SEARCH · Search NASA

Results for “physical samples”

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.

SourceResearch connectionFrom yearThrough year

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

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

In engineering and aerospace applications, it is vital to operational success to have insight into the expected performance and health of physical systems. The field of prognostics and health management provides quantitative methods for monitoring, predicting, and managing system health. Prognostics algorithms can be employed to assess the current state of a system, propagate the system throughout time, and predict potential anomalies or failures that may occur. While they can provide accurate prediction results, effective prognostics algorithms can be challenging to use in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for future remaining useful life predictions. In this work, we implement new algorithmic approaches for prediction, quantitatively compare them via a battery degradation use-case, and provide recommendations of potential improvements to a prognostics framework. One approach to prediction is through sampling, whereby the current state of a physical system is sampled many times and each sample is propagated forward until failure is reached, resulting in a distribution of failure values. To improve the efficiency of this process, we implemented five new algorithmic approaches to prediction, including three distinct sampling methods (standard Monte Carlo, Quasi-Monte Carlo, and Latin Hypercube Sampling), a variable time step algorithm, and a variable sample size algorithm. To compare the algorithms, we employ a variety of metrics designed specifically to analyze both computational efficiency and model accuracy. Our metrics include accuracy to compare the average predicted value to ground truth, mean absolute deviation to illustrate dispersion, specific percentile error to describe accuracy within a user-defined risk tolerance, and code run-time. To quantitatively analyze our results, we employ a use-case of degradation of a Lithium-ion battery. We use an electrochemistry-based model to describe the current health state of the battery, and implement our prediction algorithms to propagate forward in time until end-of-discharge (EOD) is reached. Notably, through this work it was found that none of our sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. We find that while the sampling methods are unique, the distributions they generate are similar, ultimately producing final predictions that are nearly identical. In exploring the effect of the time step within the prediction algorithm, we found that prediction accuracy was highly dependent on the time step used, and that implementing a variable time step within a particular prediction may provide an increase in computational efficiency while also maintaining prediction accuracy. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment can result in improved computation speed and maintained prediction accuracy. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency.

prognostics↗

NASA NTRS1998

Modeling Code Is Helping Cleveland Develop New Products

Master Builders, Inc., is a 350-person company in Cleveland, Ohio, that develops and markets specialty chemicals for the construction industry. Developing new products involves creating many potential samples and running numerous tests to characterize the samples' performance. Company engineers enlisted NASA's help to replace cumbersome physical testing with computer modeling of the samples' behavior. Since the NASA Lewis Research Center's Structures Division develops mathematical models and associated computation tools to analyze the deformation and failure of composite materials, its researchers began a two-phase effort to modify Lewis' Integrated Composite Analyzer (ICAN) software for Master Builders' use. Phase I has been completed, and Master Builders is pleased with the results. The company is now working to begin implementation of Phase II.

Source record↗

DOE OSTI2021

Resistance, Resilience, and Recovery of Dryland Soil Bacterial Communities Across Multiple Disturbances

Dryland ecosystems are sensitive to perturbations and generally slow to recover post disturbance. The microorganisms residing in dryland soils are especially important as they contribute to soil structure and nutrient cycling. Disturbance can have particularly strong effects on dryland soil structure and function, yet the natural resistance and recovery of the microbial components of dryland soils has not been well documented. In this study, the recovery of surface soil bacterial communities from multiple physical and environmental disturbances is assessed. Samples were collected from three field sites in the vicinity of Moab, UT, United States, 6 to 7 years after physical and climate disturbance manipulations had been terminated, allowing for the assessment of community recovery. Additionally, samples were collected in a transect that included three habitat patches: the canopy zone soils under the dominant shrubs, the interspace soils that are colonized by biological soil crusts, and edge soils at the plot borders. Field site and habitat patch were significant factors structuring the bacterial communities, illustrating that sites and habitats harbored unique soil microbiomes. Across the different sites and disturbance treatments, there was evidence of significant bacterial community recovery, as bacterial biomass and diversity were not significantly different than control plots. There was, however, a small number of 16S rRNA gene amplicon sequence variants that distinguished particular treatments, suggesting that legacy effects of the disturbances still remained. Taken together, these data suggest that dryland bacterial communities may possess a previously unappreciated potential to recover within years of the original disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1999

Mars Solar Balloon Landed Gas Chromatograph Mass Spectrometer

A Mars surface lander Gas Chromatograph Mass Spectrometer (GCMS) is described to measure the chemical composition of abundant and trace volatile species and isotope ratios for noble gases and other elements. These measurements are relevant to the study of atmospheric evolution and past climatic conditions. A Micromission plan is under study where a surface package including a miniaturized GCMS would be delivered to the surface by a solar heated hot air balloon based system. The balloon system would be deployed about 8 km above the surface of Mars, wherein it would rapidly fill with Martian atmosphere and be heated quickly by the sun. The combined buoyancy and parachuting effects of the solar balloon result in a surface package impact of about 5 m/sec. After delivery of the package to the surface, the balloon would ascend to about 4 km altitude, with imaging and magnetometry data being taken for the remainder of the daylight hours as the balloon is blown with the Martian winds. Total atmospheric entry mass of this mission is estimated to be approximately 50 kg, and it can fit as an Ariane 5 piggyback payload. The GCMS would obtain samples directly from the atmosphere at the surface and also from gases evolved from solid phase material collected from well below the surface with a Sample Acquisition and Transport Mechanism (SATM). The experiment envisioned in the Mars Micromission described would obtain samples from a much greater depth of up to one meter below the surface, and would search for organic molecules trapped in ancient stratified layers well below the oxidized surface. Insitu instruments on upcoming NASA missions working in concert with remote sensing measurement techniques have the potential to provide a more detailed investigation of mineralogy and the extent of simple volatiles such as CO2 and H2O in surface and subsurface solid phase materials. Within the context of subsequent mission opportunities such as those provided by the Ariane 5 piggyback payload based Micromissions, it is essential to implement an even broader chemical analysis and to enable a significant extension of previous isotope measurements. Such a development would enhance the presently very active study of questions of atmospheric evolution and loss and past climatic conditions. The method selected to implement this program can be based on well-established mass spectrometry techniques. Sampled gas is chemically and physically processed to separate the gas mixture into components using gas chromatograph and related enrichment techniques. This allows trace species to be identified and reveals isotopic distributions in many cases with improved precision. Samples of interest, such as organic molecules, may lie deep below the highly oxidized surface layer and the suggested program includes enhanced sampling techniques to measure volatiles preserved in solid phase material deep below the surface as well as gas from the well mixed atmosphere.

Mahaffy, P.↗

DOE OSTI2022

Establishing temperature from radiance of dynamically compressed metals

Precise temperature determination is a significant challenge in extreme environments of dynamic compression studies. How can radiance measurements taken in high-pressure shock experiments constrain temperature in a meaningful and physically consistent way? Experiments maintaining sample compression against a transparent window can be tailored to present a uniform measurement area with uncertain spectral emissivity. We compare several methods to analyze radiance collected at multiple wavelengths, applying statistical methods and physical principles to improve temperature inference. With proper radiance collection and analysis, dynamic temperature uncertainties become comparable to thermomechanical ambiguities of the emitting surface.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Chemical Characterization Results for Tank 40 Sludge Batch 10 Waste Acceptance Product Specifications (WAPS) Sample

A 3-L sample (HTF-40-23-24) obtained from Tank 40 following transfer of Tank 51 to achieve the final Sludge Batch 10 processing composition was received by Savannah River National Laboratory (SRNL). SRNL was tasked with characterization of the sample in accordance with requirements for reporting the Waste Acceptance Product Specifications. A representative subsample, approximately 500 mL, was prepared by continuously agitating the 3-L sample via a mixing blade inserted into the bottle. This subsample was then used for the chemical and physical characterization reported here. This characterization includes the following: (1) Supernate and slurry density; (2) Weight percent solids; (3) Mercury Analysis (supernate and slurry); (4) Anions; (5) Total Organic/Inorganic Carbon; (6) Free Hydroxide; (7) Other Base; (8) Elementals; (9) Volatile Organic Analysis and Semi-volatile Organic Analysis; and (10) Fissile Radionuclides and Uranium Enrichment. The results of this physical and chemical characterization of the sample are documented in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Probing Condensed-Phase Structure and Dynamics in Hierarchical Zeolites and Nanosheets for Catalytic Upgradation of Biomass (Final Report)

Understanding complex reaction pathways in systems governed by multi-scale collective interactions across time and length scales remains a central scientific challenge. This project was guided by the hypothesis that the interplay among oligomers, solvents, and active sites can be tuned by a suitable choice of solvation environment and pore architecture in solid-acid catalysts to direct chemical transformations relevant to biomass conversion. Zeolites and zeolite nanosheets were used as model platforms, allowing for the interaction of macromolecules with the surface of the zeolite nanosheets and with smaller pores that host catalytically active sites. To investigate these coupled phenomena, we employ a multi-scale computational framework that integrates molecular-level descriptions with advanced sampling approaches to capture key physical and chemical interactions. Our work through this project improved fundamental understanding of how reactants and solid-acid catalysts interact in solvent-rich environments, thereby enabling the rational design of catalytic systems that upgrade biomass with enhanced selectivity and energy efficiency. In addition, the project developed advanced sampling methodologies critical for disentangling complex, reactive processes in multi-component catalytic environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Generating Cryogenic Lunar Simulants Within the Planetary Exploration & Astromaterials Research Laboratory

The Planetary Exploration & Astromaterials Research Laboratory (PEARL) aims to provides capabilities for the creation of—and research on—cryogenic lunar regolith simulants (CRS) containing surface volatile analytes. CRS represent regolith samples that might be collected from lunar Permanently Shadowed Regions (PSRs) during future missions. Handling CRS requires procedural and engineering development due to extremely cold (i.e. ≤ - 196°C) working temperatures. However, there is an imperative to understand the physical and chemical alteration of samples during collection, transport, and curation processes throughout the Artemis missions. The chemistries that will be encountered within the PSRs need to be understood based upon prior mission data analysis. The ability to utilize these techniques provides future tests that could be relevant to planetary protection applications regarding future robotic sample return.

Lunar↗

NASA NTRS1973

Study of thermal properties of the lunar regolith based on in situ temperature measurements and experiments on soil simulants

The experimental design and the development of a theory to interpret the experimental data from measurements of the thermal conductivity of lunar core samples. Measurements conducted while the lunar material is still in the core tube reduce the possibility of physical and chemical disturbances to the sample. The sample was heated externally by radiation at a known rate, the variation of temperature was measured at the surface of the core sample, and thermal conductivity was determined by comparing the observed temperature with the theoretically expected one.

Langseth, M. G.↗

DOE OSTI2024

Toward Accelerated Nuclear-physics Parameter Estimation from Binary Neutron Star Mergers: Emulators for the Tolman–Oppenheimer–Volkoff Equations

Abstract Gravitational-wave observations of binary neutron-star (BNS) mergers have the potential to revolutionize our understanding of the nuclear equation of state (EOS) and the fundamental interactions that determine its properties. However, Bayesian parameter estimation frameworks do not typically sample over microscopic nuclear-physics parameters that determine the EOS. One of the major hurdles in doing so is the computational cost involved in solving the neutron-star structure equations, known as the Tolman–Oppenheimer–Volkoff (TOV) equations. In this paper, we explore approaches to emulating solutions for the TOV equations: multilayer perceptrons (MLPs), Gaussian processes, and a data-driven variant of the reduced basis method (RBM). We implement these emulators for three different parameterizations of the nuclear EOS, each with a different degree of complexity represented by the number of model parameters. We find that our MLP-based emulators are generally more accurate than the other two algorithms, whereas the RBM results in the largest speedup with respect to the full high-fidelity TOV solver. We employ these emulators for a simple parameter inference using a potentially loud BNS observation and show that the posteriors predicted by our emulators are in excellent agreement with those obtained from the full TOV solver.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Eco-Friendly High-Performance Carbon Building Material Development from Coal

The development of eco-friendly high-performance building materials based on coal-derived materials is greatly beneficial for promoting environmental sustainability and the coal industry. This project focused on advancing technology to create innovative and scalable construction materials from two domestic sources: (1) coal-derived pyrolyzed char (PC), and (2) solvent-extracted coal deposit, extracts, and residue (CDER). It aimed to simultaneously develop and produce two types of coal-derived building products: (1) char-based concrete bricks (CCB) for wall construction in buildings, and (2) carbon-based structural units (CSU) intended as alternatives to traditional wood, concrete, or steel framing structures. The project team has successfully developed methods for manufacturing CCB samples. Extensive experiments were conducted to assess various manufacturing techniques for these samples. This included measuring their physical properties such as thermal conductivity (ranging from 0.26 to 0.38 W/mK) and bulk density (ranging from 0.85 to 1.15 g/cm 3 ), along with their mechanical properties (e.g., compressive strength ranging from 14 to 16 MPa at 28 days) for samples with a PC composition of 70%. Quality assurance and quality control tests, focusing on density and compressive strength, were also performed on samples selected randomly from pilot-scale production, and cured for a long term (over three months). The average long-term compressive strength of two randomly selected CCB samples was measured as 15.1 MPa, which was higher than the required target strength of 14 MPa. This indicates that the manufactured CCB samples from the preliminary pilot scale production run have good quality control and long-term strength performance.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Artifact identification in X-ray diffraction data using machine learning methods

In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Correlation function distributions for O ( N ) lattice field theories in the disordered phase

Numerical computations in strongly interacting quantum field theories are often performed using Monte Carlo sampling methods. A key task in these calculations is to estimate the value of a given physical quantity from the distribution of stochastic samples that are generated using the Monte Carlo method. Typically, the sample mean and sample variance are used to define the expectation values and uncertainties of computed quantities. However, the Monte Carlo sample distribution contains more information than these basic properties, and it is useful to investigate it more generally. In this work, the exact form of the probability distributions of two-point correlation functions at zero momentum in O ( N ) lattice field theories in the disordered phase and in infinite volume are determined. These distributions allow for a robust investigation of the efficacy of the Monte Carlo sampling procedure and are shown also to allow for improved estimators of the target physical quantity to be constructed. The theoretical expectations are shown to agree with numerical calculations in the O ( 2 ) model. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

NASA NTRS2013

Dynamic Acquisition and Retrieval Tool (DART) for Comet Sample Return : Session: 2.06.Robotic Mobility and Sample Acquisition Systems

The 2011 Decadal Survey for planetary science released by the National Research Council of the National Academies identified Comet Surface Sample Return (CSSR) as one of five high priority potential New Frontiers-class missions in the next decade. The main objectives of the research described in this publication are: develop a concept for an end-to-end system for collecting and storing a comet sample to be returned to Earth; design, fabricate and test a prototype Dynamic Acquisition and Retrieval Tool (DART) capable of collecting 500 cc sample in a canister and eject the canister with a predetermined speed; identify a set of simulants with physical properties at room temperature that suitably match the physical properties of the comet surface as it would be sampled. We propose the use of a dart that would be launched from the spacecraft to impact and penetrate the comet surface. After collecting the sample, the sample canister would be ejected at a speed greater than the comet's escape velocity and captured by the spacecraft, packaged into a return capsule and returned to Earth. The dart would be composed of an inner tube or sample canister, an outer tube, a decelerator, a means of capturing and retaining the sample, and a mechanism to eject the canister with the sample for later rendezvous with the spacecraft. One of the significant unknowns is the physical properties of the comet surface. Based on new findings from the recent Deep Impact comet encounter mission, we have limited our search of solutions for sampling materials to materials with 10 to 100 kPa shear strength in loose or consolidated form. As the possible range of values for the comet surface temperature is also significantly different than room temperature and testing at conditions other than the room temperature can become resource intensive, we sought sample simulants with physical properties at room temperature similar to the expected physical properties of the comet surface material. The chosen DART configuration, the efforts to identify a test simulant and the properties of these simulants, and the results of the preliminary testing will be described in this paper.

Dynamic Acquisition and Retrieval Tool (DART)↗

NASA NTRS2019

Nasa Glenn Icing Research Tunnel: 2018 Change in Drop-Sizing Equations Due to Change in Cloud Droplet Probe Sample Area

Although there has been no physical change to the cloud drop diameters in the NASA Glenn Icing Research Tunnel (IRT), the IRT cloud calibration team now has an improved understanding of the facility’s drop-sizing instrumentation, which has resulted in a recent change to the drop-sizing equations. Only the calculated values given in the previous calibration report have changed. In 2017, IRT staff found reason to believe that since at least 2014, the sample area for its Cloud Droplet Probe (CDP) (Droplet Measurement Technologies, Inc.) has been closer to 0.289 mm2, rather than the user manual’s suggested value of 0.24 mm2. In September 2017, the probe’s sample area was measured both before and after the probe was realigned, and the end sample area was measured to be 0.248 mm2. Following the probe’s realignment, drop size measurements were made in the IRT using the CDP as well as optical array probes OAP–230X and OAP–230Y (Particle Measurement Systems, Inc.). These measurements suggested that 0.289 mm2 was the more accurate value for historical measurements. When the CDP sample area used for calculations was changed from 0.24 to 0.289 mm2, distributions previously reported to have a median volumetric diameter (MVD) between 30 and 100 μm were instead calculated to have MVD values 10 to 18 percent higher. The analyses that led to these conclusions are reported in this paper, as well as the new drop-sizing equations that have been developed for the corrected measurement values. This report contains updates to drop-sizing data for the IRT’s “normal” operating conditions (MVD < 50 μm) and discusses the effects on the IRT’s “large-drop” conditions (Mod1 nozzles, Pair < 10 psig), but it does not include updates to the drop-sizing equations for those large-drop conditions.

Particle sizing↗

DOE OSTI2023

Spoofing Cross-Entropy Measure in Boson Sampling

Cross-entropy (XE) measure is a widely used benchmark to demonstrate quantum computational advantage from sampling problems, such as random circuit sampling using superconducting qubits and boson sampling (BS). We present a heuristic classical algorithm that attains a better XE than the current BS experiments in a verifiable regime and is likely to attain a better XE score than the near-future BS experiments in a reasonable running time. The key idea behind the algorithm is that there exist distributions that correlate with the ideal BS probability distribution and that can be efficiently computed. The correlation and the computability of the distribution enable us to postselect heavy outcomes of the ideal probability distribution without computing the ideal probability, which essentially leads to a large XE. Our method scores a better XE than the recent Gaussian BS experiments when implemented at intermediate, verifiable system sizes. Much like current state-of-the-art experiments, we cannot verify that our spoofer works for quantum-advantage-size systems. However, we demonstrate that our approach works for much larger system sizes in fermion sampling, where we can efficiently compute output probabilities. Finally, we provide analytic evidence that the classical algorithm is likely to spoof noisy BS efficiently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRSDate not supplied

Aqueous alteration of Cb-type asteroid Ryugu

The samples from the asteroid Ryugu, which returned to Earth in the winter of 2020 [1], were stored under pure Nitrogen conditions at the Extraterrestrial Materials Curation Center of ISAS. After basic description [2-3], they were distributed to six initial analysis teams in Japan in June 2021. The initial analysis "Stone" team, which was responsible for the analysis of coarse particles (>1 mm in size), consisted of about 150 scientists from Japan and abroad, and conducted a series of analyses We analyzed sixteen coarse Ryugu particles 1 ~ 8 mm in size: six from the 1st touch-down site and ten from the 2nd touch-down site. Individual coarse samples were cut by Xe-FIB or wire-saw to expose particular objects or textures to be exposed on the surface based on 3D structure and element distribution obtained by synchrotron X-ray CT analysis and XRF analysis, respectively. FE-SEM/EDS and FE-EPMA/WDS analysis were made on all polished sections. TEM observation of many FIB sections was made to see microstructures and to compare with carbonaceous chondrites. Many other analyses were carried out to characterize mineralogical and compositional properties and summary of the analysis procedures is described in [4]. X-ray CT analysis showed that all sixteen Ryugu particles are composed of fine-grained material, with no chondrules and CAIs larger than 100 μm in size. FE-EPMA observation showed that Ryugu samples are breccias, consisting of many small rock fragments of different compositions, lithologies, and histories. The most common lithology includes Mg-rich saponite and serpentine, dolomite, magnesite, hydroxyapatite, pyrrhotite, and magnetite as main constituents. The mineralogy of this major lithology supports the classification of Ryugu samples as CI chondrites, which experienced extensive aqueous alteration in Ryugu’s parent asteroid. Based on the obtained mineralogical properties, we performed chemical modeling of aqueous alteration of Ryugu’s parent asteroid [5]. Numerical simulations [6-8] to reproduce thermal history and impact-induced destruction of the Ryugu’s parent asteroid were also carried out using mineralogical and physical properties of the Ryugu samples. In the talk, I would like to explain the conditions of aqueous alteration occurred in the parent asteroid of Ryugu in order to show how the water in the asteroid changed the mineralogy and chemistry of the nebular dust.

T. Nakamura↗

DOE OSTI2023

Sub-two-cycle gigawatt-peak-power LWIR OPA for ultrafast nonlinear spectroscopy of condensed state materials

The application of high-power, few-cycle, long-wave infrared (LWIR, 8–20 µm) pulses in strong-field physics is largely unexplored due to the lack of suitable sources. However, the generation of intense pulses with >6 µm wavelength range is becoming increasingly feasible with the recent advances in high-power ultrashort lasers in the middle-infrared range that can serve as a pump for optical parametric amplifiers (OPA). Here we experimentally demonstrate the feasibility of this approach by building an OPA pumped at 2.4 µm that generates 93 µJ pulses at 9.5 µm, 1 kHz repetition rate with sub-two-cycle pulse duration, 1.6 GW peak power, and excellent beam quality. The results open a wide range of applications in attosecond physics (especially for studies of condensed phase samples), remote sensing, and biophotonics.

Leshchenko, Vyacheslav (ORCID:0000000199708559)↗