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At least 343 records · Page 19

PhILMs: Collaboratory on Mathematics and Physics-Informed Learning Machines for Multiscale and Multiphysics Problems

The landscape of computational science and engineering is continually evolving, with the challenge of high-dimensional regression problems standing as a significant hurdle in numerous scientific endeavors. Addressing this challenge, our research, funded by this award, has led to the development of an innovative computational framework known as Probabilistic Partition of Unity Networks (PPOU-Nets). This initiative represents a collaborative effort to harness the potential of mathematics and physics-informed machine learning in tackling multiscale and multiphysics problems prevalent in high-dimensional spaces. Through this work, we have proposed a novel methodology that seamlessly integrates adaptive dimensionality reduction and a mixture of experts model, thereby facilitating a more efficient and accurate approximation of complex functions. This research effort has not only advanced the state of computational science but also opened new avenues for exploration in quantum computing and beyond. This report outlines the motivation, methodology, key findings, and implications of our work, underscoring our contributions to the broader scientific community and the potential pathways for future research.

97 MATHEMATICS AND COMPUTING↗

Energetic Insights into the Role of Quaternary Ammonium Cations in Zeolite Synthesis

The thermodynamics of partitioning of an organic structure-directing agent (OSDA) between water and an organic solvent such as chloroform or trichloroethane serve as a proxy for energetic interactions during zeolite synthesis. Using several newly synthesized OSDAs, we have extended our earlier calorimetric and partitioning studies of the thermodynamics of transfer to separate effects of charge (C/N + ratio) and structure in a series of structurally related OSDAs. The Gibbs free energies of transfer are close to zero, resulting from a balance of strongly exothermic and relatively similar enthalpies and strongly negative and relatively similar entropies of transfer. There is no obvious correlation between the thermodynamics of transfer and the efficacy of a given OSDA in the zeolite synthesis. Finally, one must conclude that with bulk energetics of transfer being similar in most cases studied, the critical factors in OSDA function in zeolite synthesis are kinetically rather than thermodynamically controlled and arise from differences in activation energies related to details of OSDA structure and interactions during nucleation of possible zeolite precursors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

U-splines: Splines over unstructured meshes

U-splines are a novel approach to the construction of a spline basis for representing smooth objects in Computer-Aided Design (CAD) and Computer-Aided Engineering (CAE). A spline is a piecewise-defined function that satisfies continuity constraints between adjacent cells in a mesh. U-splines differ from existing spline constructions, such as Non-Uniform Rational B-splines (NURBS), subdivision surfaces, T-splines, and hierarchical B-splines, in that they can accommodate local variation in cell size, polynomial degree, and smoothness simultaneously over more varied mesh configurations. Mixed cell types (e.g., triangle and quadrilateral cells in the same mesh) and T-junctions are also supported, although the continuity of interfaces with triangle and tetrahedral cells is limited in the present work. The U-spline algorithm introduces a new technique for using local null space solutions to construct basis functions for the global spline null space problem. The U-spline construction is presented for curves, surfaces, and volumes with higher dimensional generalizations possible. Lastly, a set of requirements are given to ensure that the U-spline basis is positive, forms a partition of unity, is complete, and is locally linearly independent.

42 ENGINEERING↗

A cohesive zone treatment for the material point method involving problems of large deformation and damage

A new algorithm is described that permits the use of cohesive zones in the material point method for problems involving large deformation and fracture. In contrast to previous cohesive zone implementations, this method does not utilize massless surface-element particles. Instead, cohesive tractions are computed using the shape function mappings from a reference grid configuration in combination with explicitly defined particle surface normals and surface positions. These normals and relative surface positions are updated each time step according to particle deformation. The tractions are converted to cohesive forces using the nodal areas and mapped back to particles using the same reference shape function mappings. These forces are then remapped by conventional particle-to-grid interpolation as external forces using the current-configuration shape-function mappings. This allows highly compliant cohesive zones to function over jump displacements larger than a grid cell. Upon damage, these interfaces can revert to conventional multi-field contact surfaces. This approach is general and readily applies to two and three dimensions as well as being compatible with damage-field gradient partitioning offering exceptional computational flexibility. The framework for this method enables other capabilities, such as improved contact precision using explicitly defined surface normals and positions, and a method to mitigate spurious material damage at weak discontinuities between stiff brittle materials and soft or compliant materials.

Cohesive zone↗

Partitioning of Fe(II) in reduced nontronite (NAu-2) to reactive sites: Reactivity in terms of Tc(VII) reduction

Abstract Clay minerals impart important chemical properties to soils, in part, by virtue of changes in the redox state of Fe in their crystal structures. Therefore, measurement of Fe(III)/Fe(II) and partitioning of Fe(II) in different reactive sites in clay minerals (during biological and chemical Fe(III) reduction) is essential to understand their role and their relative reactivity in terms of reduction and immobilization of heavy metal contaminants such as technetium. This study had three objectives: (1) to understand the degree of dissolution of nontronite (Fe-rich smectite) as a result of chemical and biological reduction of Fe(III) in the structure; (2) to quantify partitioning of chemically and biologically produced Fe(II) into different reactive sites in reduced nontronite, including aqueous Fe 2+ , ammonium chloride-extractable Fe(II) (mainly from the ion-exchangeable sites, denoted as Fe ( II ) NH 4 Cl ${\rm{Fe}}{\left( {{\rm{II}}} \right)_{{\rm{N}}{{\rm{H}}_4}{\rm{Cl}}}}$ ), sodium acetate-extractable Fe(II) (mainly from the surface complexation sites, denoted as Fe(II) acetate ), and structural Fe(II) (denoted as Fe(II) str ); and (3) to evaluate the reactivity of these Fe(II) species in terms of Tc(VII) reduction. Chemical and biological reduction of Fe(III) in nontronite (NAu-2) was performed, and reduced nontronite samples with different extents of Fe(III) reduction (1.2–71%) were prepared. The extent of reductive dissolution was measured as a function of the extent of Fe(III) reduction. Our results demonstrated that chemically and biologically produced Fe(II) in NAu-2 may be accommodated in the NAu-2 structure if the extent of Fe(III) reduction is small (< ∼30%). When the extent of reduction was >∼30%, dissolution of nontronite occurred with a corresponding decrease in crystallinity of residual nontronite. The Fe(II) produced was available for partitioning into four species: Fe ( ab ) 2 + ${\rm{Fe}}_{\left( {{\rm{ab}}} \right)}^{2 + }$ , Fe(II) acetate , Fe ( II ) NH 4 Cl ${\rm{Fe}}{\left( {{\rm{II}}} \right)_{{\rm{N}}{{\rm{H}}_4}{\rm{Cl}}}}$ , and Fe(II) str . The increase in Fe(II) acetate during the early stages of Fe(III) reduction indicated that the Fe(II) released had the greatest affinity for the surface-complexation sites, but this site had a limited capacity (∼60 µmol of Fe(II)/g of NAu-2). The subsequent increase in Fe ( II ) NH 4 Cl ${\rm{Fe}}{\left( {{\rm{II}}} \right)_{{\rm{N}}{{\rm{H}}_4}{\rm{Cl}}}}$ indicated that the released Fe(II) partitioned into the exchangeable sites once the amount of Fe at the surface-complexation sites reached half of its maximum site capacity. The fraction of Fe(II) str decreased concomitantly, as a result of Fe(II) release from the NAu-2 structure, from 100% when the extent of Fe(III) reduction was <30% to nearly 65% when the extent of Fe(III) reduction reached 71%. The Fe(II) acetate and Fe(II) str exhibited greater reactivity in terms of Tc(VII) reduction than the Fe ( II ) NH 4 Cl ${\rm{Fe}}{\left( {{\rm{II}}} \right)_{{\rm{N}}{{\rm{H}}_4}{\rm{Cl}}}}$ . Clearly, the surface-complexed and structural Fe(II) are the desirable species when reduced clay minerals are used to reduce and immobilize soluble heavy metals in contaminated groundwater and soils. These results have important implications for understanding microbe—clay mineral interactions and heavy metal immobilization in clay-rich natural environments.

54 ENVIRONMENTAL SCIENCES↗

Asymmetric response of Amazon forest water and energy fluxes to wet and dry hydrological extremes reveals onset of a local drought-induced tipping point

Understanding the effects of intensification of Amazon basin hydrological cycling—manifest as increasingly frequent floods and droughts—on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest “tipping points”. Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001–2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015–2016 El Niño drought and La Niña 2008–2009 wet events. We found that the forest responded strongly to El Niño-Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration ( ET ) leading to large increases in sensible heat fluxes ( H ). Partitioning ET by an approach that assumes transpiration ( T ) is proportional to photosynthesis, we found that water stress-induced reductions in canopy conductance ( G s ) drove T declines partly compensated by higher evaporation ( E ). By contrast, the abnormally wet La Niña period gave higher T and lower E , with little change in seasonal ET . Both El Niño-Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet-season leaf area index. However, only during El Niño 2015–2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown of G s and significant leaf shedding). Drought-reduced T and G s , higher H and E , amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post-drought. In conclusion, identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin-scale threshold-crossing changes in forest energy and water cycling, leading to slow-down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states.

54 ENVIRONMENTAL SCIENCES↗

PCAfold 2.0—Novel tools and algorithms for low-dimensional manifold assessment and optimization

We describe an update to our open-source Python package, PCAfold, designed to help researchers generate, analyze and improve low-dimensional data manifolds. In the current version, PCAfold 2.0, we introduce novel tools and algorithms for assessing and optimizing low-dimensional manifolds. This includes a method that generates a “map” of local feature sizes that can help pinpoint researchers to problematic regions on a manifold. We introduce a novel cost function that characterizes the quality of a manifold topology with a single number. We develop two algorithms for feature selection based on principal component analysis (PCA) that use the cost function as an objective function to minimize. We introduce a quantity of interest (QoI)-aware dimensionality reduction strategy where data projections are computed using an artificial neural network and are directly optimized towards representing various projection-independent and projection-dependent QoIs. We also introduce an implementation of partition of unity networks (POUnets) for efficient reconstruction of QoIs from low-dimensional manifolds based on combining neural network classification with localized polynomial regression. Our software can be broadly applicable in all domains of science and engineering that aim to reduce data dimensionality, as well as in the fundamental research on representation learning.

97 MATHEMATICS AND COMPUTING↗

General field evaluation in high-order meshes on GPUs

Robust and scalable function evaluation at any arbitrary point in the finite/spectral element mesh is required for querying the partial differential equation solution at points of interest, comparison of solution between different meshes, and Lagrangian particle tracking. This is a challenging problem, particularly for high-order unstructured meshes partitioned in parallel with MPI, as it requires identifying the element that overlaps a given point and computing the corresponding reference space coordinates. Here, we present a robust and efficient technique for general field evaluation in large-scale high-order meshes with quadrilaterals and hexahedra. In the proposed method, a combination of globally partitioned and processor-local maps are used to first determine a list of candidate MPI ranks, and then locally candidate elements that could contain a given point. Next, element-wise bounding boxes further reduce the list of candidate elements. Finally, Newton’s method with trust region is used to determine the overlapping element and corresponding reference space coordinates. Since GPU-based architectures have become popular for accelerating computational analyses using meshes with tensor-product elements, specialized kernels have been developed to utilize the proposed methodology on GPUs. The method is also extended to enable general field evaluation on surface meshes. The paper concludes by demonstrating the use of the proposed method in various applications ranging from mesh-to-mesh transfer during r-adaptivity to Lagrangian particle tracking.

97 MATHEMATICS AND COMPUTING↗

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗

Metagenomics-resolved genomics provides novel insights into chitin turnover, metabolic specialization, and niche partitioning in the octocoral microbiome

Abstract Background The role of bacterial symbionts that populate octocorals (Cnidaria, Octocorallia) is still poorly understood. To shed light on their metabolic capacities, we examined 66 high-quality metagenome-assembled genomes (MAGs) spanning 30 prokaryotic species, retrieved from microbial metagenomes of three octocoral species and seawater. Results Symbionts of healthy octocorals were affiliated with the taxa Endozoicomonadaceae , Candidatus Thioglobaceae , Metamycoplasmataceae , unclassified Pseudomonadales , Rhodobacteraceae , unclassified Alphaproteobacteria and Ca. Rhabdochlamydiaceae . Phylogenomics inference revealed that the Endozoicomonadaceae symbionts uncovered here represent two species of a novel genus unique to temperate octocorals, here denoted Ca. Gorgonimonas eunicellae and Ca. Gorgonimonas leptogorgiae . Their genomes revealed metabolic capacities to thrive under suboxic conditions and high gene copy numbers of serine-threonine protein kinases, type 3-secretion system, type-4 pili, and ankyrin-repeat proteins, suggesting excellent capabilities to colonize, aggregate, and persist inside their host. Contrarily, MAGs obtained from seawater frequently lacked symbiosis-related genes. All Endozoicomonadaceae symbionts harbored endo-chitinase and chitin-binging protein-encoding genes, indicating that they can hydrolyze the most abundant polysaccharide in the oceans. Other symbionts, including Metamycoplasmataceae and Ca. Thioglobaceae , may assimilate the smaller chitin oligosaccharides resulting from chitin breakdown and engage in chitin deacetylation, respectively, suggesting possibilities for substrate cross-feeding and a role for the coral microbiome in overall chitin turnover. We also observed sharp differences in secondary metabolite production potential between symbiotic lineages. Specific Proteobacteria taxa may specialize in chemical defense and guard other symbionts, including Endozoicomonadaceae , which lack such capacity. Conclusion This is the first study to recover MAGs from dominant symbionts of octocorals, including those of so-far unculturable Endozoicomonadaceae , Ca. Thioglobaceae and Metamycoplasmataceae symbionts. We identify a thus-far unanticipated, global role for Endozoicomonadaceae symbionts of corals in the processing of chitin, the most abundant natural polysaccharide in the oceans and major component of the natural zoo- and phytoplankton feed of octocorals. We conclude that niche partitioning, metabolic specialization, and adaptation to low oxygen conditions among prokaryotic symbionts likely contribute to the plasticity and adaptability of the octocoral holobiont in changing marine environments. These findings bear implications not only for our understanding of symbiotic relationships in the marine realm but also for the functioning of benthic ecosystems at large.

59 BASIC BIOLOGICAL SCIENCES↗

Water aging and the quality of organic carbon sources drive niche partitioning of the active bathypelagic prokaryotic microbiome

Abstract Due to the scarcity of organic matter (OM) sources in the bathypelagic (1000–4000 m depth), prokaryotic metabolism is believed to be concentrated on particles originating from the surface. However, the structure of active bathypelagic prokaryotic communities and how it changes across environmental gradients remains unexplored. Using a combination of 16S rRNA gene and transcripts sequencing, metagenomics, and substrate uptake potential measurements, here we aimed to explore how water masses aging and the quality of OM influence the structure of the active microbiome, and the potential implications for community function. We found that the relative contribution of taxa with a free‐living lifestyle to the active microbiome increased in older water masses that were enriched in recalcitrant OM, suggesting that these prokaryotes may also play a substantial role in the bathypelagic metabolism of vast areas of the ocean. In comparison to particle‐associated prokaryotes, free‐living prokaryotes exhibited lower potential metabolic rates, and harbored a limited number of two‐component sensory systems, suggesting they have less ability to sense and respond to environmental cues. In contrast, particle‐associated prokaryotes carried genes for particle colonization and carbohydrate utilization that were absent in prokaryotes with a free‐living lifestyle. Consistently, we observed that prokaryotic communities inhabiting older waters displayed reduced abilities to colonize particles, and higher capabilities to use complex carbon sources, compared to communities in waters with a higher proportion of labile OM. Our results provide evidence of regionalization of the bathypelagic active prokaryotic microbiome, unveiling a niche partitioning based on the quality of OM.

Marine & Freshwater Biology↗

Predicting Excitation Energies of Twisted Intramolecular Charge-Transfer States with the Time-Dependent Density Functional Theory: Comparison with Experimental Measurements in the Gas Phase and Solvents Ranging from Hexanes to Acetonitrile

Electronically excited states characterized by intramolecular charge transfer play an essential role in many biological processes and optical devices. The ability to make quantitative ab initio predictions of the relative energetics involved is a challenging yet desirable goal, especially for large molecules in solution. In this work, we present a data set of 61 experimental measurements of absorption and emission processes, both in the gas phase and in solvents representing a broad range of polarities, which involve intramolecular charge transfer mediated by a nonzero, "twisted" dihedral angle between one or more donor and acceptor subunits. Among a variety of density functionals investigated within the framework of linear-response theory, the "optimally tuned" LRC-ωPBE functional, which utilizes a system-specific yet nonempirical procedure to specify the range-separation parameter, emerges as the preferred choice. For the entire set of excitation energies, involving changes in dipole moment ranging from 4 to >20 Debye, the mean signed and absolute errors are 0.02 and 0.18 eV, respectively (compared, e.g., to -0.30 and 0.30 for PBE0, 0.44 and 0.47 for LRC-ωPBEh, 0.83 and 0.83 for ωB97X-V). We analyze the performance of polarizable continuum solvation models available in Q-Chem that partition the solvent response into fast and slow time scales, and clear trends emerge when measurements corresponding to the four small 4-(dimethylamino)benzonitrile (DMABN)-like molecules and a charged species are excluded. We make the case that the large errors found only for small molecules in the gas phase and weak solvents cannot be expected to improve via the optimal tuning procedure, which enforces a condition that is exact only in the well-separated donor-acceptor limit, and present empirical evidence implicating the outsized importance for small donor-acceptor systems of relaxation effects that cannot be accounted for by the linear-response time-dependent density functional theory within the adiabatic approximation. Finally, we demonstrate the utility of the optimally tuned density functional approach by targeting the charge-transfer states of a large biomimetic model system for light-harvesting structures in Photosystem II.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of Improved Simulation of Precipitation on Evapotranspiration and Its Partitioning Over Land

Evapotranspiration (ET) is a key component of the global hydrological cycle, which is strongly modulated by the occurrence of different rainfall intensities. Global climate models (GCMs) commonly suffer from “too much light rain” and a negative bias in the ratio of transpiration (T) to ET (T/ET). It is unclear whether these biases are related. Here, in this work, we show that with the improved simulation of probability density functions of rainfall intensity by suppressing light-rain occurrence using a stochastic convection parameterization in the NCAR CESM1.2, the canopy T increases in tropical forests while evaporation from canopy interception and bare soil decreases. The simulated T/ET is increased by 2.5% globally and up to 8% regionally, primarily attributable to reduced fraction of wet leaves due to less frequent light rain despite its weak intensity. These results imply that excessive light rain is an important cause of the negative T/ET bias in GCMs.

54 ENVIRONMENTAL SCIENCES↗

Physical bioenergetics: Energy fluxes, budgets, and constraints in cells

Cells are the basic units of all living matter which harness the flow of energy to drive the processes of life. While the biochemical networks involved in energy transduction are well-characterized, the energetic costs and constraints for specific cellular processes remain largely unknown. In particular, what are the energy budgets of cells? What are the constraints and limits energy flows impose on cellular processes? Do cells operate near these limits, and if so how do energetic constraints impact cellular functions? Physics has provided many tools to study nonequilibrium systems and to define physical limits, but applying these tools to cell biology remains a challenge. Physical bioenergetics, which resides at the interface of nonequilibrium physics, energy metabolism, and cell biology, seeks to understand how much energy cells are using, how they partition this energy between different cellular processes, and the associated energetic constraints. In this work, we review recent advances and discuss open questions and challenges in physical bioenergetics.

59 BASIC BIOLOGICAL SCIENCES↗

Complete Initial Evaluation of Novel Complexants for Tc Holdback for Simplified Single Cycle Separations.

Management of technetium at the back end of nuclear fuel cycle is complicated by its unique physico-chemical character, but must be addressed to due to the environmental, storage and reprocessing challenges of this fission product. In a single-cycle scenario, the recovery and purification of uranium is particularly challenging due to the tendency of a pertechnetate anion to follow uranyl cation. This report summarizes initial studies directed towards finding the solution for technetium management. Two options for controlling technetium’s chemistry in solvent extraction scenarios were studied. Molecular recognition of pertechnetate by aqueous complexants based on guanidinium moieties was compared to redox manipulation of technetium using dihydrazide reagents. Solvent extraction, potentiometric and nuclear magnetic resonance spectroscopy studies were performed. The influence of guanidinium reagents on the liquid-liquid partitioning of technetium is less pronounced, relative to dihydrazides. Strong impact exerted by dihydrazides originates from the technetium-catalyzed decomposition of such compounds which reduces technetium to a tetravalent, non-extractable state. Although this route of technetium management is very effective the destruction of dihydrazides is undesirable. Guanidinium complexants show a more tempered influence on technetium. The effect on the liquid-liquid partitioning of pertechnetate is evident and likely guided by anion recognition due to ion-pair and hydrogen bond formation. Guanidiniums are stable in presence of technetium as evidenced by nuclear magnetic resonance studies. The steady state chemistry of guanidiniums identify this class of aqueous complexants as solid candidates for structure-function pertechnetate recognition studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Springtime Drought Shifts Carbon Partitioning of Recent Photosynthates in 10-Year Old Picea mariana Trees, Causing Restricted Canopy Development

Springtime bud-break and shoot development induces substantial carbon (C) costs in trees. Drought stress during shoot development can impede C uptake and translocation. This is therefore a channel through which water shortage can lead to restricted shoot expansion and physiological capacity, which in turn may impact annual canopy C uptake. We studied effects of drought and re-hydration on early season shoot development, C uptake and partitioning in five individual 10-year old Picea mariana [black spruce] trees to identify and quantify dynamics of key morphological/physiological processes. Trees were subjected to one of two treatments: (i) well-watered control or (ii) drought and rehydration. We monitored changes in morphological [shoot volume, leaf mass area (LMA)], biochemical [osmolality, non-structural carbohydrates (NSC)] and physiological [rates of respiration (R d ) and light-saturated photosynthesis ( A sat )] processes during shoot development. Further, to study functional compartmentalization and use of new assimilates, we 13 C-pulse labeled shoots at multiple development stages, and measured isotopic signatures of leaf respiration, NSC pools and structural biomass. Shoot water potential dropped to a minimum of −2.5 MPa in shoots on the droughted trees. Development of the photosynthetic apparatus was delayed, as shoots on well-watered trees broke-even 14 days prior to shoots from trees exposed to water deficit. R d decreased with shoot maturation as growth respiration declined, and was lower in shoots exposed to drought. We found that shoot development was delayed by drought, and while rehydration resulted in recovery of A sat to similar levels as shoots on the well-watered trees, shoot volume remained lower. Water deficit during shoot expansion resulted in longer, yet more compact (i.e., with greater LMA) shoots with greater needle osmolality. The 12 C: 13 C isotopic patterns indicated that internal C partitioning and use was dependent on foliar developmental and hydration status. Shoots on drought-stressed trees prioritized allocating newly fixed C to respiration over structural components. In conclusion, temporary water deficit delayed new shoot development and resulted in greater LMA in black spruce. Since evergreen species such as black spruce retain active foliage for multiple years, impacts of early season drought on net primary productivity could be carried forward into subsequent years.

54 ENVIRONMENTAL SCIENCES↗

Systematic discovery of new nano-scale metastable intermetallic eutectic phases in laser rapid solidified Aluminum-Germanium alloy

Laser surface remelting of as-cast Al-Ge eutectic alloy is shown to produce ultrafine lamellar eutectic morphology with interlamellar spacing refined up to ∼60 nm and composed of FCC Al solid solution and unusual Al x Ge y intermetallic phases that do not form during near-equilibrium solidification. The microstructures are characterized and analyzed using a combination of selected area electron diffraction, high-resolution scanning transmission electron microscopy, energy dispersive X-ray spectroscopy to obtain high-resolution elemental maps, and atomistic modeling using density functional theory followed by atomic-scale image simulation. Depending on the local solidification conditions, the crystallography of the Al x Ge y intermetallic phases in the eutectic microstructure is either monoclinic (C 2/c) or monoclinic (P 2 1 ), with high densities of defects in both cases. This is in sharp contrast to the as-cast alloys that showed nominally pure Al and Ge phases with significant solute partitioning and equilibrium FCC and diamond cubic crystal structures, respectively. Corresponding kinetic phase diagrams are proposed to interpret the evolution of nano-lamellar eutectic morphologies with equilibrium Al and metastable Al x Ge y phases, and to explain increased solid solubility in the Al phases manifested by precipitation of ultrafine clusters of Ge. Furthermore, the reasons for the formation of these metastable eutectics under laser rapid solidification are discussed from the perspective of the competitive growth criterion.

Al-Ge eutectic↗