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At least 433 records · Page 24

Editorial special issue: Advancing foundational sun-induced chlorophyll fluorescence science

The first research on the possibilities offered by chlorophyll-a fluorescence to track the daily course of CO 2 assimilation by leaves dates back to the last century (Kautsky and Hirsch, 1931). In the second half of the XXth Century, the development of the field of active fluorescence, which relies mainly on the pulse amplitude modulation (PAM) fluorimetry technique, allowed the unraveling of the relationship between the yield of chlorophyll-a fluorescence and photochemistry (linear electron transport), which is modulated by a third process known as non-photochemical quenching (Genty et al., 1989). Since then, active fluorescence has been regularly used in ecophysiology, forestry, and crop sciences to understand the plant response to stress (Schreiber, 2004). Since the beginning of the 2000s, the development of portable field spectrometers allows for measuring passive sun-induced fluorescence (SIF) at strong solar or telluric absorption features, which do not rely on the use of artificial excitation light (e.g., Meroni and Colombo, 2006; Meroni et al., 2009; Perez-Priego et al., 2005). Since then, the field has rapidly evolved, and now fluorescence is measurable with automated field spectrometers in the field (Grossmann et al., 2018; Gu et al., 2019b; Rossini et al., 2010), airborne platforms (Rascher et al., 2015; Zarco-Tejada et al., 2000), and satellites (Guanter et al., 2012; Sun et al., 2018). These advances offer the potential to couple ecosystem-scale measurements of CO 2 fluxes and SIF to probe new aspects related to ecosystem structural impacts on SIF andphotosynthesis processes at different time-scales and on different ecosystems (e.g., Damm et al., 2010; Magney et al., 2019; Porcar-Castell et al., 2021). While SIF has been proven as a good proxy of gross primary productivity (GPP), mainly across large spatial and temporal gradients, a series of studies showed that different factors could confound this relationship, namely different canopy structures (e.g., Dechant et al., 2020; Migliavacca et al., 2017), stress conditions (e.g., Martini et al., 2022; Wieneke et al., 2018; Wohlfahrt et al., 2018), nutritional conditions (Cendrero-Mateo et al., 2015; Martini et al., 2019), species-specific differences (e.g., Van Wittenberghe et al., 2013) and light regimes (e.g., Liu and Liu, 2018). At the same time, the modeling of SIF developed rapidly (Gu et al., 2019a; Han et al., 2022; Han et al., 2021; van der Tol et al., 2014; van der Tol et al., 2009) and with an increasing degree of realism, offering the possibility to retrieve important vegetation parameters from remote sensing (Pacheco-Labrador et al., 2019; Verrelst et al., 2015; Verrelst et al., 2016; Zhang et al., 2014). Excellent and comprehensive reviews of the field are by (Mohammed et al., 2019; Porcar-Castell et al., 2021; Porcar-Castell et al., 2014; Sun et al., 2023a; Sun et al., 2023b). Despite the exponential increase in the number of publications in the field, significant progress is still needed. Here, this special issue aims to report foundational SIF science, including theoretical modeling and measurement-based research that is urgently needed to unleash the full potential of SIF for physiological and ecological applications at scales spanning from leaf to globe. The 14 articles collected in this special issue reported on the following specific aspects: first, technical capabilities enabling spectrally resolved SIF observations and their inter-comparability in space and time; second, theoretical developments in SIF-photosynthesis relationships to correctly interpret the signal and extract mechanistic information on vegetation structure and function; third, evaluation of the potential of SIF to track process beyond photosynthesis, such as transpiration; fourth, large scale-applications of SIF observations; and finally, upscaling fluorescence from leaf to canopy scales.

54 ENVIRONMENTAL SCIENCES↗

Modelling dislocation-graphene interactions in a BCC Fe matrix by molecular dynamics simulations and gradient plasticity theory

We report graphene nanosheets (GNS) can enhance the strength and ductility of metal-based composites as they can obstruct the propagation of dislocations. The present article employs Molecular Dynamics (MD) simulations to investigate dislocation-GNS interaction mechanisms and possible influencing factors, including the number of GNS layers, the thickness of the metallic amorphous layer and the C - C bond strength. The results indicated that the shear strength of the metal/GNS interface and the bending stiffness of GNS determined the ability of GNS to block dislocation transmission. A physically based phenomenological parameter that can capture such dislocation-GNS interactions is the mechanical interface energy that has been put forth within gradient plasticity. By fitting the theoretical expressions to the simulation data, it was possible to obtain estimates for the mechanical interface energy for the GNS. It was found that increasing the GNS layers and adding an amorphous layer resulted in a strengthening in the stress–strain response and increased the value of this interfacial parameter. This indicates that the mechanical interfacial energy can be a unified measure for capturing and tuning the strength of various interfaces such as grain boundaries, GNS, amorphous-crystalline interface and bimetal interfaces.

36 MATERIALS SCIENCE↗

Effects of sodium and calcium chloride ionic stresses on model yeast membranes revealed by molecular dynamics simulation

As efforts to move a renewable economy grow, it will be necessary to make use of microbial conversion strategies for the production of novel materials or the upgrading of waste to high-value products. One critical technical challenge currently limiting waste upgrading remains the difficulty in obtaining single-pot conversion techniques where physical, chemical, and biological conversion are performed in a single step. To overcome this challenge, a detailed understanding of how different stresses impact microbial membrane stability will be necessary. In this work, using all-atom molecular dynamics simulations, we examine the impacts of moderate concentrations of NaCl and CaCl 2 on a model yeast plasma membrane. Weak, though statistically significant, changes in membrane morphology and dynamics functions are observed that are consistent with swelling and stiffening. Additionally, an examination of the ion-lipid contacts and the behavior of water at the water-membrane interface suggests that the impacts of these common salts may, in part, be mediated through changes to water-membrane hydrogen-bonding and hydration water dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing a robust strength model using physically-informed genetic programming

The strength of materials is influenced by a range of external conditions, such as temperature and deformation rate. Consequently, materials that demonstrate substantial variations in their mechanical behavior due to fluctuations in temperature and strain rate require complex strength models to accurately predict material performance in real-world applications. To predict such complex behavior, a robust and flexible strength model is necessary. In this work, we utilize genetic programming-based symbolic regression (GPSR) to develop data-driven strength models that accurately represent the measured stress–strain responses of tin across a wide range of strain, strain rate and temperature regimes. The GPSR models are constrained by physically-informed conditions, which leads to significant improvement in extrapolation. The best model is integrated into a multi-physics code to perform Taylor impact simulations, validating the model’s accuracy and robustness. In conclusion, the model predictions showed excellent agreement with experimental results, particularly when compared to predictions using traditional strength models.

Genetic programming↗

Modeling strategy for progressive failure prediction in lithium-ion batteries under mechanical abuse

The prediction for the internal failure of lithium-ion batteries (LIBs) under external mechanical abuse loading remains a challenge for safe design. This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction. Hemispherical indentation experiments are conducted on a battery specimen containing 5 representative sandwich (RS) layers to examine the deformation and progressive failure behavior of battery components. Three different models, viz, a high-fidelity detailed model, an intermediate homogenized model and a fully homogenized model, are developed and employed to simulate the progressive failure in a multi-layer battery specimen. The simulation results obtained using the three models all correlate well with experimental phenomena, capturing the overall stress-strain response and ultimate failure of the battery structure. The numerical results can help us understand the failure behavior and the mechanism for mechanical abuse-induced short circuit in LIBs. The feasibility of the three models for use in progressive failure prediction is compared by analyzing the capability of the models in predicting the critical failure events, the computational efficiency of the models, and the feasibility to implement coupled mechanical-electrochemical-thermal simulations. The results of this work provide useful insights on practical choices for the modeling strategy and safety design of LIBs under mechanical abuse conditions.

25 ENERGY STORAGE↗

Deformation behavior of CP-titanium under strain path changes: Experiment and crystal plasticity modeling

The deformation behavior of commercially pure rolled titanium subjected to strain path changes is studied using experiments and a crystal plasticity model. Four different loading combinations are performed at room temperature to study the activation of slip, twinning, de-twinning and double-twinning in hexagonal closed packed titanium. The strain paths considered are: rolling direction compression (RDC) followed by normal direction compression (NDC), RDC followed by transverse direction compression (TDC), NDC followed by RDC, and NDC followed by TDC. An EBSD-based analysis of the distribution of boundary misorientation angles before and after reload was developed to analyze the evolution of {$10\bar{1}2$} tensile and {$11\bar{2}2$} compression twins. This analysis supports the model results concerning the treatment of twin reorientation. A de-twinning and double-twinning model accounting for back stress effects, an important feature of strain path changes, is implemented within the framework of the visco-plastic self-consistent (VPSC) model along with a dislocation density (DD) based hardening scheme. In the model, plasticity is accommodated by prismatic $\langle$a$\rangle$, basal $\langle$a$\rangle$ and pyramidal $\langle$c+a$\rangle$ slip modes, and {$10\bar{1}2$} tensile and {$11\bar{2}2$} compression twinning modes. The VPSC model predicts the evolution of twinning, de-twinning and double-twinning processes for both tensile and compression twinning modes under strain path change. The model predicts macroscopic stress-strain response, texture evolution, and twin volume fraction that are in agreement with experimental observations. The evolution of texture is investigated in detail by separately analyzing the twinned domains, rather than the evolution of the global texture.

36 MATERIALS SCIENCE↗

A data driven approach for cross-slip modelling in continuum dislocation dynamics

Cross-slip is a thermally activated process by which screw dislocation changes its glide plane to another slip plane sharing the same Burgers vector. The rate at which this process happens is determined by a Boltzmann type expression that is a function of the screw segment length and the stress acting on the dislocation. In continuum dislocation dynamics (CDD), the information regarding the length of the screw dislocation segment and local stress state on dislocations are lost due to the coarse-grained representation of the density. Here, in this work, a data driven approach to characterize the lost information by analyzing the discrete dislocation configurations is proposed to enable cross-slip modeling in the CDD framework in terms of the coarse-grained dislocation density and stress fields. The analysis showed that the screw segment length follows an exponential distribution, and the stress fluctuations, defined as the difference between the stress on the dislocations and the mean field stress in CDD, follows a Lorentzian distribution. A novel approach for cross slip implementation in CDD employing the screw segment length and stress fluctuation statistics was proposed and rigorously tested by comparing the CDD cross-slip rates with discrete dislocation dynamics (DDD) rates. This approach has been applied in conjunction with three cross-slip models used in DDD simulations differing mainly in the functional form of cross slip activation energy. It was found that different cross-slip activation energy formulations yielded different cross-slip rates, yet the effect on mechanical stress-strain response and dislocation density evolution was minimal for the [001] type loading.

42 ENGINEERING↗

Examining deformation localization of irradiated tungsten under uniaxial compression with crystal plasticity

In this work, the deformation behavior of irradiated tungsten at elevated service temperatures is examined using mechanism-based crystal plasticity finite element framework by considering multiple mechanisms, including thermal softening and irradiation hardening. The previously developed mechanism-based crystal plasticity model is first utilized to assess the yield stress of unirradiated and irradiated tungsten upon low-temperature irradiation. Additionally, the engineering stress-strain response under uniaxial compression is then predicted by considering the effect of irradiation-induced defect clusters on the motion of deformation-induced dislocations, and the predicted results agree well with the experimental measurements. More importantly, the formation and evolution of plastic strain localization zones in the form of shear bands are qualitatively captured, and the maximal principal strain distribution is quantitatively linked to the dose of irradiation damage. Finally, the deformation-induced shear band as a result of plastic instability in the compressed tungsten specimen is discussed.

36 MATERIALS SCIENCE↗

Quantification of grain boundary effects on the geometrically necessary dislocation density evolution and strain hardening of polycrystalline Mg 4Al using in situ tensile testing in scanning electron microscope and HR-EBSD

In situ tensile testing in a scanning electron microscope (SEM) in conjunction with high-resolution electron backscatter diffraction (HR-EBSD) under load was used to characterize the evolution of geometrically necessary dislocation (GND) densities at individual grain boundaries as a function of applied strain in a polycrystalline Mg—4Al alloy. The increase in GND density was investigated at plastic strains of 0 %, 0.6 %, 2.2 %, 3.3 % from the area including 76 grains and correlated with (i) geometric compatibility between slip systems across grain boundaries, and (ii) plastic incompatibility. We develop expressions for the grain boundary GND density evolution as a function of plastic strain and plastic incompatibility, from which uniaxial tensile stress-strain response of polycrystalline Mg—4Al are computed and compared with experimental measurement. The findings in this study contribute to understanding the mechanisms governing the strain hardening response of single-phase polycrystalline alloys and more reliable prediction of mechanical behaviors in diverse microstructures.

Geometrically necessary dislocations↗

Bayesian calibration of a physics-based crystal plasticity and damage model

In this work, we present a model parameter calibration procedure for a physics-based crystal plasticity model. The calibration process utilizes a powerful statistics-based Bayesian calibration method. Calibration of the crystal plasticity parameters makes use of experimentally-measured data, i.e. compressive stress–strain response, from $\langle$100$\rangle$ and $\langle$123$\rangle$ single crystal copper dynamically loaded via Kolsky bar tests. The calibration of damage parameters is achieved using experimentally-measured free-surface velocity history data from plate impact test on $\langle$100$\rangle$ and $\langle$110$\rangle$ single crystal copper, which generates shock compression followed by dynamic tensile failure. A validation assessment is then carried out by comparing the calibrated model predictions and experimental measurements of the dynamic tensile damage generated in an impacted bicrystal copper plate. Lastly, a model-informed rationale for the experimentally-observed dependence of the spatial distribution of ductile damage (porosity) on crystallography is provided.

42 ENGINEERING↗

Ribosome-inactivation by a class of widely distributed C-tail anchored membrane proteins

Ribosome hibernation is a commonly used strategy that protects ribosomes under unfavorable conditions and regulates developmental processes. Multiple ribosome-hibernation factors have been identified in all domains of life, but due to their structural diversity and the lack of a common inactivation mechanism, it is currently unknown how many different hibernation factors exist. Here, we show that the YqjD/ElaB/YgaM paralogs, initially discovered as membrane-bound ribosome binding proteins in E. coli, constitute an abundant class of ribosome-hibernating proteins, which are conserved across all proteobacteria and some other bacterial phyla. Our data demonstrate that they inhibit in vitro protein synthesis by interacting with the 50S ribosomal subunit. In vivo cross-linking combined with mass spectrometry revealed their specific interactions with proteins surrounding the ribosomal tunnel exit and even their penetration into the ribosomal tunnel. Thus, YqjD/ElaB/YgaM inhibit translation by blocking the ribosomal tunnel and thus mimic the activity of antimicrobial peptides and macrolide antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗

MPK6-mediated phosphorylation destabilizes MYC2 and attenuates its transcriptional activity in jasmonate signaling

Given the role of MYC2 as a pivotal regulator in the jasmonate (JA) signaling pathway, influencing the expression of a multitude of downstream genes (Zander et al., 2020), understanding the regulatory dynamics of MYC2 is essential for unraveling plant responses to stress conditions and hormonal signals. Previous studies on the regulation of MYC2 by MPK6 have reported conflicting findings. Takahashi et al. (2007) reported that MPK6 acts as a negative regulator of MYC2, whereas Sethi et al. (2014) proposed a positive regulatory role. Despite these findings, the precise genetic and biochemical mechanisms underlying the MPK6–MYC2 interaction remain poorly understood, highlighting the need for further investigation.

Im, Jong Hee [Michigan State University, East Lans↗

Elucidating Drought-Tolerance Mechanisms in Plant Roots through 1H NMR Metabolomics in Parallel with MALDI-MS, and NanoSIMS Imaging Techniques

As direct mediators between plants and soil, roots play an important role in metabolic responses to environmental stresses such as drought, yet these responses are vastly uncharacterized on a plant-specific level, especially for co-occurring species. Here, we aim to examine the effects of drought on root metabolic profiles and carbon allocation pathways of three tropical rainforest species by combining cutting-edge metabolomic and imaging technologies in an in situ position-specific 13C-pyruvate root-labeling experiment. Further, washed (rhizosphere-depleted) and unwashed roots were examined to test the impact of microbial presence on root metabolic pathways. Drought had a species-specific impact on the metabolic profiles and spatial distribution in Piper sp. and Hibiscus rosa sinensis roots, signifying different defense mechanisms; Piper sp. enhanced root structural defense via recalcitrant compounds including lignin, while H. rosa sinensis enhanced biochemical defense via secretion of antioxidants and fatty acids. In contrast, Clitoria fairchildiana, a legume tree, was not influenced as much by drought but rather by rhizosphere presence where carbohydrate storage was enhanced, indicating a close association with symbiotic microbes. This study demonstrates how multiple techniques can be combined to identify how plants cope with drought through different drought-tolerance strategies and the consequences of such changes on below-ground organic matter composition.

Drought, Carbon cycle, MALDI-MSI, Metabolomics, Na↗

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts’ opinion on the development and application of multi-omic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular and functional aberrations within the lesion and within individual cells. Additionally, single-cell proteomic data will be essential for the establishment of new tools that with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included: • The best way/s to analyze single-cells from fresh and preserved tissue • Detection and analysis of secreted molecules and from single cells, especially from a tissue slice • Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment • Multi-omic integration of data to support and inform proteomic measurements • Subcellular organelles – identifying abnormal structure, function, distribution and location within individual premalignant and malignant cells • How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post translational modifications (PTM) • The depth of coverage measured concurrently using single-cell techniques • Quantitation - absolute or semiquantitative? • Single methodology or multiplexed combinations? • Application of analytical methods for identification of biologically significant subsets • Data visualization of N-dimensional datasets • How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME) • Associations between intrinsic cellular processes and extrinsic stimuli • How to predict cellular responses to stress inducing stimuli • Identification of new markers for prediction of progression from precursor, benign and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells • Identification of new targets for immunoprevention or immunotherapy – identification of neoantigens and surfactome of individual cells within a lesion

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes

Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.

59 BASIC BIOLOGICAL SCIENCES↗

X-ray phase contrast imaging of Vitis spp. buds shows freezing pattern and correlation between volume and cold hardiness

Grapevine (Vitis spp.) buds must survive winter temperatures in order to resume growth when suitable conditions return in spring. They do so by developing cold hardiness through deep supercooling, but the mechanistic process of supercooling in buds remains largely unknown. Here we use synchrotron X-ray phase contrast imaging to study cold hardiness-related characteristics of V. amurensis, V. riparia, and V. vinifera buds: time-resolved 2D imaging was used to visualize freezing; and microtomography was used to evaluate morphological changes during deacclimation. Bud cold hardiness was determined (low temperature exotherms; LTEs) using needle thermocouples during 2D imaging as buds were cooled with a N 2 gas cryostream. Resolution in 2D imaging did not allow for ice crystal identification, but freezing was assessed by movement of tissues coinciding with LTE values. Freezing was observed to propagate from the center of the bud toward the outer bud scales. The freezing events observed lasted several minutes. Additionally, loss of supercooling ability appears to be correlated with increases in bud tissue volume during the process of deacclimation, but major increases in volume occur after most of the supercooling ability is lost, suggesting growth resumption processes are limited by deacclimation state.

59 BASIC BIOLOGICAL SCIENCES↗

Non-invasive measurement of leaf water content and pressure–volume curves using terahertz radiation

In this paper we describe a non-invasive method of measuring leaf water content using THz radiation and combine this with psychrometry for determination of leaf pressure–volume relationships. In contrast to prior investigations using THz radiation to measure plant water status, the reported method exploits the differential absorption characteristic of THz radiation at multiple frequencies within plant leaves to determine absolute water content in real-time. By combining the THz system with a psychrometer, pressure–volume curves were generated in a completely automated fashion for the determination of leaf tissue water relations parameters including water potential at turgor loss, osmotic potential at full turgor and the relative water content at the turgor loss point. This novel methodology provides for repeated, non-destructive measurement of leaf water content and greatly increased efficiency in generation of leaf PV curves by reducing user handling time.

59 BASIC BIOLOGICAL SCIENCES↗

Phase transformation path in Aluminum under ramp compression; simulation and experimental study

Abstract We present a framework based on non-equilibrium molecular dynamics (NEMD) to reproduce the phase transformation event of Aluminum under ramp compression loading. The simulated stress-density response, virtual x-ray diffraction patterns, and structure analysis are compared against the previously observed experimental laser-driven ramp compression in-situ x-ray diffraction data. The NEMD simulations show the solid–solid phase transitions are consistent to experimental observations with a close-packed face-centered cubic (fcc) (111), hexagonal close-packed (hcp) structure (002), and body-centered cubic bcc (110) planes remaining parallel. The atomic-level analysis of NEMD simulations identifiy the exact phase transformation pathway happening via Bain transformation while the previous in situ x-ray diffraction data did not provide sufficient information for deducing the exact phase transformation path.

36 MATERIALS SCIENCE↗