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DOE OSTI2025

Sedimentation and shear-induced dynamics of spheroids in fluids with spatial viscosity variations

A generalized reciprocal theorem is used to relate the force and torque induced on a particle in an inertia-less fluid with small variation in viscosity to integrals involving Stokes flow fields and the spatial dependence of viscosity. These resistivity expressions are analytically evaluated using spheroidal harmonics and then used to obtain the mobility of the spheroid during sedimentation, and in linear flows, of a fluid with linear viscosity stratification. The coupling between the rotational and translational motion induced by stratification rotates the spheroid’s centerline, creating a variety of rotational and translational dynamics dependent upon the particle’s aspect ratio, κ, and the component of the stratification unit vector in the gravity direction, d g . Spheroids with 0.55 ⪅ κ ⪅ 2.0 exhibit the largest variety of settling behaviors. Interestingly, this range covers most microplastics and typical microorganisms. One of the modes include a stable orientation dependent only on κ and d g , but independent of initial orientation, thus allowing for the potential control of settling angles and sedimentation rates. In a simple shear flow, cross-streamline migration occurs due to the stratification-induced force generated on the particle. Similarly, a particle no longer stays at the stagnation point of a uniaxial extensional flow. While fully analytical results are obtained for spheroids, numerical simulations provide a source of validation. These simulations also provide additional insights into the stratification-induced force- and torque-producing mechanisms through the stratification-induced stress, which is not accessed in the reciprocal theorem-based analytical calculations.

Geophysical and Geological Flows: Stratified flows↗

DOE OSTI2021

An unstructured C-grid type variational formulation for the sea ice dynamics

Historically, B-grid formulations of sea ice dynamics have been dominant because they have matched the grid type used by ocean models. The reason for the grid match is simple – it facilitates penetration of the curl of ice-ocean stress into the deep ocean with minimal numerical diffusivity because sea ice and ocean velocity are co-located. In recent years, as ocean models have increasingly progressed to C-grids, sea ice models have followed suit on quadrilateral meshes, but the implementation of an unstructured C-grid sea ice models is new. We present an unstructured C-grid discretization of the Elastic Viscous Plastic (EVP) rheology, where the velocity unknowns are discretized at the edges of the mesh cells with n-sides, where typically n is greater than or equal to four, rather than at the vertices, as in the B-grid. Our framework of choice is the Model for Prediction Across Scales (MPAS) within E3SM, the climate model of the U.S. Department of Energy, although our approach is general and could be applied to other models as well. While MPAS-Seaice is currently defined on a B-grid, MPAS-Ocean runs on a C-grid, hence interpolation operators are heavily used when coupled simulations are performed. In this work, we describe a mathematical formulation to transition the dynamics of MPAS-Seaice to a C-grid, in order to ultimately facilitate the coupling with MPAS-Ocean and reduce numerical errors associated with this communication. Numerical results are reported to highlight the features of the method.

58 GEOSCIENCES↗

DOE OSTI2023

Fermentation‐mediated growth, signaling, and defense in plants

Summary While traditionally considered important mainly in hypoxic roots during flooding, upregulation of fermentation pathways in plants has recently been described as an evolutionarily conserved drought survival strategy, with acetate signaling mediating reprograming of transcription and cellular carbon and energy metabolism from roots to leaves. The amount of acetate produced directly correlates with survival through potential mechanisms including defense gene activation, biosynthesis of primary and secondary metabolites, and aerobic respiration. Here, we review root ethanolic fermentation responses to hypoxia during saturated soil conditions and summarize studies highlighting acetate fermentation under aerobic conditions coupled with respiration during growth and drought responses. Recent work is discussed demonstrating long‐distance transport of acetate via the transpiration stream as a respiratory substrate. While maintenance and growth respiration are often modeled separately in terrestrial models, here we propose the concept of ‘Defense Respiration’ fueled by acetate fermentation in which upregulation of acetate fermentation contributes acetate substrate for alternative energy production via aerobic respiration, biosynthesis of primary and secondary metabolites, and the acetylation of proteins involved in defense gene regulation. Finally, we highlight new frontiers in leaf‐atmosphere emission measurements as a potential way to study acetate fermentation responses of individual leaves, branches, ecosystems, and regions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient quantum well IR photodetectors

Metal halide perovskite (MHP) multiple quantum wells which consist of multilayers of alternate organic and inorganic layers exhibit large exciton binding energies due to the dielectric confinement between the inorganic and organic layers. These naturally formed multiple quantum wells have strong spin-orbit coupling (SOC) due to the presence of heavy elements in their crystal structures. Although the fundamental properties of 2D MHPs are far from being entirely understood, it is widely accepted that their band edge absorption coefficient results from strong exciton interactions. However, studies demonstrating how different exciton interactions and doping effects influence electronic traps and disorder on the band edge absorption coefficient of 2D MHPs have not been demonstrated. Understanding these interactions in MHPs will allow us to access low energy optical transitions for the fabrication of solution processable short-to-mid-wavelength IR photodetectors (1 – 8 μm). Moreover, upon doping, it is possible to move the Fermi energy into the conduction band (CB) to favorably promote the transport of charges in a working device. Herein, we study the development of 2D MHPs having strong SOC, high carrier mobility, and tunable quantum well structures. Our studies shed light on the design and modulation of fundamental physical phenomena by carefully elucidating the role of dopants (n-type and p-type), exciton heterogeneity, orientation, structure, and bias stress effects on the performance of MHPs as potential IR photodetectors.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Distinctive Pattern of Global Warming in Ocean Heat Content

Abstract Huge heat anomalies in the atmosphere and ocean in recent years are not yet explained. Strong characteristic patterns in temperatures for upper layers of the ocean occurred from 2000 to 2023 in the presence of global warming from increasing atmospheric greenhouse gases. Here, we show that the deep tropics are warming, although sharply modulated by El Niño–Southern Oscillation events, with strong heating in the extratropics near 40°N and 40°–45°S but little heating near 20°N and 25°–30°S. The heating is most clearly manifested in zonal-mean ocean heat content and is evident in sea surface temperatures. The strongest heating is in the Southern Hemisphere, where aerosol effects are small. Estimates are made of the contributions to heating of top-of-atmosphere (TOA) radiation, atmospheric energy transports, surface fluxes of energy, and redistribution of energy by surface winds and ocean currents. The patterns of change are not directly related to TOA radiation but are evident in net surface energy fluxes and inferred ocean heat transports, underscoring their coupled origin. Changes in the atmospheric circulation through a poleward shift in ocean jet streams and storm tracks are reflected in surface wind-driven ocean Ekman transports. As well as human-induced climate change, internal natural variability is likely in play. Hence, the atmosphere and ocean currents are systematically redistributing heat from global warming, profoundly affecting local climates. Significance Statement As the climate changes, it has been difficult to discern meaningful patterns. Distinctive patterns of change have occurred in the ocean when examined as zonal averages around latitude bands. Most excess heat from global warming resides in the ocean and, since 2005, has become focused into bands near 40°N and 40°S, with little net warming in the subtropics. The strongest warming is in the Southern Hemisphere, although sea surface temperatures have increased more in the Northern Hemisphere. Changes in the atmospheric circulation through a poleward shift in the jet stream and storm tracks are primarily responsible along with corresponding changes in ocean currents. These changes are linked through surface exchanges of energy via heat, moisture, and wind stress.

Trenberth, Kevin E. [National Center for Atmospher↗

DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

DOE OSTI2023

Low temperature absolute internal quantum efficiency of InGaN-based light-emitting diodes

A method to reveal low temperature absolute internal quantum efficiency of an InGaN-based light-emitting diode (LED) is reported. Structural (via scanning electron and atomic force microscopies, x-ray diffraction, and Raman spectroscopy) and optical (via temperature- and power-dependent photoluminescence) properties of InGaN-based blue LEDs are coupled with a channel-based recombination model, which reveals the low temperature absolute internal quantum efficiency of the LED on traditional sapphire and emerging Si (111) substrates as 27.5% and 71.1%, respectively. High low-temperature absolute internal quantum efficiency of the former is attributed to its lower defect density and less strain. Furthermore, our results show assuming perfect (i.e., 100%) internal quantum efficiency in an InGaN-based LED at low temperatures could be misleading, and using negative thermal quenching properties of defect luminesce bands with a channel-based recombination model can be a method to quantify LED's less than ideal low temperature internal quantum efficiencies.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Forecasting Tropical Annual Maximum Wet-Bulb Temperatures Months in Advance From the Current State of ENSO

Humid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet-bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TW max ). We develop a multiple linear regression model that explains 80% of variance in tropical mean TW max and significant regional TW max variances. The model considers warming trends and El Niño and Southern Oscillation indices. Looking ahead, the strong-to-very-strong El Niño at the end of 2023, with an Oceanic Niño Index of ~2.0, suggests a 2024 tropical land mean TW max of 26.2°C (25.9–26.4°C), and a 68% chance (24%–94%) of breaking existing records. This method also predicts regional TW max in specific areas.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Mediated Electrochemical Probing: A Systems-Level Tool for Redox Biology

Biology uses well-known redox mechanisms for energy harvesting (e.g., respiration), biosynthesis, and immune defense (e.g., oxidative burst), and now we know biology uses redox for systems-level communication. Currently, we have limited abilities to “eavesdrop” on this redox modality, which can be contrasted with our abilities to observe and actuate biology through its more familiar ionic electrical modality. In this Perspective, we argue that the coupling of electrochemistry with diffusible mediators (electron shuttles) provides a unique opportunity to access the redox communication modality through its electrical features. Here, we highlight previous studies showing that mediated electrochemical probing (MEP) can “communicate” with biology to acquire information and even to actuate specific biological responses (i.e., targeted gene expression). We suggest that MEP may reveal an extent of redox-based communication that has remained underappreciated in nature and that MEP could provide new technological approaches for redox biology, bioelectronics, clinical care, and environmental sciences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Mesoscale Design of Magnetoelectric Heterostructures and Nanocomposites

Multiferroic materials have a coexistence of at least two ferroic orders. The coupling interaction between the different order parameters can produce new phenomena, such as the magnetoelectric (ME) effect. The ME response is the appearance of an electric polarization P upon applying a magnetic field H, and/or vice versa. Magnetoelectricity has been observed as an intrinsic effect in some natural materials at low temperature; however, such single phase materials suffer from extremely weak ME exchange. Better alternatives are two-phase composites consisting of magnetostrictive and piezoelectric phases, which have been shown to have large ME coefficients. Said composites exploit a unique product ME tensor property that depends upon the individual strictions of the piezoelectric and magnetostrictive phases, the elastic stiffness and integrity of the interphase interfaces, the phase distribution and the dimensionality of its connectivity, and any elastic constraint; amongst other things. This research program between D. Viehland PI and S.Priya at Virginia Tech investigated the mesoscale physics and chemistry of such two-phase ME heterostructures. The results of the proposed research are relevant to new generations of multifunctional materials involving heterogeneous components. How the product ME property be optimized? The answers lies with the interphase-interfaces, where the atomic layers coordinate stress transfer from one phase to another. It was the primary goal of this research program to discover such fundamental relationship for two phase ME heterostructures and nanocomposites. This research program integrated all the components required to fully investigate the ME phenomenon: starting from synthesis of nanomaterials with diversified interfacial characteristics; to full electrical, magnetic, and structural characterizations.

36 MATERIALS SCIENCE↗

DOE OSTI2024

The EGS Collab project: Outcomes and lessons learned from hydraulic fracture stimulations in crystalline rock at 1.25 and 1.5 km depth

With the goal of better understanding stimulation in crystalline rock for improving enhanced geothermal systems (EGS), the EGS Collab Project performed a series of stimulations and flow tests at 1.25 and 1.5 km depths. The tests were performed in two well-instrumented testbeds in the Sanford Underground Research Facility in Lead, South Dakota, United States. The testbed for Experiment 1 at 1.5 km depth contained two open wells for injection and production and six instrumented monitoring wells surrounding the targeted stimulation zone. Four multi-step stimulation tests targeting hydraulic fracturing and nearly year-long ambient temperature and chilled water flow tests were performed in Experiment 1. The testbed for Experiments 2 and 3 was at 1.25 km depth and contained five open wells in an outwardly fanning five-spot pattern and two fans of well-instrumented monitoring wells surrounding the targeted stimulation zone. Experiment 2 targeted shear stimulation, and Experiment 3 targeted low-flow, high-flow, and oscillating pressure stimulation strategies. Hydraulic fracturing was successful in Experiments 1 and 3 in generating a connected system wherein injected water could be collected. However, the resulting flow was distributed dynamically, and not entirely collected at the anticipated production well. Thermal breakthrough was not observed in the production well, but that could have been masked by the Joule-Thomson effect. Shear stimulation in Experiment 2 did not occur - despite attempting to pressurize the fractures most likely to shear - because of the inability to inject water into a mostly-healed fracture, and the low shear-to-normal stress ratio. The EGS Collab experiments are described to provide a background for lessons learned on topics including induced seismicity, the correlation between seismicity and permeability, distributed and dynamic flow systems, thermoelastic and pressure effects, shear stimulation, local geology, thermal breakthrough, monitoring stimulation, grouting boreholes, modeling, and system management.

15 - GEOTHERMAL ENERGY↗

DOE OSTI2022

Analytical Modeling of Biomass Transport and Feeding Systems

The processing of biomass solids in a biorefinery consists of pretreatment, enzyme hydrolysis / concurrent fermentation of sugars to ethanol, product recovery, and drying. Sustainable operation requires a front end that transforms wet solids into a pumpable slurry. Otherwise the biorefinery will suffer unscheduled shut-downs and inefficient operation due to solids that obstruct pumps and other equipment and resist mixing in a bioreactor. Downtime in pioneer biorefineries due to interruptions from materials handling problems has been 50% or more, leading to unsustainable manufacturing processes. This work addresses new technology, predictive computational models, and definition of operational conditions that result in formation of slurries of corn stover at up to 300 g/L using low enzyme loadings (1 to 3 FPU cellulase/g) before the biomass (corn stover) enters the pretreatment step. A team of researchers from Purdue University, Idaho National Laboratory (INL), Forest Concepts, AdvanceBio, Argonne National Laboratory, and DOE BETO have combined their knowledge in agricultural and biological engineering, bioprocess engineering, mechanical engineering, chemical engineering, agricultural economics, materials engineering and enzyme and microbial technology to address the challenge of making lignocellulose flow. This team effort has resulted in the development and validation of conditions that employ low levels of commercial enzyme in an agitated bioreactor to which corn stover pellets are added resulting in formation of slurries at high solids loadings, before pretreatment. This approach overcomes challenges caused by handling of dry, particulate biomass materials at the front end of the biorefinery. The subsequent materials handling issues cause obstruction at pumps, pipes and valves. Formation of high loadings slurries with low yield stress, as reported here, significantly decreases the potential for process interruption and enhances plant operability. Key advances in the knowledge of how slurry formation occurs is reported here and in recently published journal papers. We found that pellets are needed to achieve high solids loading, and that commercial enzymes are effective in forming slurries of corn stover particles from pellets that have not been pretreated. Our work has resulted in models that predict solids behavior for formation of compressed solids and pellets that in turn facilitate slurries made of high concentrations of corn stover particles. A computational model was developed that gives mechanistic insights into properties of particles and mixing process that gives the slurry rheology needed to facilitate pumping. Hence, the corn stover may be pumped into a pretreatment reactor in place of auguring in solids against high pressure which is a root cause of interruptions at the front end of a biorefinery. Subsequent mixing in enzyme and microbial bioreactors results in conversion of lignocellulose to sugars in a biorefinery in agitated bioreactors, with flows in and out of the vessels being less likely to be interrupted due to plugging or materials handling problems. The obtained data coupled to process models, techno-economic assessment (TEA) and Life Cycle Analysis (LCA) were used to assess whether this approach is practical. These results are based on a foundation of laboratory characterization and pilot runs. The NREL biochemical sugar model was utilized to carry out techno-economic analysis of enzyme catalyzed liquefaction followed by enzyme hydrolysis. The minimum sugar selling price was between 17.5 and 18.3 ¢/pound or about the same as calculated by the NREL model for dilute acid pretreatment followed by enzyme hydrolysis. Life cycle analysis (LCA) based on Argonne’s Greet Model showed the enzyme catalyzed route had the lowest greenhouse gas emissions of the three combinations studied (i.e., enzyme, enzyme mimetic, and enzyme + mimetic combined). GHG emissions for enzyme-based corn stover liquefaction step, alone, were about 21 g CO 2 -equivalent/kg of liquefied slurry. We believe this approach will further enhance operability of a pioneer biorefinery, and bring large-scale conversion of lignocellulosic biomass to low carbon footprint biofuels closer to implementation.

09 BIOMASS FUELS↗

DOE OSTI2023

Bending-induced isostructural transitions in ultrathin layers of van der Waals ferrielectrics

Using Landau-Ginzburg-Devonshire (LGD) phenomenological approach we analyze the bending-induced re-distribution of electric polarization and field, elastic stresses and strains inside ultrathin layers of van der Waals ferrielectrics. We consider a CuInP2S6 (CIPS) thin layer with fixed edges and suspended central part, the bending of which is induced by external forces. The unique aspect of CIPS is the existence of two ferrielectric states, FI1 and FI2, corresponding to big and small polarization values, which arise due to the specific four-well potential of the eighth-order LGD functional. When the CIPS layer is flat, the single-domain FI1 state is stable in the central part of the layer, and the FI2 states are stable near the fixed edges. With an increase of the layer bending below the critical value, the sizes of the FI2 states near the fixed edges decreases, and the size of the FI1 region increases. When the bending exceeds the critical value, the edge FI2 states disappear being substituted by the FI1 state, but they appear abruptly near the inflection regions and expand as the bending increases. The bending-induced isostructural FI1-FI2 transition is specific for the bended van der Waals ferrielectrics described by the eighth (or higher) order LGD functional with consideration of linear and nonlinear electrostriction couplings. Furthermore, the isostructural transition, which is revealed in the vicinity of room temperature, can significantly reduce the coercive voltage of ferroelectric polarization reversal in CIPS nanoflakes, allowing for the curvature-engineering control of various flexible nanodevices.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Metabolic Redox Coupling Controls Methane Production in Permafrost‐Affected Peatlands Through Organic Matter Quality‐Dependent Energy Allocation

ABSTRACT Permafrost thaw represents one of Earth's largest climate feedback risks, potentially releasing vast carbon (C) stores as greenhouse gases (GHG). However, our ability to predict emissions remains limited by poor understanding of how changing organic matter (OM) composition affects microbial carbon processing. We test a metabolism‐centered redox framework, which views microbial processes as coupled oxidative‐reductive reactions, to mechanistically explain how organic matter metabolite quality controls greenhouse gas production in permafrost‐affected peatland ecosystems. Rather than relying solely on geochemical redox measurements, our approach examines how microbes balance electron flow through metabolic pathways. Using active layer peat (9–19 cm) from contrasting environments (bog and fen), we employed multi‐omics approaches, including metabolomics, metagenomics, and metatranscriptomics, to link OM chemistry to microbial function. Our results reveal distinct dissolved organic matter metabolite composition, with fen systems enriched in compounds with higher substrate quality (low molecular weight (MW) sugars with high H:C ratios and low aromaticity) and bog systems dominated by compounds with lower substrate quality (high MW phenols with lower H:C ratios and higher aromaticity). In fen samples, these sugar‐like compounds correlated with higher oxidative metabolism and methanogenesis, supported by increased glycolysis gene expression. Initially, electrons from increased oxidative metabolism were balanced through nitrate and sulfate reduction, but as these electron acceptors were depleted, methanogenesis increased to maintain redox balance. Fen samples showed rapid degradation of both high‐ and low‐substrate‐quality compounds, suggesting sufficient energy for efficient C cycling. Conversely, bog samples exhibited more polyphenolic compounds, lower glycolysis activity, and higher stress‐related gene expression, suggesting energy was diverted towards cell maintenance under acidic conditions rather than C processing. This approach suggests that predicting greenhouse gas emissions requires an understanding of how organic matter quality shapes microbial energy allocation strategies, providing a mechanistic framework for improving emission predictions from permafrost‐affected peatlands and similar ecosystems.

Biodiversity & Conservation↗

DOE OSTI2022

Leafweb: Dataset in Support of Coupled Modeling of Photophysics, Photochemistry, and Biochemistry of Photosynthesis, December 2022 Release

This data set contains measurements of leaf gas exchange and Pulse-Amplitude Modulated (PAM) fluorometry of light, carbon dioxide (CO2), oxygen (O2), and temperature responses from 26 C3 photosynthetic and four C4 photosynthetic species measured by independent researchers in Canada, China, Finland, Netherlands, and United States in the field, garden, or greenhouse. Data were collected between 1987 and 2021, however data for individual species only provide coverage over a few hours to one year. Species include three lianas, three shrubs, two boreal deciduous trees, two boreal evergreen needle-leaf tree, three temperate deciduous trees, four tropical deciduous trees, three tropical evergreen trees, one C3 grass, three C4 grasses, and six crop varieties. These measurements are conducted according to standard protocols in gas exchange (Long and Bernacchi 2003) and PAM fluorometry (Baker 2008). The Scots pine (Pinus sylvestris) dataset contains one-year continuous fluorometry observations made at intervals of 10 or 30 minutes in the field under natural environments using Walz monitoring PAM. Measurements from all other 29 species include simultaneous PAM fluorometry and gas exchange observations. Among these 29 species, seven species were measured with light response curves only (i.e., light intensity varied systematically with ambient CO2 concentration controlled at a constant level, e.g., 400 ppm). All the other 22 species were measured with both the light response and CO2 response (i.e., ambient CO2 concentration varied systematically with light intensity controlled at a constant level, e.g., 1200 µmolm-2s-1). For most species, measurements were made with temperature controlled at ~ 25 degrees Celsius (C) with the exceptions of Scots pine (natural diurnal and seasonal variations), tomato cultivar Basket Vee (~ 21 degrees C), and cotton which contained temperature stress experiments (9 to 40 degrees C). All measurements were made at ambient O2 concentration except for the tomato cultivar Basket Vee and cotton which used two O2 levels (2 and 21%) and rice and tomato cultivar Growdena which used five O2 levels (2, 10, 21, 35, and 50%). This dataset supports the complete modeling of photosynthesis at the leaf scale, including photophysical, photochemical, and biochemical reactions. It will support research in the applications of remotely sensed solar induced chlorophyll fluorescence and the responses of energy dissipation pathways to environmental variations across species and climates. This dataset contains 260 data files in comma separate (.csv) format contained inside 11 compressed (*.zip) files. Additional metadata are provided: one data dictionary, a species information table, and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

air temperature↗

DOE OSTI2026

Cascading economic losses from port disruptions under capacity constrained multimodal freight networks

This study quantifies how throughput disruptions at major seaports cascade through capacity-constrained multimodal freight networks and interregional production systems. We couple an agent-based model (ABM) multimodal freight simulation that resolves rerouting, terminal queueing, and inventory drawdown under binding modal and facility capacities with a multiregional output loss input-output (MRIIM) model that propagates realized delivery shortfalls across regions and sectors. The framework is demonstrated for the Port of Los Angeles using Freight Analysis Framework flows and Bureau of Economic Analysis input-output accounts and is evaluated over a 52-week horizon under deterministic sector targeted shocks and stochastic disruption realizations with uncertain severity and duration. Results indicate nonlinear amplification: realized national losses concentrate in manufacturing and transportation/warehousing even when exogenous port shocks are dispersed, suggesting that congestion spillback and limited short-run substitution can dominate the initial shock allocation. We further evaluate a tabular reinforcement-learning (Q-learning) intervention layer that selects among a small set of implementable system level levers (truck-to-rail and truck-to-barge shift settings) without overriding shipper routing, finding that such interventions reduce total losses for moderate disruptions but yield diminishing returns once substitute modes approach capacity. By linking operational freight behavior to system wide impacts under uncertainty, the proposed ABM-MRIIM pipeline provides a reusable workflow for port disruption stress testing, identification of structurally critical sectors/corridors, and evaluation of resilience interventions under realistic capacity limits.

42 ENGINEERING↗

DOE OSTI2026

Mechanical Behavior of Neutron Irradiated Refractory Multi-Principal Element Alloys Processed via Spark Plasma Sintering

The search for advanced materials capable of withstanding the extreme conditions of Generation IV reactors is a critical area in materials science research. These reactors operate under severe environments, including high temperatures, corrosion, stress, and irradiation damage. Consequently, there is a need for innovative alloy systems to ensure the reliability and longevity of proposed Generation IV reactor components. Refractory multi-principal-element alloys (RMPEA) have emerged as a promising candidate due to their exceptional properties. These alloys, characterized by their composition of multiple principal elements in near-equiatomic ratios, exhibit superior resistance to irradiation damage, reduced void swelling, enhanced microstructural stability, and minimal irradiation-induced hardening. While initial studies on RMPEAs have shown promising results, most research has been limited to thin films, nanocrystalline microstructures, and ion irradiation, which do not accurately represent the behavior of bulk materials. To address this gap, our research focused on the neutron irradiation of bulk RMPEAs. We aim to conduct comprehensive post-irradiation examinations (PIE) of RMPEAs irradiated at the Advanced Test Reactor at Idaho National Laboratory. The RMPEAs were synthesized using spark plasma sintering (SPS) with mechanically alloyed metallurgical powder. The RMPEA specimens are a MoNbTi alloy system with additions of -Zr, and -ZrV. Furthermore, PIE consisted of mechanical testing and advanced materials characterization. The mechanical testing consisted of sub-sized tensile testing, micro- and nano- indentation. Microstructural characterization included scanning electron microscopy and transmission electron microscopy. Mechanical testing coupled with advanced microscopy techniques provides insight into phase morphology and its effects on the mechanical properties of the RMPEA specimens. The results indicate that both pristine and irradiated RMPEA specimens exhibited brittle behavior during tensile testing, which can be attributed to their heterogeneous microstructure. The SPS manufacturing process did not include any post treatment, which resulted in a heterogeneous microstructure. Energy-dispersive X-ray spectroscopy revealed the presence of intermetallic such as laves phases within the microstructure. Specifically, Ti-rich precipitates were observed in the MoNbTi specimen, while Mo-rich precipitates were found in the MoNbTiZrV specimen. Nano-hardness testing of pristine samples showed that the laves phases exhibited higher hardness values compared to the matrix phase, suggesting that precipitate hardening is likely the dominant hardening mechanism in these specimens. The results from this work will be used to build a finite element model to predict mechanical behavior of future MPEA compositions. Thus, enabling for a streamlined approach to developing novel MPEAs for the nuclear industry.

36 - MATERIALS SCIENCE↗

DOE OSTI2022

How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections?

Abstract We present an intercomparison of a suite of high‐resolution downscaled climate projections based on a six‐member General Circulation Model (GCM) ensemble from Coupled Models Intercomparison Project (CMIP6). The CMIP6 GCMs have been downscaled using dynamical and statistical downscaling techniques based on two meteorological reference observations over the conterminous United States. We use the regional climate model, RegCM4, for dynamical downscaling, double bias correction constructed analogs method for statistical downscaling, and Daymet and Livneh datasets as the reference observations for statistical training and bias‐correction. We evaluate the performances of downscaled data in both historical and future periods under the SSP585 scenario. While dynamical downscaling improves the simulation of some performance evaluation indices, it adds an extra bias in others, highlighting the need for statistical correction before its use in impact assessments. Downscaled datasets after bias‐correction compare exceptionally well with observations. However, the choice of downscaling techniques and the underlying reference observations influence the hydroclimate characteristics of downscaled data. For instance, the statistical downscaling generally preserves the GCMs climate change signal but overestimates the frequency of hot extremes. Similarly, simulated future changes are sensitive to the choice of reference observations, particularly for precipitation extremes that exhibit a higher projected increase in the ensembles trained and/or corrected by Daymet than Livneh. Overall, these results demonstrate that multiple factors, including downscaling techniques and reference observations, can substantially influence the outcome of downscaled climate projections and stress the need for a comprehensive understanding of such method‐based uncertainties.

54 ENVIRONMENTAL SCIENCES↗