-rich stars are either among the most metal-poor CEMP-s stars or the most carbon-rich CEMP-no stars known, the third is likely a CEMP-no star. We derived orbital properties for the OSIRIS sample and find that only one of our targets can be confidently associated with known substructures/accretion events, and that three out of four inner halo stars have prograde orbits. Large spectroscopic surveys may contain many hidden extremely and ultra-metal-poor stars, and adding additional information from e.g. photometry as in this work can uncover them more efficiently and confidently.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Multi-Species Complex and Standard Metabolomic Samples with Verified Truth Annotations Dataset

This dataset contains 4523251 (~6.35 GB) metabolite-spectra matches following identification with CoreMS. Data were manually curated as true positives, true negatives, or unknowns. Calculations for spectral similarity scores were carried out with two methods for a total of ~12.7 GB (6.35 * 2) of data. They are all .tsv files, though can easily be changed to .txt. The file types are: * human cerebrospinal fluid (CSF), human blood plasma human urine: already published here https://www.nature.com/articles/s41597-021-00894-y, • purchased FAMES standards • fungi species (A. niger, A. nidulans, T. reesei) • soil crust

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

Multi-spectral window radiance observations of Cirrus from satellite and aircraft, November 2, 1986 Project FIRE

High resolution infrared radiance spectra achieved from the NASA ER2 airborne HIS experiment are used to analyze the spectral emissivity properties of cirrus clouds within the 8 to 12 micron atmospheric window region. Observations show that the cirrus emissivity generally decreases with increasing wavenumber (i.e., decreasing wavelength) within this band. A very abrupt decrease in emissivity (increase in brightness temperature) exists between 930/cm (10.8 microns) and 1000/cm (10.0 microns), the magnitude of the change being associated with the cirrus optical thickness as observed by lidar. The HIS observations are consistent with theoretical calculations of the spectral absorption coefficient for ice. The HIS observations imply that cirrus clouds can be detected unambiguously from the difference in brightness temperatures observed within the 8.2 and 11.0 micron window regions of the HIRS sounding radiometer flying on the operational NOAA satellites. This ability is demonstrated using simultaneous 25 km resolution HIRS observations and 1 km resolution AVHRR imagery achieved from the NOAA-9 satellite. Finally, the cirrus cloud location estimates combined with the 6.7 micron channel moisture imagery portray the boundaries of the ice/vapor phase of the upper troposphere moisture. This phase distinction is crucial for infrared radiative transfer considerations for weather and climate models, since upper tropospheric water vapor has little effect on the Earth's outgoing radiation whereas cirrus clouds have a very large attenuating effect.

Smith, William L.↗
NASA NTRS1993

Ultraviolet spectroscopy of Nova Muscae 1991

We report on a series of ultraviolet spectroscopic observations made with the IUE satellite, which sampled critical outburst stages of the soft X-ray transient Nova Muscae 1991. Continuum light curves, and a multi-epoch line analysis are presented. In addition, a single epoch optical-UV spectra obtained with the HST/FOS is discussed. The optical-UV continuum fits approximately the 'canonical' fv varies as V exp 1/3 power low expected for thermal emission from steady state accretion disk. The emission line spectrum contains prominent high ionization lines of C IV and N V. Weaker lines are seen at intermittent epochs, including some of lower ionization. The derivation of galactic reddening which has significant implications for distance estimates is discussed. Comparisons with previous SXT sources are considered.

Shrader, C. R.↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Numerical simulations of loops heated to solar flare temperatures. III - Asymmetrical heating

A numerical model is defined for asymmetric full solar flare loop heating and comparisons are made with observational data. The Dynamic Flux Tube Model is used to describe the heating process in terms of one-dimensional, two fluid conservation equations of mass, energy and momentum. An adaptive grid allows for the downward movement of the transition region caused by an advancing conduction front. A loop 20,000 km long is considered, along with a flare heating system and the hydrodynamic evolution of the loop. The model was applied to generating line profiles and spatial X-ray and UV line distributions, which were compared with SMM, P78-1 and Hintori data for Fe, Ca and Mg spectra. Little agreement was obtained, and it is suggested that flares be treated as multi-loop phenomena. Finally, it is concluded that chromospheric evaporation is not an effective mechanism for generating the soft X-ray bursts associated with flares.

Cheng, C.-C.↗
NASA NTRS2013

UV Resonant Raman Spectrometer with Multi-Line Laser Excitation

A Raman spectrometer employs two or more UV (ultraviolet) laser wavel engths to generate UV resonant Raman (UVRR) spectra in organic sampl es. Resonant Raman scattering results when the laser excitation is n ear an electronic transition of a molecule, and the enhancement of R aman signals can be several orders of magnitude. In addition, the Ra man cross-section is inversely proportional to the fourth power of t he wavelength, so the UV Raman emission is increased by another fact or of 16, or greater, over visible Raman emissions. The Raman-scatter ed light is collected using a high-resolution broadband spectrograph . Further suppression of the Rayleigh-scattered laser light is provi ded by custom UV notch filters.

Lambert, James L.↗
NASA NTRS2004

MPT Prediction of Aircraft-Engine Fan Noise

A collection of computer programs has been developed that implements a procedure for predicting multiple-pure-tone (MPT) noise generated by fan blades of an aircraft engine (e.g., a turbofan engine). MPT noise arises when the fan is operating with supersonic relative tip Mach No. Under this flow condition, there is a strong upstream running shock. The strength and position of this shock are very sensitive to blade geometry variations. For a fan where all the blades are identical, the primary tone observed upstream of the fan will be the blade passing frequency. If there are small variations in geometry between blades, then tones below the blade passing frequency arise MPTs. Stagger angle differences as small as 0.1 can give rise to significant MPT. It is also noted that MPT noise is more pronounced when the fan is operating in an unstarted mode. Computational results using a three-dimensional flow solver to compute the complete annulus flow with non-uniform fans indicate that MPT noise can be estimated in a relatively simple way. Hence, once the effect of a typical geometry variation of one blade in an otherwise uniform blade row is known, the effect of all the blades being different can be quickly computed via superposition. Two computer programs that were developed as part of this work are used in conjunction with a user s computational fluid dynamics (CFD) code to predict MPT spectra for a fan with a specified set of geometric variations: (1) The first program ROTBLD reads the users CFD solution files for a single blade passage via an API (Application Program Interface). There are options to replicate and perturb the geometry with typical variations stagger, camber, thickness, and pitch. The multi-passage CFD solution files are then written in the user s file format using the API. (2) The second program SUPERPOSE requires two input files: the first is the circumferential upstream pressure distribution extracted from the CFD solution on the multi-passage mesh, the second file defines the geometry variations of each blade in a complete fan. Superposition is used to predict the spectra resulting from the geometric variations.

Connell, Stuart D.↗
DOE OSTI2023

pyGWBSE: a high throughput workflow package for GW-BSE calculations

Abstract We develop an open-source python workflow package, py GWBSE to perform automated first-principles calculations within the GW-BSE (Bethe-Salpeter) framework. GW-BSE is a many body perturbation theory based approach to explore the quasiparticle (QP) and excitonic properties of materials. GW approximation accurately predicts bandgaps of materials by overcoming the bandgap underestimation issue of the more widely used density functional theory (DFT). BSE formalism produces absorption spectra directly comparable with experimental observations. py GWBSE package achieves complete automation of the entire multi-step GW-BSE computation, including the convergence tests of several parameters that are crucial for the accuracy of these calculations. py GWBSE is integrated with Wannier90 , to generate QP bandstructures, interpolated using the maximally-localized wannier functions. py GWBSE also enables the automated creation of databases of metadata and data, including QP and excitonic properties, which can be extremely useful for future material discovery studies in the field of ultra-wide bandgap semiconductors, electronics, photovoltaics, and photocatalysis.

36 MATERIALS SCIENCE↗