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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Transitional Disks Associated with Intermediate-Mass Stars: Results of the SEEDS YSO Survey

Protoplanetary disks are where planets form, grow, and migrate to produce the diversity of exoplanet systems we observe in mature systems. Disks where this process has advanced to the stage of gap opening, and in some cases central cavity formation, have been termed pre-transitional and transitional disks in the hope that they represent intermediate steps toward planetary system formation. Recent reviews have focussed on disks where the star is of solar or sub-solar mass. In contrast to the sub-millimeter where cleared central cavities predominate, at H-band some T Tauri star transitional disks resemble primordial disks in having no indication of clearing, some show a break in the radial surface brightness profile at the inner edge of the outer disk, while others have partially to fully cleared gaps or central cavities. Recently, the Meeus Group I Herbig stars, intermediate-mass PMS stars with IR spectral energy distributions often interpreted as flared disks, have been proposed to have transitional and pre-transitional disks similar to those associated with solar-mass PMS stars, based on thermal-IR imaging, and sub-millimeter interferometry. We have investigated their appearance in scattered light as part of the Strategic Exploration of Exoplanets and Disks with Subaru (SEEDS), obtaining H-band polarimetric imagery of 10 intermediate-mass stars with Meeus Group I disks. Augmented by other disks with imagery in the literature, the sample is now sufficiently large to explore how these disks are similar to and differ from T Tauri star disks. The disk morphologies seen in the Tauri disks are also found for the intermediate-mass star disks, but additional phenomena are found; a hallmark of these disks is remarkable individuality and diversity which does not simply correlate with disk mass or stellar properties, including age, including spiral arms in remnant envelopes, arms in the disk, asymmetrically and potentially variably shadowed outer disks, gaps, and one disk where only half of the disk is seen in scattered light at H. We will discuss our survey results in terms of spiral arm theory, dust trapping vortices, and systematic differences in the relative scale height of these disks compared to those around Solar-mass stars. For the disks with spiral arms we discuss the planet-hosting potential, and limits on where giant planets can be located. We also discuss the implications for imaging with extreme adaptive optics instruments. Grady is supported under NSF AST 1008440 and through the NASA Origins of Solar Systems program on NNG13PB64P. JPW is supported NSF AST 100314. 0) in marked contrast to protoplanetary disks, transitional disks exhibit wide range of structural features1) arm visibility correlated with relative scale height in disk2) asymmetric and possibly variable shadowing of outer portions some transitional disks3) confirm pre-transitional disk nature of Oph IRS 48, MWC 758, HD 169142, etc.

Protoplanetary disks↗
DOE OSTI2025

Electrically Reconfigurable Liquid Metal Nanophotonic Platform for Color Display and Imaging

Dynamically tunable optical materials and device architectures are essential for future photonic technologies, yet conventional solid metals lack the intrinsic tunability required for advanced functionalities. Gallium-based liquid metals (LMs) present an appealing alternative thanks to their distinctive mechanical and optical properties; however, their practical integration in tunable photonic elements remains largely unexplored. Here, in this study, an electrochemically controlled nanophotonic platform is demonstrated that integrates a dynamically reconfigurable LM ground plane with gold nanoantenna arrays within a microfluidic system, enabling precise and reversible modulation of optical resonances across the visible to mid-infrared spectral ranges. By employing moderate operational voltages (1.5–3.0 V), real-time tuning of high-resolution structural color patterns is achieved through nanoscale control of the interfacial gap between the LM and Au nanoantennas. This innovative platform facilitates electrically programmable, high-contrast color patterns suitable for dynamic optical displays, secure anti-counterfeiting labels, and imaging applications. Additionally, this platform enables tunable mid-infrared spectral responses, which may be utilized for chemical and biological sensing applications. This versatile integrated LM-based nanophotonic platform opens new paths toward multifunctional, actively tunable/reconfigurable photonic device and system technologies.

Imaging↗
DOE OSTI2024

Scanning tunneling spectroscopy of surface-oxidized Gallium-stabilized δ -phase plutonium

Here, the first contiguous experimental scanning tunneling spectroscopy (STS) measurements of the electronic structure of a plutonium (Pu) surface are presented and compared to current theoretical results. The experiments took place under UHV conditions, for which Pu is known to retain a native surface oxide. The STS data shows that no band gap is observable at room temperature. Theoretical calculations predict that bulk Pu oxides are semiconductors, but the spectral results for the cleaned Pu surface native oxide under UHV conditions could be better characterized as that of a semimetal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

High-temperature Majorana fermions in magnet-superconductor hybrid systems

Magnet-superconductor hybrid (MSH) structures represent one of the most promising platforms to realize, control, and manipulate Majorana modes using scanning tunneling methods. By depositing either chains or islands of magnetic atoms on the surface of a conventional, elemental superconductor such as Pb or Re, topological superconducting phases can emerge. They feature either localized Majorana bound states at the chain ends or dispersing chiral Majorana modes at the island's boundary. However, some of these experiments have not reached the spectral resolution to clearly distinguish between topological Majorana and trivial Shiba states due to very small superconducting gap sizes and experiments performed at sub-Kelvin temperatures. Here we consider superconducting substrates with unconventional spin-singlet pairing, including high-temperature d -wave and extended s -wave superconductors. We derive topological phase diagrams and compute edge states for cylinder and island geometries and discuss their properties. Several time-reversal invariant topological superconducting phases of the Zhang-Kane-Mele type are found and discussed. Addiotnally, we review one-dimensional MSH structures and show that parameters to realize topologically nontrivial magnetic chains embedded into a larger, two-dimensional substrate differ from the purely one-dimensional case. Quite generally we find that unconventional superconducting substrates work as well as the conventional s -wave substrates to realize topological phases. In particular, iron-based pnictide and chalcogenide superconductors are the most promising class of substrates for future high-temperature MSH systems.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

The Search for New Molecular Species in the Atmosphere of Titan

The atmosphere of Saturn’s moon, Titan, contains a vast array of minor molecular constituents originating from the dissociation of its primary compounds, N2and CH4. The extent of Titan’s photochemical network was revealed by ionospheric measurements from the Cassini orbiter, leaving substantial gaps in the corresponding neutral inventory typically probed through infrared spectroscopy. Utilizing the unprecedented sensitivity and high spectral resolution of the Atacama Large Millimeter/submillimeter Array (ALMA) at longer wavelengths, we searched for additional trace gases in Titan’s atmosphere during 2016, 2017,and 2019to further characterize Titan’s atmospheric and surface composition. These observations have resulted in the spectroscopic detections of the small cyclic molecule, cyclopropenylidene (c-C3H2), and the largest nitrile to date, methyl cyanoacetylene (CH3C3N), for the first time in Titan’s atmosphere –or anywhere else in the Solar System. We employed radiative transfer models to determine the volume mixing ratio of both species in Titan’s middle and upper atmosphere (altitudes > 350 km)and constrained the total column densities for the incorporation into future photochemical models of Titan’s atmosphere. Discrepancies between these results and current models necessitates the need for dedicated laboratory and modeling studies regarding the production pathways for trace complex organics in Titan’s atmosphere. Additionally, the measurement of previously undetected molecular species provides further incentive for the study of planetary atmospheres in the (sub)millimeter regime with facilities such as ALMA.

A E Thelen↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

All the light we cannot see: Climate manipulations leave short and long‐term imprints in spectral reflectance of trees

Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change.

Stefanski, Artur [Department of Forest Resources U↗
NASA NTRS2022

Using Machine Learning for Timely Estimates of Ocean Color Information From Hyperspectral Satellite Measurements in the Presence of Clouds, Aerosols, and Sunglint

Retrievals of ocean color from space are important for better understanding of the ocean ecosystem but can be limited under conditions such as clouds, aerosols, and sunglint. Many ocean color algorithms use a few selected spectral bands to perform an atmospheric correction and then derive the upwelling radiance from the ocean. The limitations in the atmospheric correction under certain conditions lead to many gaps in daily spatial coverage of ocean color retrievals. To address these limitations, we introduce a new approach that uses machine learning to estimate ocean color from top of atmosphere radiances or reflectance measurements. In this approach, a principal component analysis is used to decompose the hyperspectral measurements into spectral features that describe the scattering and absorption of the atmosphere and the underlying surface. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from the MODIS atmospheric correction algorithm. This machine learning approach is independent of a priori information and does not rely on any radiative transfer modeling. We apply the approach to two hyperspectral UV/VIS instruments, the ozone monitoring instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI), using measurements from 320–500 nm to show that it can be used to reproduce ocean color properties in less-than-ideal conditions. This machine learning approach complements the current atmospheric correction ocean color retrievals by filling in the gaps resulting from cloud, aerosol, and sunglint contamination. This method can be applied to the future hyperspectral Ocean Color Instrument (OCI), which will be onboard NASA’s Plankton, Aerosol Cloud, ocean Ecosystem (PACE) ocean color satellite set to launch in 2024.

Ocean color↗
NASA NTRS1995

Global tropospheric and total ozone monitoring with a Double-Etalon Fabry-Perot interferometer

Knowledge of the global scale distribution of atmospheric ozone and its temporal variability can be achieved using a satellite-based nadir-viewing device making high spectral resolution measurements with high signal-to-noise ratios. This would enable observation in the pressure-broadened wings of strong O3 lines while minimizing the impact of undesirable signal contributions associated with, for example, the terrestrial surface and interfering species. The Fabry-Perot interferometer (FPI) provides high spectral resolution and high throughput capabilities that are essential for this measurement task. The periodic nature of the Fabry-Perot instrument function can be advantageous when observation of periodic spectra is desired. However, for most applications, additional optical elements are necessary to reduce the effect of unwanted passbands. This is frequently accomplished using additional Fabry-Perot etalons in a series configuration in conjunction with a bandpass filter. This paper discusses a Fabry-Perot interferometer conceptual instrument design to achieve tropospheric and total ozone monitoring capability from a satellite-based nadir-viewing geometry. The design involves a double-etalon fixed-gap series configuration FPI along with an ultra-narrow bandpass filter to achieve single-order operation with an overall spectral resolution of approximately .068 cm(exp -1). The impact of inter-etalon reflections has been reduced to acceptable levels by placement of a slightly attenuating medium in between the etalons. A passive device is selected for low power consumption, and continuous day/night coverage, independent of solar zenith angle, is enabled by observing within the strong 9.6 micron ozone infrared band. The IR-FPI detection will be performed through implementation of the new Circle to Line Interferometer Optical (CLIO) system, developed by researchers at the Space Physics Research Laboratory (SPRL) of the University of Michigan, to accomplish focal plane fringe detection; the CLIO system converts the circular interferometric fringes into a linear pattern which then can be detected by conventional linear array detectors. A multiplex signal advantage is achievable as all necessary frequencies can be measured simultaneously using a multichannel configuration. Through proper selection of channel spectral regions, the FPI optimized for tropospheric O3 measurements can simultaneously observe a stratospheric component and thus the total O3 column abundance.

Larar, Allen M.↗
DOE OSTI2024

Electronic, direct optical, and phonon-assisted optical properties of 4H Si from first principles

The cubic polytype of silicon (Si) is the most commercialized semiconductor material and finds applications in numerous electronic and optoelectronic devices, such as solar cells. However, recent reports on the synthesis of the hexagonal 4H Si polytype have attracted the attention of the scientific community to understand its functional properties. Here, we report the electronic, vibrational, and optical properties of the 4H Si polytype obtained with predictive first-principles calculations, with an emphasis of phonon-assisted absorption in the indirect regime. Compared to the cubic polytype, 4H Si shows a slightly narrower indirect gap by ∼0.05 eV. The calculated phonon-assisted optical spectra show that 4H Si exhibits a stronger absorption coefficient than cubic Si across the visible and IR spectral regions. We further evaluate the short-circuit current density of textured thin-films. We demonstrate that 4H Si can achieve the same short-circuit current density for a five times thinner film compared to the cubic polytype, which mainly resulted from absorption in the indirect gap regime. Our work demonstrates the advantages of 4H Si for thin-film silicon-based solar-cell applications.

Materials Science↗
DOE OSTI2023

Avoided Level Crossing and Entangled States of Interacting Hydrogen Molecules Detected by the Quantum Superposition Microscope

Pump–probe measurements by ultrashort THz pulses can be used to excite and follow the coherence dynamics in the time domain of single hydrogen molecules (H 2 ) in the junction of a scanning tunneling microscope (STM). By tailoring the resonance frequency through the sample bias, we identified two spectral signatures of the interactions among multiple H 2 molecules. First, the avoided level crossing featured by energy gaps ranging from 20 to 80 GHz was observed because of the level repulsion between two H 2 molecules. Second, the tip can sense the signal of H 2 outside the junction through the projective measurement on the H 2 inside the junction, owing to the entangled states created through the interactions. A dipolar-type interaction was integrated into the tunneling two-level system model of H 2 , enabling accurate reproduction of the observed behaviors. Furthermore, our results obtained by the quantum superposition microscope reveal the intricate quantum mechanical interplay among H 2 molecules and additionally provide a 2D platform to investigate unresolved questions of amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Towards higher frequencies in a compact prebunched waveguide THz-FEL

Free-electron-lasers fill a critical gap in the space of THz-sources as they can reach high average and peak powers with spectral tunability. Using a waveguide in a THz FEL significantly increases the coupling between the relativistic electrons and electromagnetic field enabling large amounts of radiation to be generated in a single passage of electrons through the undulator. In addition to transversely confining the radiation, the dispersive properties of the waveguide critically affect the velocity and slippage of the radiation pulse which determine the central frequency and bandwidth of the generated radiation. In this paper, we characterize the spectral properties of a compact waveguide THz FEL including simultaneous lasing at two different frequencies and demonstrating tuning of the radiation wavelength in the high frequency branch by varying the beam energy and ensuring that the electrons injected into the undulator are prebunched on the scale of the resonant radiation wavelength.

Experimental particle physics↗
DOE OSTI2026

Influence of Markovianity and self-consistency on time-resolved spectral functions of driven quantum systems

We present a systematic comparison of the real-time Dyson expansion (RTDE) with established nonequilibrium Green's function (GF) approaches for simulating driven, interacting quantum systems. Focusing on density matrix dynamics, time-off-diagonal GFs, and time-resolved photoemission spectra, we benchmark RTDE against fully self-consistent Kadanoff-Baym equation (KBE) calculations, the generalized Kadanoff-Baym ansatz, and exact diagonalization for small systems using second-order many-body perturbation theory. Using a driven two-band Hubbard model, we show that mean-field single-particle density matrix trajectories provide a reliable baseline for RTDE across a broad range of interaction strengths and excited-carrier populations. Further, RTDE accurately captures correlation effects in the GFs, including long-lived oscillations and revivals that are strongly suppressed by the overdamping inherent to self-consistent KBE schemes. As a consequence, RTDE resolves rich nonequilibrium spectral structure in time-resolved photoemission, such as interaction- and population-dependent quasiparticle splittings and band gap renormalization, which are largely washed out in self-consistent approaches yet are present in exact solutions. Furthermore, our results demonstrate that RTDE bridges the gap between mean-field propagation and full two-time KBE simulations, retaining favorable linear scaling while capturing essential dynamical correlations relevant for ultrafast spectroscopy.

Electronic structure↗
NASA NTRS2026

Optimization of X-ray Absorbers for High-Resolution TES Detectors in NewATHENA X-IFU

NewATHENA’s X-ray Integral Field Unit (X-IFU) uses a large-format array of Transition Edge Sensor (TES) microcalorimeters coupled with absorbers made of gold and bismuth providing 4 eV FWHM resolution up to 7 keV in the 0.2- 12 keV band. X-ray absorbers must be thick enough for photon absorption, maintain low heat capacity for energy resolution, and have good thermalization properties. The X-IFU requires total Quantum Efficiency (QE) of 96%, 87%, and 63% at 1, 7, and 9.5 keV, respectively. Optimal thicknesses are 1.05 µm gold and 5.5 µm bismuth to achieve 0.731 pJ/K at 90 mK and 87% QE at 7 keV. While typical TES absorbers are 3-4 µm thick, producing the required 5.5 µm Bi absorbers via standard electroplating creates enlarged grains and surface roughness. The increased roughness and grain size variability produced with our standard recipe have resulted in instances of 1) low energy spectral tails 2) spectral broadening of the energy resolution and 3) thermal shorts between pixels when a large grain bridges the gap between absorbers. In this study, we have introduced a new fabrication process and altered the morphology of the thick Bi through changes in the electroplating process. The process changes are intended to address all three issues as well as reduce particulate contamination observed on the finished detector arrays.

Absorber↗
DOE OSTI2025

Probing the PeV region in the astrophysical neutrino spectrum using 𝜈 𝜇 from the Southern sky

IceCube has observed a diffuse astrophysical neutrino flux over the energy region from a few TeV to a few PeV. At PeV energies, the spectral shape is not yet well measured due to the low statistics of the data. This analysis probes the gap between 1 and 10 PeV by using high-energy downgoing muon neutrinos. Here, to reject the large atmospheric muon background, two complementary techniques are combined. The first technique selects events with high stochasticity to reject atmospheric muon bundles whose stochastic energy losses are smoothed due to high muon multiplicity. The second technique vetoes atmospheric muons with the IceTop surface array. Using 9 yrs of data, we found two neutrino candidate events in the signal region, consistent with expectation from background, each with relatively high signal probabilities. A joint maximum likelihood estimation is performed using this sample and an independent 9.5-yr sample of tracks to measure the neutrino spectrum. A likelihood ratio test is done to compare the single power-law (SPL) vs SPL+cutoff hypothesis; the SPL+cutoff model is not significantly better than the SPL. High-energy astrophysical objects from four source catalogs are also checked around the direction of the two events. No significant coincidence was found.

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗
NASA NTRS1992

CCD reflectance spectra of selected asteroids. I - Presentation and data analysis considerations

Narrowband reflectance spectra have been acquired which contribute to the library of asteroid data in the visible and near-IR spectral regions. The spectra support the existence of aqueous alteration products on asteroids located in the outer part of the main asteroid belt out to at least 4 AU. No evidence for features similar to the spectral features of ordinary chondrite meteorites was found in the spectra of asteroids located near the 3:1 Kirkwood Gap chaotic zone.

Vilas, Faith↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗