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At least 271 records · Page 15

Recycling of natural fiber composites: Challenges and opportunities

Natural fibers have been widely used for reinforcing polymers attributed to their sustainable nature, excellent stiffness to weight ratio, biodegradability, and low cost compared with synthetic fibers like carbon or glass fibers. Thermoplastic composites offer an advantage of recyclability after their service life, but challenges and opportunities remain in the recycling of natural fiber reinforced polymer composites (NFRPCs). This article summarized the effects of reprocessing/recycling on the material properties of NFRPCs. The material properties considered include mechanical performance, thermal properties, hygroscopic behavior, viscoelasticity, degradation, and durability. NFRPCs can generally be recycled approximately 4–6 times until their thermomechanical properties change. After recycling 7 times, the tensile strength of NFRPCs can decrease by 17%, and the tensile modulus can decrease by 28%. The mitigation approaches to overcome degradation of material properties of NFRPCs such as adding functional additives and virgin plastics are also discussed. The main challenges in these approaches such as degradation and incompatibility are discussed, and an effort is made to provide a rationale for reprocessing/recyclability assessment. Finally, future applications of NFRPCs such as additive manufacturing and automotive part use are discussed.

36 MATERIALS SCIENCE↗

Post-landing major element quantification using SuperCam laser induced breakdown spectroscopy

The SuperCam instrument on the Perseverance Mars 2020 rover uses a pulsed 1064 nm laser to ablate targets at a distance and conduct laser induced breakdown spectroscopy (LIBS) by analyzing the light from the resulting plasma. SuperCam LIBS spectra are preprocessed to remove ambient light, noise, and the continuum signal present in LIBS observations. Prior to quantification, spectra are masked to remove noisier spectrometer regions and spectra are normalized to minimize signal fluctuations and effects of target distance. In some cases, the spectra are also standardized or binned prior to quantification. To determine quantitative elemental compositions of diverse geologic materials at Jezero crater, Mars, we use a suite of 1198 laboratory spectra of 334 well-characterized reference samples. The samples were selected to span a wide range of compositions and include typical silicate rocks, pure minerals (e.g., silicates, sulfates, carbonates, oxides), more unusual compositions (e.g., Mn ore and sodalite), and replicates of the sintered SuperCam calibration targets (SCCTs) onboard the rover. For each major element (SiO 2 , TiO 2 , Al 2 O 3 , FeO T , MgO, CaO, Na 2 O, K 2 O), the database was subdivided into five “folds” with similar distributions of the element of interest. One fold was held out as an independent test set, and the remaining four folds were used to optimize multivariate regression models relating the spectrum to the composition. We considered a variety of models, and selected several for further investigation for each element, based primarily on the root mean squared error of prediction (RMSEP) on the test set, when analyzed at 3 m. In cases with several models of comparable performance at 3 m, we incorporated the SCCT performance at different distances to choose the preferred model. Shortly after landing on Mars and collecting initial spectra of geologic targets, we selected one model per element. Subsequently, with additional data from geologic targets, some models were revised to ensure results that are more consistent with geochemical constraints. The calibration discussed here is a snapshot of an ongoing effort to deliver the most accurate chemical compositions with SuperCam LIBS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exposure, health effects, sensing, and remediation of the emerging PFAS contaminants – Scientific challenges and potential research directions

Per- and polyfluoroalkyl substances (PFAS) make up a large group of persistent anthropogenic chemicals which are difficult to degrade and/or destroy. PFAS are an emerging class of contaminants, but little is known about the long-term health effects related to exposure. In addition, technologies to identify levels of contamination in the environment and to remediate contaminated sites are currently inadequate. In this opinion-type discussion paper, a team of researchers from the University of Connecticut and the University at Albany discuss the scientific challenges in their specific but intertwined PFAS research areas, including rapid and low-cost detection, energy-saving remediation, the role of T helper cells in immunotoxicity, and the biochemical and molecular effects of PFAS among community residents with measurable PFAS concentrations. Potential research directions that may be employed to address those challenges and improve the understanding of sensing, remediation, exposure to, and health effects of PFAS are then presented. Here, we hope our account of emerging problems related to PFAS contamination will encourage a broad range of scientific experts to bring these research initiatives addressing PFAS into play on a national scale.

Challenges and research directions↗

Sink or source? Insights into the behavior of copper and zinc in the sediment porewater of a constructed wetland by peepers

The H-02 free water surface constructed wetland has been applied to remove heavy metals, mainly copper (Cu) and zinc (Zn), from wastewater on the Savannah River Site (Aiken, SC, USA). More and more studies focus on the metal behavior between the sediment and the overlying water, which directly reflects the stability of metals after sedimentation in constructed wetlands. This study focused on the biogeochemical pathways in metal bioavailability and remobilization in the sediment after metals were removed from the overlying water. The dialysis sampling devices (peepers) were used to collect porewater samples from eight depths in the sediment for the measurement of Cu, Zn, dissolved organic carbon (DOC), and major anions (sulfate and chloride). Surface water samples were also collected for the measurement of Cu, Zn, DOC, and anions. Different temporal trends were observed for dissolved Cu between the surface and bottom waters, but not for dissolved Zn. There were no obvious changes in porewater metal concentrations with increasing depths in the sediment. Sediment served as a sink for Cu as only 3% of porewater samples showed higher labile Cu concentrations than the surface water during the entire year. Furthermore, sediment served as a source for Zn in summer and winter as 32% of porewater samples showed higher labile Zn concentrations than the surface water, and these samples were collected at all sediment depths. We think the seasonal changes in the behaviors of Cu and Zn were primarily controlled by the sulfur dynamics and the metal removal processes in the constructed wetland, as well as the different complexing chemistry between Cu and Zn. Also, our study supports that peeper is a powerful tool for studying the biogeochemistry of metals in the sediment.

54 ENVIRONMENTAL SCIENCES↗

Bioaccumulation of contaminants in Scarabaeidae and Silphidae beetles at sites polluted by coal combustion residuals and radiocesium

Anthropogenic contamination from coal-fired power plants and nuclear reactors is a pervasive issue impacting ecosystems across the globe. As a result, it is critical that studies continue to assess the accumulation and effects of trace elements and radionuclides in a diversity of biota. In particular, bioindicator species are a powerful tool for risk assessment of chemically contaminated habitats. Using inductively coupled plasma mass spectrometry (ICP-MS) and auto-gamma counting, we analyzed trace element and radiocesium contaminant concentrations in Scarabaeidae and Silphidae beetles (Order: Coleoptera), important taxa in decomposition and nutrient cycling, at contaminated and reference sites on the Savannah River Site, South Carolina, U.S. Our results revealed variability in trace element concentrations between Scarabaeidae and Silphidae beetles at uncontaminated and contaminated sites. Compared to Scarabaeidae, Silphidae had higher levels of chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), and zinc (Zn). Unexpectedly, concentrations of Cr, Cu, and Ni were higher in both taxa at the uncontaminated sites. Scarabaeidae and Silphidae beetles at the coal combustion waste site consistently had high concentrations of arsenic (As), and Scarabaeidae had high concentrations of selenium (Se). Of the 50 beetles analyzed for radiocesium levels, two had elevated radioactivity concentrations, both of which were from a site contaminated with radionuclides. Furthermore, our results suggest carrion beetles may be particularly sensitive to bioaccumulation of contaminants due to their trophic position and role in decomposition, and thus are useful sentinels of trace element and radionuclide contamination.

59 BASIC BIOLOGICAL SCIENCES↗

Generation of a fluorescent short-lifetime oxygen nanosensor by coupling of an exciplex forming dye pair

Typical oxygen-sensitive dyes have lifetimes in the μs-ms regime for sensitive oxygen detection based on molecular quenching. Due to the long triplet-state lifetimes and poor quenching efficiency of these probes, it has been difficult to develop short lifetime probes. We have developed oxygen sensors using a short-lifetime dye (∼30–60 ns) that forms an anthracene-aniline exciplex, which is quenched by molecular oxygen through an excited-state charge transfer mechanism. To achieve measurements in aqueous systems, we have tethered the dyes together via a C3 alkyl linker to facilitate greater exciplex formation at low dye concentration (20 μg mL −1 ) and encapsulated the resulting compound into polymeric nanoparticles to form an aqueous-dispersible short-lifetime oxygen nanosensor. The sensors emit at 420 nm (unfolded dye) and 500 nm (exciplex), and the ratiometric Stern-Volmer Constant is 1.52 ± 0.02 L mol −1 , showing good sensitivity from 0 % to 40 % dissolved oxygen without the tradeoff of a long lifetime needed for direct molecular quenching. In this paper, we characterize this sensor for both lifetime-based measurements using time-correlated single-photon counting and ratiometric intensity-based measurements using the unfolded dye emission as an internal reference peak.

Biological and medical sciences↗

Microbial extracellular polysaccharide production and aggregate stability controlled by switchgrass ( Panicum virgatum ) root biomass and soil water potential

Deep-rooting perennial grasses are promising feedstocks for biofuel production, especially in marginal soils lacking organic material, nutrients, and/or that experience significant water stress. Perennial grass roots influence surrounding soil conditions and microbial activities, and produce extracellular polymeric substances (EPS) composed primarily of extracellular polysaccharides (EPSac). These polymers can alleviate microbial moisture and nutrient stress, and enhance soil characteristics through improved water retention and aggregate stability—which may in turn enhance carbon persistence. Here, we used a 13 CO 2 greenhouse tracer experiment to examine the effect of switchgrass cultivation on EPSac production and origin in a marginal soil with five fertilization/water treatments (control, +N, +NP, +P, low water), and compared these results with measurements of field soils collected after long-term switchgrass cultivation. Soils with added nitrogen and phosphorus (+NP) had the highest root biomass, EPSac and percentage of water-stable soil aggregates. Multiple linear regression analyses revealed that root biomass and soil water potential were important determinants of soil EPSac production, potentially by controlling carbon supply and diurnal changes in moisture stress. Path analysis showed that soil aggregation was positively correlated with bulk soil EPSac content and also regulated by soil water potential. High mannose content indicated the majority of EPSac was of microbial origin and 13 CO 2 labeling indicated that 0.18% of newly fixed plant carbon was incorporated into EPSac. Analysis of field soils suggests that EPSac is significantly enhanced after long-term switchgrass cultivation. Taken as a whole, our greenhouse and field results demonstrate that switchgrass cultivation can promote microbial production of EPSac, providing a mechanism to enhance aggregation in marginal soils.

13c labeling↗

Active microbial biomass decreases, but microbial growth potential remains similar across soil depth profiles under deeply-vs. shallow-rooted plants

Climate-smart land management practices that replace shallow-rooted annual crop systems with deeply-rooted perennial plants can contribute to soil carbon sequestration. However, deep soil carbon accrual may be influenced by active microbial biomass and their capacity to assimilate fresh carbon at depth. Incorporating active microbial biomass, dormancy, and growth in microbially-explicit models can improve our ability to predict soil's capacity to store carbon. But, so far, the microbial parameters that are needed for such modeling are poorly constrained, especially in deep soil layers. Here, we used a lab incubation experiment and growth kinetics model to estimate how microbial parameters vary along 240 cm of soil depth in profiles under shallow- (soy) and deeply-rooted (switchgrass) plants 11 years after plant cover conversion. We also assessed resource origin and availability (total organic carbon, 14 C, extractable organic carbon, specific UV absorbance of K 2 SO 4 extractable organic C, total nitrogen, total dissolved nitrogen) along the soil profiles to examine associations between soil chemical and biological parameters. Even though root biomass was greater and rooting depth was deeper under switchgrass than soy, resource availability and microbial growth parameters were generally similar between vegetation types. Instead, depth significantly influenced soil chemical and biological parameters. For example, resource availability and total and relative active microbial biomass decreased with soil depth. Decreases in the relative active microbial biomass coincided with increased lag time (response time to external carbon inputs) along the soil profiles. Even at a depth of 210–240 cm, microbial communities were activated to grow by added resources within a day. Maximum specific growth rate decreased to a depth of 90 cm and then remained consistent in deeper layers. Our findings show that >10 years of vegetation and rooting depth changes may not be long enough to alter microbial growth parameters, and suggest that at least a portion of the microbial community in deep soils can grow rapidly in response to added resources. Our study determined microbial growth parameters that can be used in microbially-explicit models to simulate carbon dynamics in deep soil layers.

14C↗

Phosphate amendment drives bloom of RNA viruses after soil wet-up

Soil rewetting after a dry period results in a surge of activity and succession in both microbial and DNA virus communities. Less is known about the response of RNA viruses to soil rewetting—while they are highly diverse and widely distributed in soil, they remain understudied. We hypothesized that RNA viruses would show temporal succession following rewetting and that phosphate amendment would influence their trajectory, as viral proliferation may cause phosphorus limitation. Using 39 time-resolved metatranscriptomes and amplicon data, 2190 RNA viral populations were identified across five phyla, with 26 % of these predicted to infect bacteria, and 11 % fungi. Only 1.2 % of viral populations had annotated capsid genes, suggesting most persist via intracellular replication without a free virion phase. Phosphate amendment altered RNA viral community composition within the first week and amended vs. unamended communities remained distinguishable for up to three weeks. While the overall host community remained stable, certain bacterial populations showed reduced abundance in phosphate-amended soils, likely due to increased viral lysis, as RNA bacteriophages proliferated significantly. Notably, 60 % of the viruses with increased abundance under phosphate amendment belonged to basal Lenarviricota clades rather than well-known groups like Leviviricetes. We estimate RNA bacteriophage infections may affect 10 7 –10 9 bacteria per gram of soil, aligning with the total bacterial population (10 7 –10 10 g -1 soil), suggesting that RNA phages significantly influence bacterial communities post-wet-up, with phosphorus availability modulating this effect.

59 BASIC BIOLOGICAL SCIENCES↗

High-throughput characterization of Lu-doped zirconia

Lu-doped zirconia (LuDZ) was reported in the 1960s to be a poor oxygen ion conductor. However, we identified this system as worthy of reexamination based on the results of a machine learning-based screen for promising oxygen ion conductors, further supported by a physical argument: because Lu is the heaviest and smallest of the lanthanides, it should offer the possibility of high conductivity due to its high polarizability and size compatibility with the zirconia structure. Here the relationship between dopant concentration and conductivity in the LuDZ system was determined using a high throughput experimental methodology in which spatially resolved conductivity was measured across a compositionally graded film, spanning from Zr 0.93 Lu 0.07 O 1.965 to Zr 0.82 Lu 0.18 O 1.91 . The conductivity broadly peaks with composition at 15 cation % Lu, coinciding with the approximate phase boundary of the fully stabilized cubic phase. The composition-dependent conductivity measurements reveal a surprising increase in activation energy for ion transport with increasing Lu content with no change in this trend at the composition of the conductivity maximum. The pre-exponential factor increases sharply with Lu content, but displays a distinct plateau once the conductivity maximum composition is attained. At 500 °C, the conductivity of Zr 0.85 Lu 0.15 O 1.925 is 2 × 10 –3 S cm –1 , approaching that of optimally doped Sc-stabilized zirconia, which has the highest reported conductivity among zirconia compounds. In comparison to other oxide ion conductors, Lu-stabilized zirconia offers the advantage over ceria of negligible electronic conductivity and is easier to process than (La,Sr)(Ga,Mg)O 3-δ .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Translating dosimetry of Dibenzo[ def,p ]chrysene (DBC) and metabolites across dose and species using physiologically based pharmacokinetic (PBPK) modeling

We report that Dibenzo[def,p]chrysene (DBC) is an environmental polycyclic aromatic hydrocarbon (PAH) that causes tumors in mice and has been classified as a probable human carcinogen by the International Agency for Research on Cancer. Animal toxicity studies often utilize higher doses than are found in relevant human exposures. Additionally, like many PAHs, DBC requires metabolic bioactivation to form the ultimate toxicant, and species differences in DBC and DBC metabolite metabolism have been observed. To understand the implications of dose and species differences, a physiologically based pharmacokinetic model (PBPK) for DBC and major metabolites was developed in mice and humans. Metabolism parameters used in the model were obtained from experimental in vitro metabolism assays using mice and human hepatic microsomes. PBPK model simulations were evaluated against mice dosed with 15 mg/kg DBC by oral gavage and human volunteers orally microdosed with 29 ng of DBC. DBC and its primary metabolite DBC-11,12-diol were measured in blood of mice and humans, while in urine, the majority of DBC metabolites were obeserved as conjugated DBC-11,12-diol, conjugated DBC tetrols, and unconjugated DBC tetrols. The PBPK model was able to predict the time course concentrations of DBC, DBC-11,12-diol, and other DBC metabolites in blood and urine of human volunteers and mice with reasonable accuracy. Agreement between model simulations and measured pharmacokinetic data in mice and human studies demonstrate the success and versatility of our model for interspecies extrapolation and applicability for different doses. Furthermore, our simulations show that internal dose metrics used for risk assessment do not necessarily scale allometrically, and that PBPK modeling provides a reliable approach to appropriately account for interspecies differences in metabolism and physiology.

59 BASIC BIOLOGICAL SCIENCES↗

Bivalent hemagglutinin and neuraminidase influenza replicon particle vaccines protect pigs against influenza a virus without causing vaccine associated enhanced respiratory disease

Alphavirus-derived RNA replicon particle (RP) vaccines represent the next generation of swine influenza A virus (IAV) vaccines, as they were shown to be safe, effective, and offer advantages over traditional vaccine platforms. IAV is a significant respiratory pathogen of swine and there is a critical need to improve current commercial swine IAV vaccine platforms. Adjuvanted whole inactivated virus (WIV) IAV swine vaccines provide limited heterologous protection and may lead to vaccine-associated enhanced respiratory disease (VAERD). This study investigated the ability of RP IAV hemagglutinin (HA) vaccines to avoid VAERD and evaluated experimental multivalent HA and neuraminidase (NA) RP vaccines. RP vaccines were formulated with HA or NA heterologous or homologous to the challenge virus in monovalent HA or HA and NA bivalent combinations (HA/NA bivalent). Pigs were vaccinated with an HA RP, HA/NA bivalent RP, or heterologous HA WIV, followed by IAV challenge and necropsy 5 days post infection. RP vaccines provided homologous protection from challenge and induced robust peripheral and local antibody responses. The RP vaccine did not induce VAERD after challenge with a virus containing the heterologous HA, in contrast to the traditional WIV vaccine. The HA monovalent and HA/NA bivalent RP vaccines showed superior protection compared to traditional WIV. Additionally, the RP platform allows greater flexibility to adjust HA and NA content to reflect circulating IAV in swine antigenic diversity.

60 APPLIED LIFE SCIENCES↗

Phylogenomics reveals convergent evolution of red-violet coloration in land plants and the origins of the anthocyanin biosynthetic pathway

The flavonoids, one of the largest classes of plant secondary metabolites, are found in lineages that span the land plant phylogeny and play important roles in stress responses and as pigments. Perhaps the most well-studied flavonoids are the anthocyanins that have human health benefits and help plants attract pollinators, regulate hormone production, and confer resistance to abiotic and biotic stresses. The canonical biochemical pathway responsible for the production of these pigments is well-characterized for flowering plants yet its conservation across deep divergences in land plants remains debated and poorly understood. Many early land plants such as mosses, liverworts, and ferns produce flavonoid pigments, but their biosynthetic origins and homologies to the anthocyanin pathway remain uncertain. We conducted phylogenetic analyses using full genome sequences representing nearly all major green plant lineages to reconstruct the evolutionary history of the anthocyanin biosynthetic pathway then test the hypothesis that genes in this pathway are present in early land plants. We found that the entire pathway was not intact until the most recent common ancestor of seed plants and that orthologs of many downstream enzymes are absent from seedless plants including mosses, liverworts, and ferns. Our results also highlight the utility of phylogenetic inference, as compared to pairwise sequence similarity, in orthology assessment within large gene families that have complex duplication-loss histories. Here, we suggest that the production of red-violet flavonoid pigments widespread in seedless plants, including the 3-deoxyanthocyanins, requires the activity of novel, as-yet discovered enzymes, and represents convergent evolution of red-violet coloration across land plants.

59 BASIC BIOLOGICAL SCIENCES↗

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The influence of environmental microseismicity on detection and interpretation of small-magnitude events in a polar glacier setting

Glacial environments exhibit temporally variable microseismicity. To investigate how microseismicity influences event detection, we implement two noise-adaptive digital power detectors to process seismic data from Taylor Glacier, Antarctica. We add scaled icequake waveforms to the original data stream, run detectors on the hybrid data stream to estimate reliable detection magnitudes and compare analytical magnitudes predicted from an ice crack source model. We find that detection capability is influenced by environmental microseismicity for seismic events with source size comparable to thermal penetration depths. When event counts and minimum detectable event sizes change in the same direction (i.e. increase in event counts and minimum detectable event size), we interpret measured seismicity changes as ‘true’ seismicity changes rather than as changes in detection. Generally, one detector (two degree of freedom (2dof)) outperforms the other: it identifies more events, a more prominent summertime diurnal signal and maintains a higher detection capability. We conclude that real physical processes are responsible for the summertime diurnal inter-detector difference. One detector (3dof) identifies this process as environmental microseismicity; the other detector (2dof) identifies it as elevated waveform activity. Our analysis provides an example for minimizing detection biases and estimating source sizes when interpreting temporal seismicity patterns to better infer glacial seismogenic processes.

54 ENVIRONMENTAL SCIENCES↗

Radiocarbon analysis of soil microbial biomass via direct chloroform extraction

Microbial processing of soil organic matter is a significant driver of C cycling, yet we lack an understanding of what shapes the turnover of this large terrestrial pool. In part, this is due to limited options for accurately identifying the source of C assimilated by microbial communities. Laboratory incubations are the most common method for this; however, they can introduce artifacts due to sample disruption and processing and can take months to produce sufficient CO 2 for analysis. We present a biomass extraction method which allows for the direct 14 C analysis of microbial biomolecules and compare the results to laboratory incubations. In the upper 50 cm soil depths, the Δ 14 C from incubations was indistinguishable from that of extracted microbial biomass. Below 50 cm, the Δ 14 C of the biomass was more depleted than that of the incubations, either due to the stimulation of labile C decomposition in the incubations, the inclusion of biomolecules from non-living cells in the biomass extractions, or differences in C used for assimilation versus respiration. Our results suggest that measurement of Δ 14 C of microbial biomass extracts can be a useful alternative to soil incubations.

54 ENVIRONMENTAL SCIENCES↗