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243 records · Page 11

Plasma flow generation and particle acceleration from expanding magnetic bubbles

Impulsive plasma dynamics in the laboratory are often driven by rising electric currents, yet their quantitative plasma response has not been well established. By means of fully kinetic particle-in-cell simulations and laser-driven capacitor-coil experiments, we show that a rising current expels plasma, forming an expanding magnetic bubble and accelerating particles. The expansion front velocity scales with the Alfvén speed determined by the magnetic field at its inner edge and the plasma density at its outer edge. This mechanism establishes impulsive current drive as a fundamental way that generates plasma flows and accelerates particles in laboratory plasmas, with potential relevance to astrophysics.

Zhang, Yang [Princeton University, NJ (United Stat

Tokamak Energy’s pre-concept design for a fusion power plant: an overview of ST-E1

Climate change and rapidly rising energy demand, driven in part by artificial intelligence and data-centre growth, create an urgent need for stable, low-carbon, and abundant power. Fusion is a promising long-term solution, yet its commercialisation faces a fundamental paradox in today’s investment environment: pilot plants are essential to de-risk physics, engineering, and operations, but their limited lifetime energy output and high upfront costs make them difficult to finance. This paper presents Tokamak Energy’s response: ST-E1, a pre-concept design for a low-aspect-ratio tokamak power plant engineered specifically to overcome this challenge. ST-E1 is designed from the outset for phased operation—pilot and commercial phases, with an upgrade phase in between—with emphasis on commercial viability, maintainability, nuclear engineering, modularity, and upgradability. A key design principle is the deliberate separation of long-lived assets, such as the magnet cage and vacuum vessel, from replaceable in-vessel systems. This provides an attractive and credible investment approach to generate operational data and de-risk key technologies while preserving most capital-intensive assets for later commercial phases. The architecture supports continuous optimisation toward high net electric power (targeting 800–1000 MW net electric), a normalised capital expenditure of $\$$ 12–14k/kW of net electric power, and high availability (targeting > 80%). A tokamak core with a 5 m major radius, aspect ratio of 2.3, and on-plasma axis toroidal field of 5.25 T was selected to meet these objectives. This paper summarises the ST-E1 design philosophy, principal features, and development methodology. It introduces a Focus Collection of 11 papers detailing the pre-concept design of the entire tokamak and corresponding plant.

ST-E1

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry

Mitigation of polysulfide shuttle effect in Li-S batteries through catalytic disproportionation reaction

Polysulfides are poorly retained within porous cathodes and readily diffuse into the electrolyte over time, leading to the well-known shuttle effect that undermines the reversibility of Li-S batteries. Here, in this study, we demonstrate that catalytic disproportionation of polysulfides provides an effective pathway to suppress this process by rapidly converting dissolved species into solid sulfur and sulfides, thereby preventing their migration into the electrolyte. Fundamentally, the sluggish kinetics of sulfur redox reactions are responsible for the accumulation and redistribution of soluble polysulfides in the bulk electrolyte. By accelerating these kinetics, catalyzed disproportionation not only confines sulfur within the conductive cathode matrix but also promotes the homogeneous precipitation of Li₂S₂/Li₂S, which enhances electrochemical reversibility and cycling stability. Using nitrogen-doped carbon (NC800) as a model catalyst, we reveal its ability to drive a pseudo-16-electron reduction pathway, leading to a single dominant Li₂S product and uniform deposition within the porous framework. In contrast, a non-catalytic carbon (KB) yields multiple polysulfide intermediates and heterogeneous deposition. The mechanistic insights provided here highlight the pivotal role of catalytic disproportionation in reshaping sulfur redox pathways and offer a rational strategy for mitigating polysulfide shuttling in practical Li-S pouch cells.

25 ENERGY STORAGE

A comparison of wrought and powder metallurgical FeCrAl claddings under simulated LWR accident transients

Iron-chromium-aluminum (FeCrAl) alloys are potential accident tolerant fuel (ATF) cladding candidates for light-water reactors but are difficult to fabricate as thin-walled tubes via conventional cast-and-wrought routes. Powder metallurgy (PM) offers a manufacturing alternative with improved compositional control, but its transient accident performance has not been directly benchmarked against wrought variants. This study evaluates the burst behavior of commercially developed PM-processed FeCrAl alloys, PM-C26M (Fe-12Cr-6Al-2Mo) and the high precipitate density FA-SMT (Fe-22Cr-5Al-3Mo), under simulated light-water reactor accident transient conditions. Burst testing was conducted using the Severe Accident Test Station with heating rates of 5 °C/s and 50 °C/s and internal pressures ranging from 25 MPa to 100 MPa. PM-C26M reproduced wrought C26M burst behavior within 7–37 °C across the stress range, indicating that PM processing does not compromise transient strength. FA-SMT exhibited markedly higher burst temperatures and reduced heating-rate sensitivity, consistent with its engineered precipitate strengthening. FA-SMT rupture exhibited axial "unzipping" rather than the lateral tearing characteristic of PM- and wrought C26M. Post-test EBSD and fractography indicate that this behavior is strongly correlated with strain-gated intergranular void nucleation associated with the dense precipitate architecture of FA-SMT, a response absent in the comparatively clean PM-C26M matrix and consistent with rupture morphologies reported for oxide-dispersion strengthened (ODS) FeCrAl of similar base-matrix chemistry to PM-C26M. These findings highlight the potential of powder metallurgy as a viable fabrication route for ATF claddings from an accident performance standpoint.

Bell, Sam [ORNL] (ORCID:0000000251905657)

Automated scanning probe microscopy of combinatorial ferroelectric libraries: Gaussian-process-guided exploration and noise-aware experiment planning

Combinatorial materials libraries provide an efficient route for mapping composition–property relationships, but their broader impact depends on rapid, quantitative, and functionally relevant characterization. Scanning Probe Microscopy (SPM), including piezoresponse force microscopy (PFM), offers significant potential for quantitative, functionally relevant combi-library readouts. Here, we implement a fully automated SPM workflow for ferroelectric combinatorial libraries and benchmark Gaussian-process-based Bayesian optimization strategies for autonomous experiment planning. The workflow integrates automated probe motion, contact optimization, imaging, and dual amplitude resonance tracking-PFM spectroscopy, and uses scalarized spectroscopic observables to guide subsequent measurements. Stage motion, probe engagement, in-contact tuning, imaging, spectroscopy, and the choice of the next measurement location all proceed without human input. We demonstrate the approach on Sm-doped BiFeO 3 and Zn x Mg 1−x O libraries. By comparing vanilla Bayesian optimization with a measured-noise variant, we show that explicit treatment of local reproducibility can improve modeling of composition-dependent response when the measured variance is physically meaningful, but can also reduce robustness when variability is dominated by outliers or topographic artifacts. Furthermore, these results establish automated SPM as a bridge between combinatorial synthesis and quantitative functional characterization.

Liu, Yu [University of Tennessee, Knoxville, TN (U

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Preliminary Evaluation of Joint Electricity-Hydrogen Concept of Operations

An initial thermal power dispatch (TPD) concept of operations was evaluated that couples a nuclear power plant to a nearby hydrogen production plant. GSE Systems’ generic pressurized water reactor full-scope simulator was modified with a TPD model comprised of a thermal power extraction and delivery system. A prototype human-system interface (HSI) was developed to interact with the TPD model and allow participants to execute the basic operating scenarios for normal operations. Four retired operators performed the evaluation, and due to COVID-19 travel restrictions, the original in-person experimental design was restructured to support a remote participator evaluation using a web meeting platform. Data from operator feedback, observations from the research team, and quantitative survey responses revealed that the initial TPD concept of operations is feasible. The operators were comfortable with the engineered system and HSI and could manage it without adverse impacts to reactor power, plant safety, or equipment. Findings are discussed in terms of both the TPD system design and HSI performance.

human factors

Photosynthetic capacity is reduced by warming but unaffected by elevated CO2 in seedlings of five boreal tree species

Abstract Increasing atmospheric CO2 concentrations fuel global warming, with boreal regions warming at a faster rate than many other areas. Boreal forests are an important component of the global carbon cycle, yet we have little data on photosynthetic responses of boreal trees to elevated CO2 (EC) and warming. We grew seedlings of 5 widespread North American boreal tree species (from Betula, Larix, Picea, and Pinus) under current (410 ppm) or elevated (750 ppm) CO2 and either ambient (+0 °C) or increased (+4 °C or +8 °C) temperature, then measured photosynthetic traits over a range of leaf temperatures. Our results were generally consistent across species: photosynthetic capacity (maximum rates of Rubisco carboxylation, Vcmax, and electron transport, Jmax) was unaffected by EC but decreased under +8 °C warming. Accordingly, net photosynthesis measured at the growth CO2 concentration (Agrowth) was reduced under warming and increased under EC. The thermal optimum for Agrowth (ToptA) increased by ∼1.8 °C with EC but increased with warming in only two species. In contrast, the activation energies and thermal optima for Vcmax and Jmax, which are used to estimate photosynthesis in Earth System Models, were unaffected by growth environment. There were a few interactions between growth, CO2, and warming. These results suggest increased photosynthesis of widespread boreal tree species under EC may be offset by future reductions in photosynthetic capacity related to warming. We also show that the temperature sensitivities of parameters used to estimate global photosynthesis in large-scale models are generally unaffected by simulated climate change in these species.

Plant Sciences

Nuclear Safety [Vol. 37, No. 2, April-June 1996]

Nuclear Safety is a journal that covers significant issues in the field of nuclear safety. Its primary scope is safety in the design, construction, operation, and decommissioning of nuclear power reactors worldwide and the research and analysis activities that promote this goal, but it also encompasses the safety aspects of the entire nuclear fuel cycle, including fuel fabrication, spent-fuel processing and handling, and nuclear waste disposal, the handling of fissionable materials and radioisotopes, and the environmental effects of all these activities. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 97 The Nuclear Community and the Public: Cognitive and Cultural Influences on Thinking About Nuclear Risk, M. A. Meyer; 109 Twenty-Third Water Reactor Safety Information Meeting, D. A. Copinger; ACCIDENT ANALYSIS: 126 Analysis of a PWR LBLOCA Without SCRAM, Trevor N. Tyler, Rafael Macian-Juan and John H. Mahaffy; DESIGN FEATURES: 139 Vulnerability of Multiple-Barrier Systems, N. C. Lind; ENVIRONMENTAL EFFECTS: 149 A Study of Wet Catalytic Oxidation of Radioactive Spent Ion Exchange Resin by Hydrogen Peroxide, Xingchao Jian, Tianbao Wu, and Guichun Yun; 157 A Comparison Study and Resolution of Differences Between Emergency Response and Safety Analysis Codes Used at the Savannah River Site, A. A. Simpkins; OPERATING EXPERIENCES: 164 Reactor Shutdown Experience, Compiled by J. W. Cletcher; RECENT DEVELOPMENTS: 167 Reports, Standards, and Safety Guides, D. S. Queener; 172 Proposed Rule Changes as of Dec. 31,1995; ANNOUNCEMENTS: 178 American Nuclear Society 1997 Annual Meeting; 178 American Nuclear Society Nuclear Criticality and Safety Division Topical Meeting; 176 The Authors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Observed Land Surface Influence on Atmospheric Heat and Moisture Profiles During Interstorms

Land-atmospheric (L-A) feedbacks have historically been studied using models whose structure and parameterizations influence outcomes and insights. The representation of L-A feedbacks based on observations alone remains an ongoing challenge for understanding boundary layer development and precipitation. To address this gap, we use ground-based passive remote sensing and in-situ observations to present an analysis of the atmosphere during 103 interstorm soil moisture drydown events spanning nine warm seasons (2016–2024) in the U.S. Southern Great Plains region. By separating events based on local L-A coupling signals and characterizing the profiles of atmospheric heat and moisture to surface energy flux behavior, we investigate the physical mechanisms linking land surface processes to boundary layer development. We find that during interstorm drydowns, the atmospheric column follows a consistent pattern: moisture increases within the boundary layer, peaks near its top, and declines rapidly above, while warming occurs through the depth. Drydowns that shift toward evaporation produce stronger and deeper thermodynamic responses than cases dominated by sensible heating, which are weaker and shallower. Additionally, moisture is accumulated faster within the boundary layer during shorter drydowns, with longer drydowns representing slower, moisture-limited growth. Drydowns with wetter initial soil moisture will sustain stronger moistening within and above the boundary layer, accelerating buoyancy growth and convective potential toward the next storm. These results provide observational evidence linking surface flux evolution to boundary layer thermodynamics and offer a process-level benchmark for evaluating coupled L-A representations in models and demonstrating the influence of soil moisture on short-term weather forecasting skill.

Zhang, M. S. [Massachusetts Inst. of Technology (M

Maximizing dynamic range and performance of anatase TiO 2 ECRAM through structure and programming

Here, in this study, we investigate the structure-dependent modulation characteristics of all-solid-state three-terminal electrochemical random-access memory (ECRAM) based on an anatase Li x TiO 2 channel. By directly comparing “asymmetric” and “symmetric” ECRAM device architectures, we reveal significant insight into the impact of a non-zero gate-drain open-circuit voltage and its influence on voltage vs. current-controlled gating. We also explore the impact of potentiation/depression write parameters on the symmetry, linearity, and dynamic range of the device response. Together, initial results from optimizing structure and programming approaches yielded unprecedented G max /G min ratios of >1,000 for ECRAM and hundreds of tunable memory states with excellent linearity and symmetry. Simulations based on these ECRAM devices further illustrate the promise of this analog memory technology, achieving near 2% classification error in the MNIST digit recognition benchmark for a range of training parameters compared to a theoretical best of 1.66% and outperforming other device models extracted from the literature.

AIHWKit

Decorated Honeycomb Lattice and Successive Magnetic Transitions of the Delafossite Derivative K 4 Ni 5 Te 3 O 16

Here, we report the synthesis and characterization of the delafossite derivative K 4 Ni 5 Te 3 O 16 , which hosts a decorated honeycomb Ni 2+ lattice. Single-crystal X-ray diffraction, electron microscopy, and neutron diffraction establish a noncentrosymmetric Pmm2 crystal structure that combines regular honeycomb units with elongated motifs formed by Ni 2+ trimers along extended edges. Magnetic susceptibility reveals strong antiferromagnetic interactions, while heat capacity measurements identify two successive magnetic transitions at 30 and 12 K. Neutron diffraction shows that these transitions correspond to a progression from partial to full long-range magnetic order on distinct Ni sites, reflecting competition among the various exchange interactions. The resulting magnetic point group, mm2.1′, inherits the lattice polarity and permits high-order magnetoelectric coupling. Consistent with this symmetry, a quadratic magnetic-field-induced polarization is experimentally observed below the magnetic ordering temperature, likely arising from exchange-driven magnetostriction coupled to the polar lattice. These results establish K 4 Ni 5 Te 3 O 16 as an interesting platform for engineering B-site ordering in delafossite derivatives to realize complex quantum magnetism and functional responses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Asymmetric pathways for lithium extraction and recovery based on the two-phase equilibrium of layered oxides

Electrochemical intercalation offers a promising platform for Li + extraction. However, only limited types of electrode materials have been investigated. The challenge to broaden and tailor materials for electrochemical intercalation-based Li + extraction lies in the lack of understanding of material’s response upon co-intercalation of multiple ions, therefore, paired process design to enable reversible Li + extraction and recovery. Here, we showcase the design of asymmetric ion pathways for Li + extraction and recovery for host material with complex Li + and Na + interaction using layered cobalt oxide as a model material. The two-phase equilibrium of Na 0.48 CoO 2 and Li 0.94 CoO 2 governs Li + selectivity when a high depth of intercalation is achieved (low vacancy level). We show that the relative rate between ion exchange and intercalation is critical to determine the ion pathways. The relationship can be quantitatively compared using the average pseudo ion exchange rate (C pseudoIX ) and the intercalation rate (C inter ). The ion pathways at the three regimes with C pseudoIX > C inter , C pseudoIX ~ C inter , and C pseudoIX < C inter are constructed. By selecting the optimized ion pathway and particle size, we demonstrate 9.7×10 4 Li + selectivity with 99% purity Li + recovery from an initial 1:1000 Li: Na molar ratio solution using 115 mAh/g specific capacity.

electrochemistry

Conceptual design study of neutron detectors for safeguards measurement of an irradiated pebble

Nuclear material control and accounting (MC&A) of pebble-bed reactors (PBRs) is challenging because a PBR utilizes hundreds of thousands of identical, unmarked pebbles that are continuously recirculated through the core. To develop tools that enable the implementation of international safeguards, especially in the context of MC&A of spent pebbles, we designed and simulated three neutron detection concepts to determine fissile content in individual pebbles: a differential die-away (DDA) detector, a californium interrogation prompt neutron (CIPN) detector, and a passive neutron albedo reactivity (PNAR) detector using Monte Carlo calculations. Burnup calculations were performed on the spent pebbles from the PBMR-400 classic PBR. The varying neutron and gamma source terms, and isotopic compositions in the spent pebbles calculated at various burnup levels were used in the neutron detector models. DDA was found to be sensitive to the number of passes a pebble has had through the core and to the fissile content contained in a spent pebble. Optimization in the DDA design further increased the neutron count rates and thus reduced counting uncertainty. Meanwhile, passive neutron counting using the same detector body could distinguish pebbles with different numbers of passes, but its response was dominated by neutron-emitting actinides and was not sensitive to fissile content. On the other hand, the PNAR technique was not viable for a single pebble but performed reasonably for a 27-pebble array, which suggested potential use for verification measurements of containers filled with 27 or more spent pebbles.

CIPN

Decoupling the capacity fade contributions in polymer electrolyte-based high-voltage solid-state batteries

Polymer electrolyte (PE)-based solid-state batteries (PE-SSBs) made with high-voltage cathodes are known to suffer from severe capacity fade, stemming primarily from the poor oxidative stability of most PEs under high-voltage cycling conditions. PEs also suffer from greater ion-transport limitations compared to liquid or solid electrolytes. However, often, these limitations are collectively stated to be responsible for the observed capacity fade, and it is challenging to decouple the contributions of different factors. Herein, a tunable cell fabrication platform was developed to systematically investigate and decouple the two primary capacity fade drivers (cell impedance growth and kinetic limitations), while keeping the other cell parameters constant. Three PE types with distinct transport characteristics were compared. By utilizing a voltage profile analysis method, the contribution of the cell's internal impedance growth was quantitatively decoupled from the kinetic limitations stemming from the high concentration gradient in the polymer catholyte and slow charge transfer reactions. We demonstrate that the high interfacial impedance did not necessarily correlate with the high capacity fade rate. Kinetic limitations that are not reflected by impedance measurements can play a dominant role in causing cumulative capacity decay.

Ock, Ji-young [Oak Ridge National Laboratory (ORNL

Tradeoffs and Synergies in Tropical Forest Root Traits and Dynamics for Nutrient and Water Acquisition: Field and Modeling Advances

Vegetation processes are fundamentally limited by nutrient and water availability, the uptake of which is mediated by plant roots in terrestrial ecosystems. While tropical forests play a central role in global water, carbon, and nutrient cycling, we know very little about tradeoffs and synergies in root traits that respond to resource scarcity. Tropical trees face a unique set of resource limitations, with rock-derived nutrients and moisture seasonality governing many ecosystem functions, and nutrient versus water availability often separated spatially and temporally. Root traits that characterize biomass, depth distributions, production and phenology, morphology, physiology, chemistry, and symbiotic relationships can be predictive of plants’ capacities to access and acquire nutrients and water, with links to aboveground processes like transpiration, wood productivity, and leaf phenology. In this review, we identify an emerging trend in the literature that tropical fine root biomass and production in surface soils are greatest in infertile or sufficiently moist soils. We also identify interesting paradoxes in tropical forest root responses to changing resources that merit further exploration. For example, specific root length, which typically increases under resource scarcity to expand the volume of soil explored, instead can increase with greater base cation availability, both across natural tropical forest gradients and in fertilization experiments. Also, nutrient additions, rather than reducing mycorrhizal colonization of fine roots as might be expected, increased colonization rates under scenarios of water scarcity in some forests. Efforts to include fine root traits and functions in vegetation models have grown more sophisticated over time, yet there is a disconnect between the emphasis in models characterizing nutrient and water uptake rates and carbon costs versus the emphasis in field experiments on measuring root biomass, production, and morphology in response to changes in resource availability. Closer integration of field and modeling efforts could connect mechanistic investigation of fine-root dynamics to ecosystem-scale understanding of nutrient and water cycling, allowing us to better predict tropical forest-climate feedbacks.

54 ENVIRONMENTAL SCIENCES