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At least 559 records · Page 31

Effect of heat treatment on microstructural evolution and hardness homogeneity in laser powder bed fusion of alloy 718

The thermal history developed in laser powder bed fusion (LPBF) processes has been shown to be complex resulting in equally complex microstructures and mechanical properties. Microscopic observations and Vickers micro-hardness mapping measurements were carried out on diff ;erent section planes of LPBF alloy 718 cuboids. Three-dimensional finite element analysis was used to simulate thermal history and to predict the residual stress distribution in the as-built material. Computational thermodynamics was used to predict the micro-segregation and nucleation driving force of various phases in the bulk and in segregated regions. Varied heat-treatments such as simulated hot isostatic pressing, and double aging were applied. Their influence on the microstructure, microsegregation, precipitate formation, and micro-hardness variations of LPBF alloy 718 were investigated. Hardness map results showed heterogeneous micro-hardness on the xy- and xz-planes of the as-built parts where the bottom plane and center regions had larger hardness of ~315 HV 0.5 while the top plane and contours showed hardness of ~300 HV 0.5 . It was found that the aging treatment increased the overall hardness of the as-built condition from ~310 HV 0.5 to 470 HV 0.5 but also increased the hardness gradient throughout the coupon. After simulated hot isostatic pressing process (i.e., without applied pressure) at 1020 °C for 4 h followed by water quench (HIPWQ), the hardness gradient and hardness was minimized (~210 HV 0.5 ) as the microstructure transitioned from heterogeneous columnar grains in the as-built condition to more uniform recrystallized grains. A double aging treatment was applied to enhance hardness from ~210 HV 0.5 to ~440 HV 0.5 . Finally, HIPWQ followed by double aging produced a homogeneous microstructure and more uniform hardness map with enhanced mechanical properties in LPBF alloy 718 coupons.

36 MATERIALS SCIENCE↗

Correlated 4D-STEM and EDS for the classification of fine Beta-precipitates in aluminum alloy AA 6063-T6

Tuning the properties of aluminum alloys AA 6063-T6 involves artificial aging to induce precipitate formation, particularly β’’ and β’ phases. Previous characterization challenges due to their similar appearance are addressed here by correlating 4D scanning transmission electron microscopy (4DSTEM) and energy-dispersive spectroscopy (EDS) mapping. This approach allows us to analyze the structure and composition of precipitates individually, overcoming limitations of conventional imaging and structural analysis techniques when the precipitates appear simultaneously, as is often the case. We present detailed characterizations of needle-shaped Beta precipitates, revealing distinct diffraction patterns (DPs) and compositional differences. The method's applicability extends beyond aluminum alloys, offering a promising strategy for complex composite material characterization with multimodal scanning transmission electron microscopy (STEM) techniques.

36 MATERIALS SCIENCE↗

Two-step route to size and shape controlled gibbsite nanoplates and the crystal growth mechanism

Mastery of gibbsite (α-Al(OH) 3 ) nucleation and crystal growth is significant in fundamental aluminum chemistry and also beneficial for industrial applications and the remediation of nuclear waste. Herein, we developed an additive-free two-step route to size and morphology controlled synthesis of gibbsite nanoplates. Independent temperature manipulation of nucleation and crystal growth regimes was used to control the efficacy and yield of the process, producing gibbsite nanoplates with tunable morphologies and sizes. We achieve morphologies ranging from hexagon, pseudo hexagon, truncated triangle to rhombic, and average basal plane diameters from 120 to 850 nm, with thicknesses between 8 and 45 nm. Analysis of gibbsite structure, size and morphology with techniques including powder X-ray diffraction (p-XRD), 27 Al magic angle spinning nuclear magnetic resonance spectroscopy (MAS NMR), scanning electron microscopy (SEM), and atomic force microscopy (AFM) provided key details on the nucleation and crystal growth mechanisms. The results indicate the temperature of the nucleation aging step is the most important factor controlling the final particle size. Particularly small nanoplates were obtained with a low nucleation aging temperature followed by high crystal growth temperature, suggesting that gibbsite growth can be approximated via a LaMer-type burst nucleation and crystal growth mechanism. Scalability was demonstrated by triplicate of 2 L experiments which prepared gibbsite nanoplates of ~200 nm size and with an average yield of ~55% after 84 h. Compared to existing techniques, this improved two-step route is cheaper, more efficient and environmentally friendly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The gMOSS: the galaxy survey and galaxy populations of the large homogeneous field

ABSTRACT We present the gMOSS (Galaxies of Medium-band One-meter Schmidt telescope Survey) catalogue of ∼19 000 galaxies in 20 filters (4 broad-band SDSS and 16 medium-band filters). We observed 2.386 deg2 on the central part of the HS47.5-22 field with the 1-m Schmidt telescope of the Byurakan Astrophysical Observatory. The gMOSS is a complete flux-limited sample of galaxies with a threshold magnitude of r SDSS ≤ 22.5 AB. From photometric measurements with 16 medium-band filters and u SDSS, we get spectral energy distributions for each object in the field, which are used for further analysis. Galaxy classification and photometric redshift estimation based on spectral template matching with zebra software. The obtained redshift accuracy is σNMAD < 0.0043. Using the SED-fitting cigale code, we obtained the main properties of the stellar population of galaxies, such as rest-frame (u − r)res colour, stellar mass, extinction, and mass-weighted age with a precision of 0.16 ± 0.07 mag, 0.14 ± 0.04 dex, 0.27 ± 0.1 mag, and 0.08 ± 0.04 dex, respectively. Using a dust-corrected colour–mass diagram, we divided the full sample into populations of red and blue galaxies and considered the dependencies between stellar mass and age. Throughout cosmic time, red sequence galaxies remain older and more massive than blue cloud galaxies. The star formation history of a complete subsample of galaxies selected in the redshift range 0.05 ≤ z ≤ 0.015 with <$\mathrm{log} M \mathrm{\gt }_\mathrm{[M_\odot ]}$>8.3 shows an increase in the SFRD up to z ∼ 3, under the results obtained in earlier studies.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimal Coordination of Electric Vehicles for Grid Services using Deep Reinforcement Learning

Recent research has shown the effectiveness of reinforcement learning (RL) in coordinating electric vehicles (EVs) with vehicle-to-grid capabilities for grid services. However, many of these studies rely on lookup table and deep Q-network techniques, which can be impractical when dealing with continuous states and actions. In addition, existing RL designs inadequately account for battery aging effects, EV user satisfaction, uncertain departure and arrival time, and trip distance, which may compromise effective coordination. This paper aims to bridge these gaps by developing an innovative deep deterministic policy gradient-based RL framework for optimal coordination of EVs. Case studies were carried out using a test system with 100 EVs, and numerical analysis results showed that the proposed RL framework can effectively coordinate EVs to maximize economic benefits and user satisfaction while ensuring the expected battery lifespan.

Das, Avijit↗

Major Drivers of Long-Term Distribution Transformer Demand

Distribution transformers, used to step-down medium voltage to service-voltage level for end-use electrical consumption, are currently experiencing major shortages. Utilities are experiencing extended lead times for transformers of up to 2 years (a 4x increase on lead times pre-2022) and prices have gone up by as much as 5-6 times in the past 2 years. Current shortages have been attributed to pent-up post-pandemic demand, workforce shortages and low retention rates, component supply chain challenges, and materials shortages (grain-oriented electrical steel, aluminum, and copper). The supply of this equipment is critical for the reliability and growth of the power system, and in meeting administration climate goals in terms of electrification of demand and the growth of renewable energy. This report details some of the initial analysis conducted by the National Renewable Energy Laboratory (NREL), supported by the Department of Energy's Office of Electricity and Office of Policy, in assessing the long-term demand trends for distribution transformers. Expected increased demand is due to a confluence of not only electrification and renewable energy growth, but also in the context of aging electric infrastructure, increased frequency and severity of extreme weather events, and utility-driven investments in reliability and resiliency of the electricity distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

High energy X-ray characterization of the microstructure of PuGa alloy samples at macroscopic depths and non-ambient conditions

High energy (95 keV) X-rays were utilized to characterize the microstructure of eight PuGa alloy samples at room temperature and during cooling to ∼10 K. The samples had different Ga content (nominally 0-3.4 at.%), age, and history. A ninth sample, similarly characterized with neutron diffraction, was included to extend the Ga range to 7 at.%. The samples span the range from single phase α (monoclinic) to δ (face-centered cubic) PuGa, as well as a two-phase α′/δ sample. The crystallographic textures, phase fractions, lattice parameters and dislocation densities of each sample were evaluated through distinct analysis techniques. The textures of the samples were modest. In each case, the dislocation densities were relatively high, comparable to cold worked metals and metals exposed to similar radiation dose. At room temperature, the lattice parameters determined in the predominantly single-phase samples were larger than expected based on the nominal Ga concentration. The observed lattice thermal expansions of the single-phase δ samples to 10 K are self-consistent across the samples and consistent with previous measurements reported in the literature. Significantly larger thermal lattice strain is observed in the δ phase of the two-phase material due to mechanical constraint from the α′ phase, which has a three times larger thermal expansion and is much harder than the δ phase. In conclusion, the results demonstrate the unique value of high-energy X-rays for relatively routine microstructural characterization of Pu alloy samples.

36 MATERIALS SCIENCE↗

Quantifying the impact of operating temperature on cracking in battery electrodes, using super-resolution of microscopy images and stereology

There are numerous factors that can have an impact on the degradation behavior of batteries, such as the number of recharge cycles or the charge rate. Here, we investigate the influence of operating temperature on the structural degradation of the microstructure in lithium-ion positive electrodes. For that purpose, the microstructure is characterized for cathodes which have been cycled for 200 cycles under 6C (10-minute) charging at different operating temperatures, namely, 20°C, 30°C, 40°C, and 50°C. For each operating condition scanning electron microscopy (SEM) images of cross-sectioned Li x Ni 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) electrodes have been analyzed, to determine structural descriptors such as global particle porosity, crack size/length/width distribution, and porosity and specific surface area distribution of individual particles. Additionally, a stereological method has been deployed to investigate the local particle porosity as a function of distance to the particle center. Results show that particle porosity increases with increasing cycling temperature. Particle porosity is greatest at the particle center and decreases along the particle radius to the exterior. Particle surface area is similar across the four cycling-temperature aging conditions.

25 ENERGY STORAGE↗

Early calendar life and health prediction of silicon batteries via machine learning with uncertainty quantification

Lithium-ion batteries with silicon anodes promise high energy density but are limited by calendar lifetime. Reducing the long iteration time to obtain experimental results requires predicting calendar lifetime early in a cell's life. In this study, we demonstrate that lightweight machine learning models with feature engineering can provide calendar lifetime estimates from early electrochemical signals. After 1 month of electrochemical aging, the best models achieve 10% error in calendar-life prediction and can separate "bad" from "good" lifetime cells with a mean F1 score of 0.857. As battery systems exhibit inherent variability, four methods for uncertainty quantification are compared, and confidence intervals are demonstrated with an uncertainty of +-3.6 months in lifetime prediction. A feature importance analysis indicates that early patterns in voltage decay are the strongest indicators of calendar lifetime. Finally, this modeling approach has high error when generalizing to new electrode chemistries or testing conditions but with appropriately low confidence.

25 ENERGY STORAGE↗

Ceria Incorporation in Sinter-Resistant Platinum-Based Catalysts

Platinum group metals (PGM) are widely used for exhaust emission abatement. Sintering during the high-temperature emission control conditions decreases noble metal utilization efficiency. Efficient use of scarce noble metals requires sinter-resistant catalysts. Here we extend an approach to synthesize catalysts consisting of platinum nanoparticles encapsulated in a mixture of cerium and aluminum oxides (Pt@Al 2 O 3 -CeO 2 ). We tested the activity of this catalyst toward carbon monoxide, propene, and propane oxidation chosen as model oxidation reactions for emission control catalysts. Pt@Al 2 O 3 -CeO 2 catalysts demonstrated similar activity and stability upon aging as the comparison system without ceria, Pt@Al 2 O 3 , while maintaining small Pt nanoparticles and ceria crystallites. Additionally, we studied the influence of various thermal treatments on CO oxidation activity and determined that a steam treatment can activate low temperature CO oxidation activity of Pt@Al 2 O 3 -CeO 2 . STEM-EDS analysis revealed that thermal treatments led to the co-location of Pt and CeO 2 and temperature programmed-reduction analysis revealed that the steam treatment specifically enhanced CO oxidation activity through surface reduction of the CeO 2 . As a result, we demonstrate the versatility of this encapsulation approach to generate mixed metal-oxide supports with improved metal-support interactions without hindering nanoparticle stability.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Design of a Robust Memristive Spiking Neuromorphic System with Unsupervised Learning in Hardware

Spiking neural networks (SNN) offer a power efficient, biologically plausible learning paradigm by encoding information into spikes. The discovery of the memristor has accelerated the progress of spiking neuromorphic systems, as the intrinsic plasticity of the device makes it an ideal candidate to mimic a biological synapse. Despite providing a nanoscale form factor, non-volatility, and low-power operation, memristors suffer from device-level non-idealities, which impact system-level performance. To address these issues, this article presents a memristive crossbar-based neuromorphic system using unsupervised learning with twin-memristor synapses, fully digital pulse width modulated spike-timing-dependent plasticity, and homeostasis neurons. Additionally, the implemented single-layer SNN was applied to a pattern-recognition task of classifying handwritten-digits. The performance of the system was analyzed by varying design parameters such as number of training epochs, neurons, and capacitors. Furthermore, the impact of memristor device non-idealities, such as device-switching mismatch, aging, failure, and process variations, were investigated and the resilience of the proposed system was demonstrated.

97 MATHEMATICS AND COMPUTING↗

SULI Technical Report: WIRE (Draft)

Local climate undoubtedly affects facility maintenance requirements; however, knowledge of the link between weather and facility condition over time is grounded in the 1990s and needs to be updated. WIRE aims to quantify the relationship between climate and infrastructure by calculating climate-based service life estimates to be used in BUILDER, a program the Department of Energy (DOE) uses for facility management. Phase One of this project is a case study on window-or-wall-mounted AC units. The independent variables influencing service life are load, maintenance quality, and effective age, with load calculated from three weather variables: temperature, humidity, and solar radiation. Given sufficient data, service life can be calculated as a function of these variables via regression. WIRE is currently collecting data. Preliminary estimated service life projections as a function of load derived from Lawrence Livermore National Laboratory (LLNL) data support the need for updated analysis on the relationship between climate and facility condition. With the groundwork laid, WIRE can generate deliverables immediately upon arrival of data. The methods used for this case study constitute a framework for deriving the relationship between weather variables and service life for other components.

42 ENGINEERING↗

Spent Nuclear Fuel Exploratory Roadmaps - 20054

The U.S. Department of Energy manages nearly 2,500 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) resulting from several decades of research, testing, and production reactors [DOE 1995]. This SNF is managed at the DOE Hanford Site in Washington State (Hanford), Idaho National Laboratory (INL), and Savannah River Site in South Carolina (SRS). From 1995 to 2004, the Department of Energy (DOE) made several key programmatic decisions, supported by appropriate documentation in accordance with the National Environmental Policy Act (NEPA) for the management of SNF [DOE 1995]. These decisions have provided an overarching framework for SNF management, as well as site-specific and SNF-related management decisions for the past two decades. In the years since these decisions were made, with the notable exception of the successful drying and packaging of the production reactor fuel at Hanford, a majority of the decisions have been largely unimplemented. Also, since these decisions were made, a number of changes that bear on considerations relative to the path forward have occurred. A SNF Exploratory Road map activity, identified reasonable alternate pathways for DoE's inventory of SNF. Three fundamental pathways were identified in this activity for the long-term management and disposition of DOE SNF: Direct Disposal Pathway, Existing Processing Pathway and Alternate Processing Pathway. Further actions would be required (e.g., evaluation of NEPA analysis, technology maturity evaluations, refinement of cost and risks, benefits and advantages relative to other alternate paths) to define and inform many key decisions that will result in the selection of the disposition pathways that are most beneficial to the US Government in dispositioning DoE's SNF inventory. DOE is currently managing all SNF safely; however, the age of DOE-owned SNF and facilities for storing and processing SNF, coupled with the uncertainty of the storage duration, necessitates decisions and actions to ensure that the infrastructure will be in place to ensure continued safe and effective long-term management and eventual disposal. The identification of reasonable alternate pathways took these considerations into account in an effort to proactively manage conditions that could challenge the safety of storing and managing DOE SNF over the time periods now contemplated and also to ensure that flexibility is preserved to ensure that the DOE SNF remains compatible with final disposition pathways when they become available. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Environmental exposure to industrial air pollution is associated with decreased male fertility

Objective: To understand how chronic exposure to industrial air pollution is associated with male fertility through semen parameters. Design: Retrospective cohort study. Subjects: Men in the Subfertility, Health and Assisted Reproduction cohort who underwent a semen analysis 2005-2017 with ≥1 measured semen parameter (N=21,563). Intervention(s): Residential histories for each man were constructed using locations from administrative records linked through the Utah Population Database. Industrial facilities with air emissions of nine endocrine disrupting compound chemical classes were identified from the Environmental Protection Agency Risk-Screening Environmental Indicators microdata. Chemical levels were linked with residential histories for the 5 years prior to each semen analysis. Main Outcome Measures: Semen analyses were classified as azoospermic or oligozoospermic (< 15 M/mL) using World Health Organization cutoffs for concentration. Bulk semen parameters such as concentration, total count, ejaculate volume, total motility, total motile count, and total progressive motile count were also measured. Multivariable regression models with robust standard errors were used to associate exposure quartiles for each of the nine chemical classes with each semen parameter, adjusting for age, race, and ethnicity, as well as neighborhood socioeconomic disadvantage. Results: After adjustment for demographic covariates, several chemical classes were associated with azoospermia and decreased total motility and volume. For exposure in the 4th relative to 1st quartile, significant associations were observed for acrylonitrile (β total motility = -0.87 pp), aromatic hydrocarbons (odds ratio [OR]azoospermia = 1.53; β volume = -0.14 mL), dioxins (OR azoospermia = 1.31; β volume = -0.09 mL; β total motility = -2.65 pp), heavy metals (β total motility = -2.78pp), organic solvents (OR azoospermia = 1.75; β volume = -0.10 mL), organochlorines (OR azoospermia = 2.09; β volume = -0.12 mL), phthalates (OR azoospermia = 1.44; β volume = -0.09 mL; β total motility = -1.21 pp), and silver particles (OR azoospermia = 1.64; β volume = -0.11 mL). All semen parameters significantly decreased with increasing socioeconomic disadvantage. Men who lived in the most disadvantaged areas had concentration, volume, and total motility of 6.70 M/mL, 0.13 mL, and 1.79 pp lower, respectively. Count, motile count, and total progressive motile count all decreased by 30–34 M.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Surface Reconstruction in Hydrated Amphiphilic Block Copolymer Thin Films Probed by Fluid Cell Atomic Force Microscopy

In many thin film materials, nuanced interplays of interfacial energies control the surface morphology and rearrangement. This work evaluates polymer−solvent interactions and solvent-driven surface reconstructions via ex situ and in situ fluid cell Atomic Force Microscopy (fc-AFM) analysis of amphiphilic block copolymer (BCP) thin films upon exposure to deionized (DI) water. We examine the differences in surface morphology, whole-film swelling, and force response in thin films of polystyrene-block-poly(ethylene oxide) (PS-b-PEO) and polystyrene- block-poly[(allyl glycidyl ether)-co-(ethylene oxide)] (PS-b- P[AGE-co-EO]) processed into standing-up cylinder morphologies perpendicular to a silicon substrate (⊥C). Using Amplitude Modulation AFM (AM-AFM) and Amplitude-Phase Distance (APD) force spectroscopy, this work probes the mechanoresponsive nature of the dynamic surface layers of these films, unveiling surface layer stratification and surface chain rearrangement via minimal tip−sample stimulation. To help rationalize the observed reconfigurations, the energetic driving forces were estimated using the harmonic mean approximations of interfacial energies. Given the nonionizable nature of the minority P(AGE-co-EO) block and the energetic driving forces for chain mobility, this work shows how the elimination of unfavorable PS−water interfaces drives chain rearrangement and coverage of the PS surface by chains of the hydrophilic block. This work highlights considerations for increasing the heterogeneity and complexity of BCP thin films via random blocks and how those changes to local interfacial energies may drive larger scale film morphology reconstructions, with broader implications for tuning interface hydrophilicity.

Copolymers↗

Comprehensive characterization of N- and O- glycosylation of SARS-CoV-2 human receptor angiotensin converting enzyme 2

The emergence of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created the need for development of new therapeutic strategies. Understanding the mode of viral attachment, entry and replication has become a key aspect of such interventions. The coronavirus surface features a trimeric spike (S) protein that is essential for viral attachment, entry and membrane fusion. The S protein of SARS-CoV-2 binds to human angiotensin converting enzyme 2 (hACE2) for entry. Herein, we describe glycomic and glycoproteomic analysis of hACE2 expressed in HEK293 cells. We observed high glycan occupancy (73.2 to 100%) at all seven possible N-glycosylation sites and surprisingly detected one novel O-glycosylation site. To deduce the detailed structure of glycan epitopes on hACE2 that may be involved in viral binding, we have characterized the terminal sialic acid linkages, the presence of bisecting GlcNAc and the pattern of N-glycan fucosylation. We have conducted extensive manual interpretation of each glycopeptide and glycan spectrum, in addition to using bioinformatics tools to validate the hACE2 glycosylation. Our elucidation of the site-specific glycosylation and its terminal orientations on the hACE2 receptor, along with the modeling of hACE2 glycosylation sites can aid in understanding the intriguing virus-receptor interactions and assist in the development of novel therapeutics to prevent viral entry. Here, the relevance of studying the role of ACE2 is further increased due to some recent reports about the varying ACE2 dependent complications with regard to age, sex, race and pre-existing conditions of COVID-19 patients.

59 BASIC BIOLOGICAL SCIENCES↗

Stakeholder Engagement Review Meeting Summary Report

Sustainability in the context of the Light Water Reactor Sustainability (LWRS) Program is the ability to maintain the safe and economic operation of the existing fleet of nuclear power plants now and in the future. It has two objectives with respect to long-term operations: (1) to provide science and technology-based solutions to industry to safely enhance the economical operation of power reactors; and (2) to manage the aging of systems, structures, and components (SSCs) so that nuclear power plants can continue to operate safely and cost-effectively.

42 ENGINEERING↗

Association of post-COVID phenotypic manifestations with new-onset psychiatric disease

Acute COVID-19 infection can be followed by diverse clinical manifestations referred to as Post Acute Sequelae of SARS-CoV2 Infection (PASC). Studies have shown an increased risk of being diagnosed with new-onset psychiatric disease following a diagnosis of acute COVID-19. However, it was unclear whether non-psychiatric PASC-associated manifestations (PASC-AMs) are associated with an increased risk of new-onset psychiatric disease following COVID-19. A retrospective electronic health record (EHR) cohort study of 2,391,006 individuals with acute COVID-19 was performed to evaluate whether non-psychiatric PASC-AMs are associated with new-onset psychiatric disease. Data were obtained from the National COVID Cohort Collaborative (N3C), which has EHR data from 76 clinical organizations. EHR codes were mapped to 151 non-psychiatric PASC-AMs recorded 28–120 days following SARS-CoV-2 diagnosis and before diagnosis of new-onset psychiatric disease. Association of newly diagnosed psychiatric disease with age, sex, race, pre-existing comorbidities, and PASC-AMs in seven categories was assessed by logistic regression. There were significant associations between a diagnosis of any psychiatric disease and five categories of PASC-AMs with odds ratios highest for neurological, cardiovascular, and constitutional PASC-AMs with odds ratios of 1.31, 1.29, and 1.23 respectively. Secondary analysis revealed that the proportions of 50 individual clinical features significantly differed between patients diagnosed with different psychiatric diseases. Our study provides evidence for association between non-psychiatric PASC-AMs and the incidence of newly diagnosed psychiatric disease. Significant associations were found for features related to multiple organ systems. This information could prove useful in understanding risk stratification for new-onset psychiatric disease following COVID-19. Prospective studies are needed to corroborate these findings.

60 APPLIED LIFE SCIENCES↗