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NASA NTRS1998

A Multi-Scale Sampling Strategy for Detecting Physiologically Significant Signals in AVIRIS Imagery

Models of photosynthetic production at ecosystem and global scales require multiple input parameters specifying physical and physiological surface features. While certain physical parameters (e.g., absorbed photosynthetically active radiation) can be derived from current satellite sensors, other physiologically relevant measures (e.g., vegetation type, water status, carboxylation capacity, or photosynthetic light-use efficiency), are not generally directly available from current satellite sensors at the appropriate geographic scale. Consequently, many model parameters must be assumed or derived from independent sources, often at an inappropriate scale. An abundance of ecophysiological studies at the leaf and canopy scales suggests strong physiological control of vegetation-atmosphere CO2 and water vapor fluxes, particularly in evergreen vegetation subjected to diurnal or seasonal stresses. For example hot, dry conditions can lead to stomatal closure, and associated "downregulation" of photosynthetic biochemical processes, a phenomenon often manifested as a "midday photosynthetic depression". A recent study with the revised simple biosphere (SiB2) model demonstrated that photosynthetic downregulation can significantly impact global climate. However, at the global scale, the exact significance of downregulation remains unclear, largely because appropriate physiological measures are generally unavailable at this scale. Clearly, there is a need to develop reliable ways of extracting physiologically relevant information from remote sensing. Narrow-band spectrometers offer many opportunities for deriving physiological parameters needed for ecosystem and global scale photosynthetic models. Experimental studies on the ground at the leaf- to stand-scale have indicated that several narrow-band features can be used to detect plant physiological status. One physiological signal is caused by xanthophyll cycle pigment activity, and is often expressed as the Photochemical Reflectance Index (PRI). Because the xanthophyll cycle pigments are photoregulatory pigments closely linked to photosynthetic function, this index can be used to derive relative photosynthetic rates. An additional signal with physiological significance is the 970 nm water absorption band, which provides a measure of liquid water content. This feature has been quantified both using a simple 2-band ratio (900/970 nm, here referred to as the "Water Band Index" or WBI;), and using the "continuum removal" method. Current atmospheric correction methods for AVIRIS imagery also obtain quantitative expressions of surface liquid water absorption based on the 970 nm water band and may be comparable to ground-based estimates of water content using this feature. However, physiological interpretations of both the PRI and the WBI are best understood at the leaf and canopy scales, where complications of atmospheric interference and complex stand and landscape features can be minimized, and where experimental manipulations can be readily applied. Currently it is not known whether these physiological indices can be used to derive meaningful physiological information from AVIRIS imagery. In addition to the problem of atmospheric interference, another challenge is that any simple physiological index can be confounded by multiple factors unrelated to physiology, and this problem can become more severe at progressively larger spatial scales. For example, previous work has suggested that both the PRI and the WBI, are strongly correlated with other optical measures of canopy structure (e.g., the Normalized Difference Vegetation Index or green vegetation fraction), indicating a confounding effect of structure on physiological signals at the larger, landscape scale. Furthermore, the normal operating mode of most imaging spectrometers does not allow simultaneous, ground truthing at a level of detail needed for physiological sampling. Additionally, manipulative experiments of physiology are difficult to apply at a geographic scale suitable for comparison with remote imagery, which often works at spatial scales that are several orders of magnitude larger than those typically used for physiological studies. These limitations require the consideration of alternative approaches to validating physiological information derived from AVIRIS data. In this report, we present a multi-scale sampling approach to detecting physiologically significant signals in narrow-band spectra. This approach explores the multi-dimensional data space provided by narrow-band spectrometry, and combines AVIRIS imagery at a large scale, with ground spectral sampling at an intermediate scale, and detailed ecophysiological measurements at a fine scale, to examine seasonally and spatially changing relationships between multiple structural and physiological variables. Examples of this approach are provided by simultaneous sampling of the Normalized Difference Vegetation Index (NDVI), an index of fractional PAR interception and green vegetation cover, the Water Band Index (WBI, an index of liquid water absorption, and the Photochemical Reflectance Index (PRI, an index of xanthophyll cycle pigment activity and photosynthetic light-use efficiency. By directly linking changing optical properties sampled on the ground with measurable physiological states, we hope to develop a basis for interpreting similar signals in AVIRIS imagery.

Gamon, John A.↗
DOE OSTI2023

AutoSourceID-Classifier: Star-galaxy classification using a convolutional neural network with spatial information

Aims.Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images. Methods.The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results. Results.We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Astronomy & Astrophysics↗
DOE OSTI2025

Quantitative Nonlinear Optical Polarimetry with High Spatial Resolution

Nonlinear optical microscopy such as in the optical second-harmonic generation (SHG) modality has become a popular tool today for probing materials in the physical and biological sciences. While imaging and spectroscopy are widely used in the microscopy mode, nonlinear polarimetry, which can shed light on materials’ symmetry and microstructure, is relatively underdeveloped. This is partly because quantitative analytical modeling of the optical SHG response for anisotropic crystals and films largely assumes low-numerical aperture (NA) focusing of light, where the plane-wave approximation is sufficient. Tight focusing provides unique benefits in revealing out-of-plane polarization responses, which cannot be detected by near-plane-wave illumination at normal incidence. Here, we outline a method for quantitatively analyzing SHG polarimetry measurements obtained under high-NA focusing within a microscope geometry. Experiments and simulations of a variety of standard samples, from single crystals to thin films, are in good agreement, including measured and simulated spatial SHG maps of ferroelectric domains. A solution to the inverse problem is demonstrated, where the spatial distribution of an SHG tensor with unknown tensor coefficient magnitudes is determined by experimentally measured polarimetry. The ability to extract the out-of-plane component of the nonlinear polarization in normal incidence is demonstrated, which can be valuable for high-resolution polarimetry of 2D materials, thin films, heterostructures, and uniaxial crystals with a strong out-of-plane response.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

VIPER: Introduction to the Resource Prospecting Mission

With the Artemis Program, NASA plans to return humans to the Moon to stay, which means if there are local materials available, they could be deployed to help support extended lunar stays. Since the moon’s polar regions have confirmed the presence of volatiles, as revealed by LCROSS, LRO and other lunar missions, the next step is to understand the nature and distribution of those candidate resources and how they might be extracted. Recent studies have even indicated local volatiles could be processed into propellants and human life-supporting resources, significantly aiding in sustaining humans on the Moon, and eventually and later to support missions to Mars. The Volatiles Investigating Polar Exploration Resource (VIPER) is an in-situ resource utilization (ISRU) mission within NASA’s Science Mission Directorate (SMD), based on the pathfinding development of the Resource Prospector (RP) mission concept. This clever mission is targeting late 2023 and may spend over 100 days mapping and surveying four different Ice Stability Regions to understand the nature and distribution of water and volatiles already confirmed to be there, including measuring mineralogical content such as silicon and light metals from lunar regolith. The knowledge attained by a mission like VIPER could have many-fold benefits for space exploration, but also commercial applications. VIPER is an essential, early mission supporting the “moon rush” which has developed over the past few years, with both governments and commercial entities making their cases for lunar exploration. VIPER aims to understand just how the water-ice and other volatiles are distributed, both horizontally and vertically, enabling creation of volatiles resource maps, which will guide what might be required to harvest those resources at scale. With sufficient infrastructural investment, led by governments and then optimized by the commercial marketplace, VIPER will be a pathfinder mission addressing key decadal lunar science and early strategic knowledge gaps.

Daniel Andrews↗
DOE OSTI2020

Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.

Rasheed, Fayaz↗
DOE OSTI2022

$K^{*}(892)^0$ meson production in inelastic p+p interactions at 40 and 80 $\text{ GeV }\!/\!c$ beam momenta measured by NA61/SHINE at the CERN SPS

Measurements of $K^{*}(892)^0$ resonance production via its $K^{+}\pi ^{-}$ decay mode in inelastic p+p collisions at beam momenta 40 and 80 $\text{ GeV }\!/\!c$ ($\sqrt{s_{NN}}=8.8$ and 12.3 $\text{ GeV }$) are presented. The data were recorded by the NA61/SHINE hadron spectrometer at the CERN Super Proton Synchrotron. The template method was used to extract the $K^{*}(892)^0$ signal. Transverse momentum and rapidity spectra were obtained. The mean multiplicities of $K^{*}(892)^0$ mesons were found to be $(35.1 \pm 1.3 \mathrm {(stat)} \pm 3.6 \mathrm {(sys))} \cdot 10^{-3}$ at 40 $\text{ GeV }\!/\!c$ and $(58.3 \pm 1.9 \mathrm {(stat)} \pm 4.9 \mathrm {(sys))} \cdot 10^{-3}$ at 80 $\text{ GeV }\!/\!c$. The NA61/SHINE results are compared with the Epos1.99 and Hadron Resonance Gas models as well as with world data. The transverse mass spectra of $K^{*}(892)^0$ mesons and other particles previously reported by NA61/SHINE were fitted within the Blast-Wave model. The transverse flow velocities are close to 0.1–0.2 of the speed of light and are significantly smaller than the ones determined in heavy nucleus-nucleus interactions at the same beam momenta.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Advanced Electron Microscopy of Nanophased Synthetic Polymers and Soft Complexes for Energy and Medicine Applications

After decades of developments, electron microscopy has become a powerful and irreplaceable tool in understanding the ionic, electrical, mechanical, chemical, and other functional performances of next-generation polymers and soft complexes. The recent progress in electron microscopy of nanostructured polymers and soft assemblies is important for applications in many different fields, including, but not limited to, mesoporous and nanoporous materials, absorbents, membranes, solid electrolytes, battery electrodes, ion- and electron-transporting materials, organic semiconductors, soft robotics, optoelectronic devices, biomass, soft magnetic materials, and pharmaceutical drug design. For synthetic polymers and soft complexes, there are four main characteristics that differentiate them from their inorganic or biomacromolecular counterparts in electron microscopy studies: (1) lower contrast, (2) abundance of light elements, (3) polydispersity or nanomorphological variations, and (4) large changes induced by electron beams. Since 2011, the Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory has been working with numerous facility users on nanostructured polymer composites, block copolymers, polymer brushes, conjugated molecules, organic–inorganic hybrid nanomaterials, organic–inorganic interfaces, organic crystals, and other soft complexes. This review crystalizes some of the essential challenges, successes, failures, and techniques during the process in the past ten years. It also presents some outlooks and future expectations on the basis of these works at the intersection of electron microscopy, soft matter, and artificial intelligence. Machine learning is expected to automate and facilitate image processing and information extraction of polymer and soft hybrid nanostructures in aspects such as dose-controlled imaging and structure analysis.

36 MATERIALS SCIENCE↗
NASA NTRS1991

The role of time and speed in NASA's SUNLITE program

The SUNLITE program of NASA's LaRC aims to demonstrate lower noise and better frequency stability for continuous-wave (CW) solid-state lasers in the microgravity environment of space. The program will utilize laser-diode-pumped nonplanar-ring oscillators regulated by ultra-stable high-finesse Fabry-Perot Spectrometers to produce light beams with phase rate or frequency variations as low as 3 Hz. SUNLITE will use the period-method (P-method) to measure the phase rate and frequency stability of the lasers. The P-method was chosen because it requires less memory space for the raw data, because frequencies can be analyzed on-line in real-time simply by reciprocating the periods (fi = 1/pi), and because the mean and variance of the frequencies can be calculated as fast or faster than they can be with the fastest fast Fourier transformations. Furthermore, for a given signal-to-noise power ratio, the P-method requires less data and less computer time to extract the noise components. Although the P-method does require fast Time Interval Counters, the Fourier transformation method requires comparably fast Sampling Volt meters. For either method, however, time and computer speed play a critical role.

Hafele, Joseph C.↗
DOE OSTI2024

Plastic additives in the ocean: Use of a comprehensive dataset for meta-analysis and method development

In excess of 13,000 chemicals are added to plastics (‘additives’) to improve performance, durability, and production of plastic products. They are categorized into numerous chemical classes including flame retardants, light stabilizers, antioxidants, and plasticizers. While research on plastic additives in the marine environment has increased over the past decade, there is a lack of methodological standardization. To direct future measurement of plastic additives, we compiled a first-of-its-kind dataset of literature assessing plastic additives in marine environments, delineated by sample type (plastic debris, seawater, sediment, biota). Using this dataset, we performed a meta-analysis to summarize the state of the science. Currently, our dataset includes 217 publications published between 1978 and May 2023. The majority of publications analyzed plastic additives in biota collected from Europe and Asia. Analyses concentrated on plasticizers, brominated flame retardants, and bisphenols. Common sample preparation techniques included Solvent - Agitation extraction for plastic, sediment, and biota samples, and Solid Phase Extraction for seawater samples with dichloromethane and solvent mixtures including dichloromethane as the organic extraction solvent. Finally, most analyses were performed utilizing gas chromatography/mass spectrometry. There are a variety of data gaps illuminated by this meta-analysis, most notably the small number of compounds that have been targeted for detection compared to the large number of additives used in plastic production. The provided dataset facilitates future investigation of trends in plastic additive concentration data in the marine environment (allowing for comparison to toxicity thresholds) and acts as a starting point for optimizing and harmonizing plastic additive analytical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Analysis of IRAS solar system dust data

Data in the Infrared Astronomical Satellite (IRAS) Zodiacal History File were analyzed to extract dust band locations and peak brightness measurements from approximately 1,000 individual IRAS scans. The study had three goals. One was to show that the prominent solar system dust bands are associated with Hirayama asteroid families and thus that collisions between asteroids account for a significant fraction of the particles in the zodiacal cloud. Recent work suggests that while the Hirayama families are a major source of the dust in the bands, there may also be contributions from two or three smaller, more recently recognized asteroid families. A second goal was to show that there is evidence in the IRAS dust data for the transport of particles from asteroid belt to the Earth by Poynting-Robertson light drag and thus account for the fact that asteroid particles are collected in the Earth's stratosphere. Results of the study will confirm the location of the dust bands within the inner asteroid belt, and show conclusively that the material seen by IRAS is now spread over a wide range of distances from the sun. The third goal was to construct a model of the background zodiacal cloud that satisfies the proper dynamical constraints. Figures are provided to show the scans processed to remove zodiacal background and Galactic signals, and the resulting polynomial fits to the 25 micron scan. The latter provided objective estimates of band widths, peak locations, and peak fluxes. Modelling and analysis of the resulting band data has been presented at several conferences and is the subject of a number of forthcoming papers.

Dermott, S. F.↗
DOE OSTI2024

Entanglement of excitons by acoustic guiding

A system is described that exhibits the functionality of a beam-splitter, typically an optical device that splits a beam of light in two. In this case, the beams are acoustic pulses and can lead to the creation of a Wannier-Mott exciton: a bound state of an electron and an electron hole whose attraction to each other is maintained by the electrostatic Coulomb force. This exciton beam-splitter is lossy (i.e., involves the dissipation of electrical or electromagnetic energy). Half of the time the exciton is radiated away. Nevertheless, if the exciton is not lost, the exciton is now in a superposition of two states that can be well separated in position. Four such beam-splitters can be used to make an exciton interferometer that uses the interference patterns from the interacting acoustic pulses to extract information.

Yurke, Bernard↗
DOE OSTI2025

Time-dependent phenomena in correlated materials

Understanding time-dependent processes and light-matter interaction in strongly correlated materials, and the interplay between electronic, orbital, vibrational, and spin degrees of freedom, is a cornerstone of condensed matter. These mechanisms can be proven by measuring the response of the systems to time-dependent perturbations. The corresponding time scales are dictated by the way light couples to the different excitations, and how these excitations exchange energy and momentum. Our research advances our understanding of these processes, and the interpretation of different equilibrium and time-resolved spectroscopies. Our project encompasses two main themes: (i) developing and refining computational techniques to study non-equilibrium spectroscopies including non-perturbative effects and (ii) applications to non-equilibrium phenomena. We have developed a new computational approach that works directly in the time domain: by including all the degrees of freedom involved in the scattering process (e.g. electrons, photons, neutrons), we solve the time dependent problem: a faithful numerical simulation of the experiment. By measuring the energy and momentum of the outgoing particles, we can extract information about the energy and momentum absorbed by the system. Prior to our work, people attempting to model and calculate non-equilibrium spectral functions relied on a description of the scattering cross section based on a formulation in the frequency domain, a treatment that is extremely cumbersome and complex. Our technique works in and out of equilibrium and can reproduce spectra by several spectroscopic techniques, such as time-resolved photoemission, neutron scattering, Raman, X-ray spectroscopies (RIXS, Auger, XAS, XMCD), and, by not relying on analytical approximations, yields results that reveal novel overlooked transient mechanisms. These tools provide sorely needed intuition for understanding the phenomenology of strongly correlated materials and will help experimentalists in identifying signatures of relevant excitations in pump-probe experiments, such as those conducted in DOE supported facilities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Baryon–Antibaryon Photoproduction off the Proton

The GlueX Experiment at Jefferson Lab uses linearly polarized photon beam to study the photoproduction of light mesons and baryons off a proton target with unprecedented precision. We have observed p¯p photoproduction and, for the first time, ?¯? photoproduction from thresholds up to E = 11.6 GeV. We reproduce the observed kinematic distributions with a phenomenological model that includes t-channel Regge exchange and double Regge exchange. The model uses few parameters to match all the kinematic spectra via an optimization algorithm developed specifically for this purpose. We report the total cross sections of the two reactions, as well as differential cross sections with respect to various momentum transfers and invariant mass spectra of p¯p, ?¯?, p¯? systems which show enhancements right above production thresholds. Furthermore, the beam asymmetries of the p¯p system are extracted from the GlueX data to further probe the nature of the t-channel Regge exchanges. We also report preliminary measurements of the spin polarizations of the individual hyperons. No prominent resonance structure was found in these reaction channels, but the angular distributions and the correlation of longitudinal momenta indicate the existence of multiple production mechanisms. Besides a dominant forward peak in the polar angle of the baryon-antibaryon pair in t-channel production, we see wide-angle antibaryon distributions different from that of the baryon. In the hyperon channel, we see a clear separation between the photoproduction of the ?¯?, p¯? systems.

Li, Hao↗
DOE OSTI2021

Reaction losses of charged particles in CsI(Tl) crystals

To efficiently detect energetic light charged particles, it is common to use arrays of energy-loss telescopes involving two or more layers of detection media. As the energy of the particles increases, thicker layers are usually needed. However, carrying out measurements with thick-telescopes may require corrections for the losses due to nuclear reactions induced by the incident particles on nuclei within the detector and for the scattering of incident particles out of the detector, without depositing their full energy in the active material. In this paper, we develop a method for measuring such corrections and determine the reaction and out-scattering losses for data measured with the silicon-CsI(Tl) telescopes of the newly developed HiRA10 array. Here, the extracted efficiencies are in good agreement with model predictions using the GEANT4 reaction loss algorithm for Z = 1 and Z = 2 isotopes. After correcting for the HiRA10 geometry, we obtain a general function that describes the loss of efficiency due to reaction losses in CsI(Tl) crystals as a function of range.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Hybrid Machine Learning for Scanning Near-Field Optical Spectroscopy

The underlying physics behind an experimental observation often lacks a simple analytical description. This is especially the case for scanning probe microscopy techniques, where the interaction between the probe and the sample is nontrivial. Realistic modeling to include the details of the probe is always exponentially more difficult than its "spherical cow" counterparts. On the other hand, a well-trained artificial neural network based on real data can grasp the hidden correlation between the signal and sample properties. In this work, we show that, via a combination of model calculation and experimental data acquisition, a physics-infused hybrid neural network can predict the tip-sample interaction in the widely used scattering-type scanning near-field optical microscope. This hybrid network provides a long-sought solution for accurate extraction of material properties from tip-specific raw data. The methodology can be extended to other scanning probe microscopy techniques as well as other data-oriented physical problems in general.

36 MATERIALS SCIENCE↗
NASA NTRS2013

FRET-Aptamer Assays for Bone Marker Assessment, C-Telopeptide, Creatinine, and Vitamin D

Astronauts lose 1.0 to 1.5% of their bone mass per month on long-duration spaceflights. NASA wishes to monitor the bone loss onboard spacecraft to develop nutritional and exercise countermeasures, and make adjustments during long space missions. On Earth, the same technology could be used to monitor osteoporosis and its therapy. Aptamers bind to targets against which they are developed, much like antibodies. However, aptamers do not require animal hosts or cell culture and are therefore easier, faster, and less expensive to produce. In addition, aptamers sometimes exhibit greater affinity and specificity vs. comparable antibodies. In this work, fluorescent dyes and quenchers were added to the aptamers to enable pushbutton, one-step, bind-and-detect fluorescence resonance energy transfer (FRET) assays or tests that can be freeze-dried, rehydrated with body fluids, and used to quantitate bone loss of vitamin D levels with a handheld fluorometer in the spacecraft environment. This work generated specific, rapid, one-step FRET assays for the bone loss marker C-telopeptide (CTx) when extracted from urine, creatinine from urine, and vitamin D congeners in diluted serum. The assays were quantified in nanograms/mL using a handheld fluorometer connected to a laptop computer to convert the raw fluorescence values into concentrations of each analyte according to linear standard curves. DNA aptamers were selected and amplified for several rounds against a 26- amino acid form of CTx, creatinine, and vitamin D. The commonalities between loop structures were studied, and several common loop structures were converted into aptamer beacons with a fluorophore and quencher on each end. In theory, when the aptamer beacon binds its cognate target (CTx bone peptide, creatinine, or vitamin D), it is forced open and no longer quenched, so it gives off fluorescent light (when excited) in proportion to the amount of target present in a sample. This proportional increase in fluorescence is called a "lights on" FRET response. The vitamin D aptamer beacon gives a "lights off" or inversely proportional fluorescence response to the amount of vitamin D present in diluted serum. These FRET-aptamer assays are rapid (<30 minutes), sensitive (low ng/mL detection limits), and quite easy to carry out (add sample, mix, and detect in the handheld reader). Benefits include the speed of the assays as well as the small amount of space taken up by the handheld reader and cuvette assays. The aptamer DNA sequences represent novel additional features of the existing (patent-pending) FRET-aptamer assay platform.

Bruno, John G.↗
DOE OSTI2025

Radiation-resilient InAs quantum dot lasers

Displacement damage from particle radiation increases the threshold current of semiconductor lasers, impeding the deployment of photonic systems in harsh radiation environments. Replacing conventional quantum well (QW) gain regions with quantum dots (QDs) has been shown to suppress the radiation-induced increase in threshold current owing to three-dimensional carrier confinement, which effectively segregates charge carriers away from radiation-induced defects. However, radiation-induced change in threshold current is also affected by extrinsic design elements of a laser, such as photon lifetime, and therefore provides only a partial assessment of the radiation hardness. In this work, we advance the understanding of the radiation resiliency of InAs QD lasers by extracting the change in the nonradiative recombination rate after radiation exposure, which provides a more fundamental assessment of the intrinsic radiation hardness of InAs QD gain regions. We find that carriers that populate InAs QD states have a nonradiative recombination rate that is over an order-of-magnitude less sensitive to neutron radiation relative to carriers in InGaAsP QWs. InAs QD lasers must be designed such that carriers primarily occupy QD states, preventing carrier spillover into surrounding barrier layers to obtain the maximum benefit. Furthermore, we show that enhanced radiation hardness is observed in InAs QD lasers grown on both highly lattice-mismatched silicon substrates and native GaAs substrates, further broadening the appeal of InAs QD lasers as reliable light sources for photonic systems operating in harsh radiation environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Optimizing Simulation Parameters for Weak Lensing Analyses Involving Non-Gaussian Observables

We performed a series of numerical experiments to quantify the sensitivity of the predictions for weak lensing statistics obtained in ray-tracing dark matter (DM)-only simulations, to two hyper-parameters that influence the accuracy as well as the computational cost of the predictions: the thickness of the lens planes used to build past light cones and the mass resolution of the underlying DM simulation. The statistics considered are the power spectrum (PS) and a series of non-Gaussian observables, including the one-point probability density function, lensing peaks, and Minkowski functionals. Counterintuitively, we find that using thin lens planes (< 60 h {sup −1} Mpc on a 240 h {sup −1} Mpc simulation box) suppresses the PS over a broad range of scales beyond what would be acceptable for a survey comparable to the Large Synoptic Survey Telescope (LSST). A mass resolution of 7.2 × 10{sup 11} h {sup −1} M {sub ⊙} per DM particle (or 256{sup 3} particles in a (240 h {sup −1} Mpc){sup 3} box) is sufficient to extract information using the PS and non-Gaussian statistics from weak lensing data at angular scales down to 1′ with LSST-like levels of shape noise.

79 ASTRONOMY AND ASTROPHYSICS↗