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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A comparative study of mechanical and chemical durability of non-wetting superhydrophobic and lubricant-infused surfaces

Fabrication of bioinspired non-wetting superhydrophobic surfaces (SHS) and lubricant-infused surfaces (LIS) has been studied extensively on a variety of materials. In contrast, durability of the surfaces exposed to harsh mechanical and chemical environments has been the subject of little attention. This study considers the mechanical and chemical durability of SHS and LIS copper surfaces fabricated via facile electrodeposition and chemical etching methods. The as-fabricated surfaces demonstrate excellent non-wetting characteristics with water contact angle of 160° and sliding angle below 5°. The surfaces are subject to mechanical wear through scratch test and water jet impingement at 15 psi and 20 psi as well as accelerated corrosion following the ASTM-E407 standard. The performance of the electrodeposited and etched non-wetting surfaces is systematically assessed in terms of contact and sliding angles and corrosion rate in a simulated marine environment. All surfaces are shown to be robust to mechanical wear after scratch test, with excellent stability of contact and sliding angles, and up to two orders of magnitude reduced corrosion rate compared to bare copper surface. SHS retained steadfast non-wetting characteristics under high-pressure water jet tests compared to the other surfaces while LIS, regardless of texturing method, showed one to two orders of magnitude reduced corrosion rate compared to bare copper surface throughout water jet impingement and chemical durability tests. The study presents for the first time a systematic comparison of durability of SHS and LIS through a common set of fabrication and testing protocol and helps identify appropriate non-wetting surfaces and fabrication methods based on the use environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Kinetic model-based group contribution method for derived cetane number prediction of oxygenated fuel components and blends

A four-step autoignition model was used to derive an expression for the ignition delay (ID) measured in ignition quality testers (IQT) with the derived cetane number (DCN) determined from this ID using the ASTM D6890 standard correlation. The model predicts DCN for individual compounds and blends as a function of each compound's global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in each compound. Measurement data for 125 compounds and 94 binary and ternary blends (including oxygenates: alcohols, aldehydes, esters, ethers, and ketones), from literature and from measurements performed in our lab, were used to obtain the dependence of the measured ignition delay on each functional group. The new kinetic model-based group contribution method was able to predict the ignition delay of both pure compounds and blends, with an average DCN error of 4.4 (19%) and 2.8 (11%), respectively. Here, the blend model was also used to develop an ID mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule gave an average DCN error of 3.6 (16%) for blends. Both the blend model and mixing rule were found to be superior compared to standard linear by volume fraction or mole fraction mixing rules commonly used to estimate the DCN of mixtures.

42 ENGINEERING↗
DOE OSTI2016

A patch-based pseudo-CT approach for MRI-only radiotherapy in the pelvis

Purpose: In radiotherapy based only on magnetic resonance imaging (MRI), knowledge about tissue electron densities must be derived from the MRI. This can be achieved by converting the MRI scan to the so-called pseudo-computed tomography (pCT). An obstacle is that the voxel intensities in conventional MRI scans are not uniquely related to electron density. The authors previously demonstrated that a patch-based method could produce accurate pCTs of the brain using conventional T{sub 1}-weighted MRI scans. The method was driven mainly by local patch similarities and relied on simple affine registrations between an atlas database of the co-registered MRI/CT scan pairs and the MRI scan to be converted. In this study, the authors investigate the applicability of the patch-based approach in the pelvis. This region is challenging for a method based on local similarities due to the greater inter-patient variation. The authors benchmark the method against a baseline pCT strategy where all voxels inside the body contour are assigned a water-equivalent bulk density. Furthermore, the authors implement a parallelized approximate patch search strategy to speed up the pCT generation time to a more clinically relevant level. Methods: The data consisted of CT and T{sub 1}-weighted MRI scans of 10 prostate patients. pCTs were generated using an approximate patch search algorithm in a leave-one-out fashion and compared with the CT using frequently described metrics such as the voxel-wise mean absolute error (MAE{sub vox}) and the deviation in water-equivalent path lengths. Furthermore, the dosimetric accuracy was tested for a volumetric modulated arc therapy plan using dose–volume histogram (DVH) point deviations and γ-index analysis. Results: The patch-based approach had an average MAE{sub vox} of 54 HU; median deviations of less than 0.4% in relevant DVH points and a γ-index pass rate of 0.97 using a 1%/1 mm criterion. The patch-based approach showed a significantly better performance than the baseline water pCT in almost all metrics. The approximate patch search strategy was 70x faster than a brute-force search, with an average prediction time of 20.8 min. Conclusions: The authors showed that a patch-based method based on affine registrations and T{sub 1}-weighted MRI could generate accurate pCTs of the pelvis. The main source of differences between pCT and CT was positional changes of air pockets and body outline.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Measuring neutron spectra in radiotherapy using the nested neutron spectrometer

Purpose: Out-of-field neutron doses resulting from photonuclear interactions in the head of a linear accelerator pose an iatrogenic risk to patients and an occupational risk to personnel during radiotherapy. To quantify neutron production, in-room measurements have traditionally been carried out using Bonner sphere systems (BSS) with activation foils and TLDs. In this work, a recently developed active detector, the nested neutron spectrometer (NNS), was tested in radiotherapy bunkers. Methods: The NNS is designed for easy handling and is more practical than the traditional BSS. Operated in current-mode, the problem of pulse pileup due to high dose-rates is overcome by measuring current, similar to an ionization chamber. In a bunker housing a Varian Clinac 21EX, the performance of the NNS was evaluated in terms of reproducibility, linearity, and dose-rate effects. Using a custom maximum-likelihood expectation–maximization algorithm, measured neutron spectra at various locations inside the bunker were then compared to Monte Carlo simulations of an identical setup. In terms of dose, neutron ambient dose equivalents were calculated from the measured spectra and compared to bubble detector neutron dose equivalent measurements. Results: The NNS-measured spectra for neutrons at various locations in a treatment room were found to be consistent with expectations for both relative shape and absolute magnitude. Neutron fluence-rate decreased with distance from the source and the shape of the spectrum changed from a dominant fast neutron peak near the Linac head to a dominant thermal neutron peak in the moderating conditions of the maze. Monte Carlo data and NNS-measured spectra agreed within 30% at all locations except in the maze where the deviation was a maximum of 40%. Neutron ambient dose equivalents calculated from the authors’ measured spectra were consistent (one standard deviation) with bubble detector measurements in the treatment room. Conclusions: The NNS may be used to reliably measure the neutron spectrum of a radiotherapy beam in less than 1 h, including setup and data unfolding. This work thus represents a new, fast, and practical method for neutron spectral measurements in radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Additionally, based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10 -3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Design and analysis of Vivaldi antenna with enhanced radiation characteristics for mm-wave and THz applications

This article presents a novel approach to design Vivaldi antennas for millimeter and Terahertz band applications. The radiation performance of the proposed Vivaldi antenna is enhanced by employing cross shape resonator and abridged rectangular slots at the edge of radiating arms. In the THz regime, the simulated − 10 dB impedance bandwidth is approximately 76 GHz, minimum return loss of − 58.83 dB, VSWR of 1.002, peak gain of 11.77 dB, radiation efficiency of 97.40% and directivity of 11.89 dBi are achieved at the corresponding resonance frequency of 0.603 THz. Further, in order to validate the suggested design method, targeted antennas are fabricated, tested at 0.06125-THz and 0.06215-THz frequency. The significant performance improvement in radiation characteristics are observed over the frequency band from 0.06- to 0.065-THz. The proposed THz antenna useful for the application of video-rate imaging, object imaging, detection of illicit drugs using spectroscopy, Doppler radar and/or on-body techniques and wireless communications. Similarly, the planned mm-wave antenna is useful for the imaging system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Development of Alkoxide Precursors-Based Hybrid Coatings on Ti-6Al-4V Alloy for Biomedical Applications: Influence of pH of Sol

The Ti-6Al-4V alloy, widely used in biomedical applications, is associated with cytotoxic effects due to the release of aluminum and vanadium ions in the human body. One of the most effective ways to control the release of cytotoxic ions is through anti-corrosive coatings. Among them, the alkoxysilanes stand out for their good barrier properties and the absence of toxicity. Aiming to improve the clinical success rate of metallic implants, this study sets out to evaluate the influence of the pH of the sol on the physico-chemical, morphological, mechanical and electrochemical characteristics of hybrid films based on 3-(trimethoxysilylpropyl)methacrylate (MAP) and tetraethoxysilane (TEOS) applied to Ti-6Al-4V. The film was prepared by using the sol–gel method for pH values of 3, 4, and 5. The results indicated that maintaining the pH of the sol at 4 favors the hydrolysis rate of alkoxide precursors, which results in a uniform, dense and adherent film with excellent anti-corrosion performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

2,3-Butanediol recovery from fermentation broth using membrane pertraction

2,3-Butanediol (BDO) has gained immense interest for use as a platform chemical in the production of many important chemicals such as synthetic rubber, plasticizer, and octane boosters. Using BDO as a precursor for sustainable aviation fuel production may significantly reduce the carbon footprint of the airline industry. However, recovery of BDO is challenging due to its relatively low concentration (∼10 wt %) in fermentation broth and its high affinity for water. In this work, we developed a membrane pertraction process for BDO recovery from biomass derived fermentation broth. Different organic solvents such as hexanol and oleyl alcohol were investigated. With traditional solvent extraction, hexanol required a solvent to feed ratio of 10 to recover >90 % BDO, and oleyl alcohol could recover 35 % of BDO at the same ratio. BDO recovery of >90 % was demonstrated with pertraction; a BDO extraction rate of 15 g 1 m −2 h −1 was achieved using hexanol, and an extraction rate of 10 g 1 m −2 h −1 was achieved using oleyl alcohol. Impurities commonly found in fermentation broth did not affect the separation performance of the pertraction process. In conclusion, this work demonstrates pertraction as a low-footprint, scalable method for recovery of high-purity BDO from fermentation broth.

2,3 butanediol↗
DOE OSTI2025

Numerical assessment of triply periodic minimal surfaces for direct air capture of carbon dioxide

Direct air capture (DAC) systems often consist of packing material wetted by a capture fluid that reacts with CO 2 in the airstream. The efficiency of the contactor is determined by a complex relationship of fluid dynamics, heat and mass transfer, contactor geometry, and chemical properties. The efficiency of the contactor must be balanced with other factors, primarily pressure drop through the system. Triply periodic minimal surfaces (TPMS) are a class of differential surfaces that have been explored in multiple engineering applications and have been shown to exhibit excellent performance when used in heat exchangers. Their tortuous path provides a high surface-to-volume ratio and favorable trade-off between contact area and pressure drop. In this work, a gyroid-type TPMS contactor was evaluated using computational fluid dynamics for a variety of geometric parameters to explore the potential benefit of TPMS shapes for DAC applications. A thin-film model was employed to model the flow and distribution of the capture solvent, allowing efficient simulations of TPMS structures at scale by eliminating the need for a computationally intensive interface capturing method. A liquid-gas mass transfer model was implemented in the commercial software STAR-CCM+ and used to predict the CO 2 capture efficiency and study the trade-off between capture performance and pressure drop through analysis of capture rates, mass transfer coefficients, and other relevant variables. TPMS contactors with a variety of geometric parameters and two capture solvent options were investigated to determine the effect of design choices on the operational performance of DAC systems. In conclusion, results showed that while contactor geometry is the dominant factor in efficiency and pressure drop, the physiochemical properties of the solvent are an important secondary influence on the contactor performance.

CFD↗
DOE OSTI2023

Exploiting Kronecker structure in exponential integrators: Fast approximation of the action of φ $-$functions of matrices via quadrature

Here, in this article, we propose an algorithm for approximating the action of φ $-$ functions of matrices against vectors, which is a key operation in exponential time integrators. In particular, we consider matrices with Kronecker sum structure, which arise from problems admitting a tensor product representation. The method is based on quadrature approximations of the integral form of the φ $-$ functions combined with a scaling and modified squaring method. Owing to the Kronecker sum representation, only actions of 1D matrix exponentials are needed at each quadrature node and assembly of the full matrix can be avoided. Additionally, we derive a priori bounds for the quadrature error, which show that, as expected by classical theory, the rate of convergence of our method is supergeometric. Guided by our analysis, we construct a fast and robust method for estimating the optimal scaling factor and number of quadrature nodes that minimizes the total cost for a prescribed error tolerance. We investigate the performance of our algorithm by solving several linear and semilinear time-dependent problems in 2D and 3D. The results show that our method is accurate and orders of magnitude faster than the current state-of-the-art.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Modeling of proton-induced radioactivation background in hard X-ray telescopes: Geant4-based simulation and its demonstration by Hitomi ’s measurement in a low Earth orbit

Hard X-ray astronomical observatories in orbit suffer from a significant amount of background due to radioactivation induced by cosmic-ray protons and/or geomagnetically trapped protons. Within the framework of a full Monte Carlo simulation, we present modeling of in-orbit instrumental background which is dominated by radioactivation. To reduce the computation time required by straightforward simulations of delayed emissions from activated isotopes, we insert a semi-analytical calculation that converts production probabilities of radioactive isotopes by interaction of the primary protons into decay rates at measurement time of all secondary isotopes. Therefore, our simulation method is separated into three steps: (1) simulation of isotope production, (2) semi-analytical conversion to decay rates, and (3) simulation of decays of the isotopes at measurement time. This method is verified by a simple setup that has a CdTe semiconductor detector, and shows a 100-fold improvement in efficiency over the straightforward simulation. To demonstrate its experimental performance, the simulation framework was tested against data measured with a CdTe sensor in the Hard X-ray Imager onboard the Hitomi X-ray Astronomy Satellite, which was put into a low Earth orbit with an altitude of 570 km and an inclination of 31°, and thus experienced a large amount of irradiation from geomagnetically trapped protons during its passages through the South Atlantic Anomaly. The simulation is able to treat full histories of the proton irradiation and multiple measurement windows. As a result, the simulation results agree very well with the measured data, showing that the measured background is well described by the combination of proton-induced radioactivation of the CdTe detector itself and thick Bi 4 Ge 3 O 12 scintillator shields, leakage of cosmic X-ray background and albedo gamma-ray radiation, and emissions from naturally contaminated isotopes in the detector system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

On the efficacy of stochastic collocation, stochastic Galerkin, and stochastic reduced order models for solving stochastic problems

The stochastic collocation (SC) and stochastic Galerkin (SG) methods are two well-established and successful approaches for solving general stochastic problems. A recently developed method based on stochastic reduced order models (SROMs) can also be used. Herein we provide a comparison of the three methods for some numerical examples; our evaluation only holds for the examples considered in the paper. The purpose of the comparisons is not to criticize the SC or SG methods, which have proven very useful for a broad range of applications, nor is it to provide overall ratings of these methods as compared to the SROM method. Furthermore, our objectives are to present the SROM method as an alternative approach to solving stochastic problems and provide information on the computational effort required by the implementation of each method, while simultaneously assessing their performance for a collection of specific problems.

42 ENGINEERING↗
DOE OSTI2025

Anomaly Detection Based on Machine Learning for the CMS Electromagnetic Calorimeter Online Data Quality Monitoring

Using a semi-supervised machine learning approach we present a real-time anomaly detection system based on an autoencoder used for online data quality monitoring of the CMS electromagnetic calorimeter operating at the CERN LHC. We introduce a novel method that maximizes the anomaly detection performance making use of the time-dependence of anomalies and the spatial variations in the detector response. The autoencoder-based system efficiently detects anomalies in real time and maintains a very low false discovery rate. We validate the performance of this novel system with anomalies from LHC collision data taken in 2018 and 2022. In addition, results are presented after deploying the autoencoder-based system in the CMS online Data Quality Monitoring workflow at the beginning of LHC Run 3 resulting in the system to detect issues that were missed by the existing system.

Harilal, Abhirami [Carnegie Mellon University, Pit↗
DOE OSTI2021

A New Class of AMG Interpolation Methods Based on Matrix-Matrix Multiplications

A new class of distance-two interpolation methods for algebraic multigrid (AMG) that can be formulated in terms of sparse matrix-matrix multiplications is presented and analyzed. Compared with similar distance-two prolongation operators, the proposed algorithms exhibit improved efficiency and portability to various computing platforms, since they allow one to easily exploit existing high-performance sparse matrix kernels. The new interpolation methods have been implemented in hypre, a widely used parallel multigrid solver library. With the proposed interpolations, the overall time of hypre's BoomerAMG setup can be considerably reduced, while sustaining equivalent, sometimes improved, convergence rates. Numerical results for a variety of test problems on parallel machines are presented that support the superiority of the proposed interpolation operators over the existing ones in hypre.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Method development for thermal analyses testing on Reillex HPQ resin using the advanced reactive system screening tool (ARSST)

Reillex™ HPQ resin was developed by Los Alamos Laboratory and Reilly Industries Inc. in an effort to increase safety and process efficiency during the recovery and purification of plutonium. Ionac™ A-641, another strong base macroporous anion exchange resin used in the nuclear industry, was known to undergo a runaway reaction in hot nitric acid solutions. Because of this, an extensive amount of thermal analyses testing on the Reillex™ HPQ resin in SRNL was performed in 1999-2001 prior to use. A report on the thermal stability qualification of the Reillex™ HPQ resin in 8M (35%) and 12M (53%) HNO 3 was reported in 2000. In 2001, the reactivity of Reillex™ HPQ resin in 14.4M (64%) HNO 3 was evaluated. In January of 2001, thermal stability scoping tests were performed on irradiated Reillex™ HPQ resin in 14.4M (64%) HNO 3 (as a worst case scenario) and the results sent to Fauske and Associates to calculate a rupture disk size for the HB-Line resin column. A technical report by Fauske and Associates was issued in February 2001 recommending a 2.0” vent line with a rupture disk set pressure of 60 psig. This calculation was based on ARSST thermal analyses scoping tests at SRNL in which 4 grams of dried resin and 6.0 grams of 64% nitric acid in a 10 gram test cell, produced a maximum pressure rate (dP/dt) of 720 psi/min (12 psi/sec) and a maximum temperature of 250 °C. In 2015, a new batch of Reillex™ HPQ resin was manufactured by Vertellus Industries. A test sample of the resin was sent to SRNL to perform acceptance and qualification thermal stability testing using the ARSST. During these tests, method development was performed to ensure that a representative resin to acid ratios were used while running the tests in the ARSST. Fauske and Associates recommended to either use a full test cell representative of the HB-Line column or a 10 gram sample in the test cell that was representative of the ratios of resin to nitric acid in the actual HB-Line column. An observation was made during method development testing that the 4 grams of resin to 6 grams of 64% acid ratio used in 2001 to determine the rupture disk size did not entirely wet the resin and was not representative of the actual HB-Line column. The results of this study raised questions as to whether the ratio of 4 grams of resin to 6 grams of 64% nitric acid recommended by Fauske and Associates in 2001 was the correct ratio.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Non-Equilibrium Effects in Quantum Magnets

While most often the state of a material will tend toward an equilibrium determined by its environment, there are many cases of scientific and technological interest where materials are manipulated to be or are found in non-equilibrium configurations. For example, data can be stored in hard drives by deliberately altering the magnetic orientation in a material to store information in non-equilibrium pattern. In this project, the main goals were studies of non-equilibrium properties of quantum magnets using neutron scattering as the primary experimental method. Neutron scattering allows characterization of magnetic correlation lengths sensitive to the presence of defects. It can also be used to distinguish equilibrium from non-equilibrium states via energy transfer rates. Typical bulk state magnetization relaxation times are too short to perform many neutron scattering measurements of interest. To enable the study of non-equilibrium conditions, materials with longer magnetic relaxation times were targeted. CoNb 2 O 6 was used in two experiments related to non-equilibrium physics. In the first, evidence for defects created via the Kibble-Zurek mechanism (KZM) was sought by quenching across a magnetic field-dependent phase transition. Somewhat unexpectedly, clear evidence for KZM-induced defects was absent. Additional measurements of CoNb 2 O 6 were made to better characterize its crystal field and other properties to provide a better theoretical understanding to enable more effective non-equilibrium physics measurements. In another project, LiHo 0.45 Y 0.55 F 4 was used to compare a quantum annealing protocol to a thermal annealing one since magnetic fields can be used to control the thermal fluctuations in LiHo 0.45 Y 0.55 F 4 . In addition, a new pulsed magnet power supply and new techniques were developed suitable for neutron scattering experimental environments to enable faster magnetic field changes for producing non-equilibrium conditions. The power supply developed for this project has wider technological applications in addition to faster magnetic field ramps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Impact of Misclassification Rates on Compression Efficiency of Red Blood Cell Images of Malaria Infection Using Deep Learning

Malaria is a severe public health problem worldwide, with some developing countries being most affected. Reliable remote diagnosis of malaria infection will benefit from efficient compression of high-resolution microscopic images. This paper addresses a lossless compression of malaria-infected red blood cell images using deep learning. Specifically, we investigate a practical approach where images are first classified before being compressed using stacked autoencoders. We provide probabilistic analysis on the impact of misclassification rates on compression performance in terms of the information-theoretic measure of entropy. We then use malaria infection image datasets to evaluate the relations between misclassification rates and actually obtainable compressed bit rates using Golomb–Rice codes. Simulation results show that the joint pattern classification/compression method provides more efficient compression than several mainstream lossless compression techniques, such as JPEG2000, JPEG-LS, CALIC, and WebP, by exploiting common features extracted by deep learning on large datasets. This study provides new insight into the interplay between classification accuracy and compression bitrates. The proposed compression method can find useful telemedicine applications where efficient storage and rapid transfer of large image datasets is desirable.

59 BASIC BIOLOGICAL SCIENCES↗