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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Characterizing Signatures of Geothermal Exploration Data with Machine Learning Techniques: An Application to the Nevada Play Fairway Analysis

We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Observational Assessment of Metocean Conditions in the WFIP3 Region

The WFIP3 project, sponsored by the U.S. Department of Energy, is aimed at improving our understanding of the physics of the atmosphere and ocean that dictate the structure and variability of the wind resource within the MABL. As part of the project, a long-term offshore field campaign will take place along the U.S. East Coast to provide an unprecedented characterization of the MABL in the vicinity of the Massachusetts/Rhode Island wind energy lease areas. The unprecedented observational data set collected in the WFIP3 field campaign will allow intensive numerical modeling development and validation efforts. To inform the field campaign design and the preliminary studies associated with it, here we perform a characterization of the MABL and ocean conditions by leveraging available observations in the region.

lidars↗
NASA NTRS2012

Missions to Near-Earth Asteroids: Implications for Exploration, Science, Resource Utilization, and Planetary Defense

Introduction: In 2009 the Augustine Commission identified near-Earth asteroids (NEAs) as high profile destinations for human exploration missions beyond the Earth-Moon system as part of the Flexible Path. More recently the U.S. presidential administration directed NASA to include NEAs as destinations for future human exploration with the goal of sending astronauts to a NEA in the mid to late 2020s. This directive became part of the official National Space Policy of the United States of America as of June 28, 2010. NEA Space-Based Survey and Robotic Precursor Missions: The most suitable targets for human missions are NEAs in Earth-like orbits with long synodic periods. However, these mission candidates are often not observable from Earth until the timeframe of their most favorable human mission opportunities, which does not provide an appropriate amount of time for mission development. A space-based survey telescope could more efficiently find these targets in a timely, affordable manner. Such a system is not only able to discover new objects, but also track and characterize objects of interest for human space flight consideration. Those objects with characteristic signatures representative of volatile-rich or metallic materials will be considered as top candidates for further investigation due to their potential for resource utilization and scientific discovery. Once suitable candidates have been identified, precursor spacecraft are required to perform basic reconnaissance of a few NEAs under consideration for the human-led mission. Robotic spacecraft will assess targets for potential hazards that may pose a risk to the deep space transportation vehicle, its deployable assets, and the crew. Additionally, the information obtained about the NEA's basic physical characteristics will be crucial for planning operational activities, designing in-depth scientific/engineering investigations, and identifying sites on the NEA for sample collection. Human Exploration Considerations: These missions would be the first human expeditions to interplanetary bodies beyond the Earth-Moon system and would prove useful for testing technologies required for human missions to Mars, Phobos and Deimos, and other Solar System destinations. Current analyses of operational concepts suggest that stay times of 15 to 30 days may be possible at a NEA with total mission duration limits of 180 days or less. Hence, these missions would undoubtedly provide a great deal of technical and engineering data on spacecraft operations for future human space exploration while simultaneously conducting detailed investigations of these primitive objects with instruments and equipment that exceed the mass and power capabilities delivered by robotic spacecraft. All of these activities will be vital for refinement of resource characterization/identification and development of extraction/utilization technologies to be used on airless bodies under low- or micro-gravity conditions. In addition, gaining enhanced understanding of a NEA s geotechnical properties and its gross internal structure will assist the development of hazard mitigation techniques for planetary defense. Conclusions: The scientific, resource utilization, and hazard mitigation benefits, along with the programmatic and operational benefits of a human venture beyond the Earth-Moon system, make a piloted sample return mission to a NEA using NASA s proposed human exploration systems a compelling endeavor.

Abell, P. A.↗
DOE OSTI2025

Advancing the Representation of Human Actions in Large‐Scale Hydrological Models: Challenges and Future Research Directions

Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human-water interactions in large-scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (~10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper-resolution” hydrological models (~0.1–1 km), multi-sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human-water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper-resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort.

catchment hydrology↗
DOE OSTI2019

From Lignin to Valuable Products–Strategies, Challenges, and Prospects

The exploration of effective approaches for the valorization of lignin to valuable products attracts broad interests of a growing scientific community. By fully unlocking the potential of the world’s most abundant resource of bio-aromatics, it could improve the profitability and carbon efficiency of the entire biorefinery process, thus accelerate the replacement of fossil resources with bioresources in our society. This review summaries the latest cutting-edge innovations of lignin chemical valorization with the focus on the aforementioned three key aspects.

lignin, biofuels↗
DOE OSTI2021

Asymptotic reversibility of thermal operations for interacting quantum spin systems via generalized quantum Stein’s lemma

Abstract For quantum spin systems in any spatial dimension with a local, translation-invariant Hamiltonian, we prove that asymptotic state convertibility from a quantum state to another one by a thermodynamically feasible class of quantum dynamics, called thermal operations, is completely characterized by the Kullback–Leibler (KL) divergence rate, if the state is translation-invariant and spatially ergodic. Our proof consists of two parts and is phrased in terms of a branch of the quantum information theory called the resource theory. First, we prove that any states, for which the min and max Rényi divergences collapse approximately to a single value, can be approximately reversibly converted into one another by thermal operations with the aid of a small source of quantum coherence. Second, we prove that these divergences collapse asymptotically to the KL divergence rate for any translation-invariant ergodic state. We show this via a generalization of the quantum Stein’s lemma for quantum hypothesis testing beyond independent and identically distributed situations. Our result implies that the KL divergence rate serves as a thermodynamic potential that provides a complete characterization of thermodynamic convertibility of ergodic states of quantum many-body systems in the thermodynamic limit, including out-of-equilibrium and fully quantum situations.

Physics↗
DOE OSTI2021

Event-Based Analysis of Solar Power Distribution Feeder Using Micro-PMU Measurements

Solar distribution feeders are commonly used in solar farms that are integrated into distribution substations. In this paper, we focus on a real-world solar distribution feeder and conduct an event-based analysis by using micro-PMU measurements. The solar distribution feeder of interest is a behind-the-meter solar farm with a generation capacity of over 4 MW that has about 200 low-voltage distributed photovoltaic (PV) inverters. The event-based analysis in this study seeks to address the following practical matters. First, we conduct event detection by using an unsupervised machine learning approach. For each event, we determine the event’s source region by an impedancebased analysis, coupled with a descriptive analytic method. We segregate the events that are caused by the solar farm, i.e., locallyinduced events, versus the events that are initiated in the grid, i.e., grid-induced events, which caused a response by the solar farm. Second, for the locally-induced events, we examine the impact of solar production level and other significant parameters to make statistical conclusions. Third, for the grid-induced events, we characterize the response of the solar farm; and make comparisons with the response of an auxiliary neighboring feeder to the same events. Fourth, we scrutinize multiple specific events; such as by revealing the dynamics to the control system of the solar distribution feeder. The results and discoveries in this study are informative to utilities and solar power industry.

14 SOLAR ENERGY↗
DOE OSTI2024

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2

The project Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2 is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Los Angeles Basin presents an opportunity for large-scale geologic CO2 storage. Due to its large population and historical and geologic setting as one of the most prolific oil and gas producing basins in the United States, the region is home to more than 12 major power plants and oil refineries that produce more than 5 million metric tons of fossil fuel-related CO2 emissions each year. GeoMechanics Technologies worked to characterize the Pliocene and Miocene sediments in the Wilmington Graben, offshore of Los Angeles, California, for high-volume CO2 storage. The Graben is located offshore of the Los Angeles and Long Beach Harbor area, making it accessible yet geologically isolated from the nearby Wilmington oilfield and onshore areas. These sediments span more than 5,000 feet of vertical interval with an estimated storage resource of more than 100 million metric tons of CO2. The project team analyzed and interpreted existing geologic data within the region, including detailed exploration well log data and 2-D and 3-D seismic data. New seismic lines were acquired to fill in current data gap areas and two new characterization wells were drilled and logged. This information was integrated with existing geologic interpretations for adjacent onshore areas to help characterize optimal areas for CO2 storage and seals to safely store CO2. Integrated 3-D geologic and geomechanical models for the Wilmington Graben were developed to simulate the fate and transport of injected CO2 in the subsurface and to assess risks. This project contributed to the understanding of injectivity, containment mechanisms, rate of dissolution and mineralization, and storage capacity of the Wilmington Graben and associated analogous basins. This effort also provided greater insight into the potential for offshore geologic formations to safely and permanently store CO2.

.las↗
DOE OSTI2025

Helium recovery system at IB3a

The increasing need for optimal and sustainable use of cryogenic resources to support Fermilab’s scientific mission has highlighted the necessity of improving the Laboratory’s helium management practices. An assessment of cryogenic test facilities identified the Technical Division’s Industrial Building 3a (IB3A) as a key site requiring upgrades to integrate a helium recovery system. The IB3A facility is essential for characterizing and testing superconductors, cables, and coils for various R&D projects, including the US High-Luminosity LHC Accelerator Upgrade Project (AUP), Mu2e, and other external collaborations. Currently, the facility relies on 500 L helium Dewars and vents the vaporized helium directly into the atmosphere, leading to significant helium loss. Given the non-renewable nature of helium, recovering and reusing this resource is critical for the sustainability of Fermilab’s operations. To address this challenge, a project has been initiated to connect IB3A to an existing helium purification station and refrigeration system located in another building via a dedicated pipeline pass over the roof of several buildings. This solution will enable the efficient capture of vented helium, its transfer to the purification station, and subsequent liquefaction for reuse in future operations. The project includes a detailed design phase, specifying the pipeline route, flow control mechanisms, and integration with the existing cryogenic infrastructure, followed by phased implementation and commissioning. By implementing this pipeline connection and upgrading IB3A, Fermilab aims to significantly reduce helium waste, lower operational costs, and align with its commitment to sustainability. This initiative provides a model for resource-efficient cryogenic operations and reinforces the Laboratory’s capacity to support its science mission for the long term.

Porwisiak, D. [Fermilab]↗
DOE OSTI2019

Highly Efficient Separation/Recycling Palladium(II) Ions from Aqueous Solutions by Silica Gel-Coated Graphene Oxide Modified with Mercapto Groups

The separation and recovery of precious metals from secondary resources is an extremely important and challenging task. Herein, a novel sorbent is successfully prepared by chemical grafting and utilized for the extraction and separation of Pd(II) ions from aqueous solutions. Various characterization techniques, including Fourier transform infrared spectroscopy, scanning electron microscopy, Brunauer–Emmett–Teller, X-ray photoelectron spectroscopy, and element analysis, are employed to study the structure, morphology, porous nature, and chemical composition of the as-prepared SiO{sub 2}@GO-SH nanocomposites. The adsorption of Pd(II) ions on the SiO{sub 2}@GO-SH can be described by the pseudo-second-order model and Langmuir isotherm model. The adsorption equilibrium has been attained within 90 min and the maximum adsorption capacity of 423.2 mg g{sup −1} was attained at pH 3.5 and T = 308 K. The results reveal that SiO{sub 2}@GO-SH exhibits an excellent adsorption performance towards Pd(II) ions. In addition, we have proposed the adsorption mechanism for Pd(II) ions on the SiO{sub 2}@GO-SH surface. The adsorption of Pd(II) in SiO{sub 2}@GO-SH is a chemisorption process, where partial adsorbed Pd(II) ions are reduced to Pd(0) by functional groups (-SH) in the SiO{sub 2}@GO-SH. The results indicate that SiO{sub 2}@GO-SH can serve as a promising sorbent for the efficient separation and recovery of palladium from the palladium-containing secondary resources.

36 MATERIALS SCIENCE↗
DOE OSTI2018

An open experimental database for exploring inorganic materials

The use of advanced machine learning algorithms in experimental materials science is limited by the lack of sufficiently large and diverse datasets amenable to data mining. If publicly open, such data resources would also enable materials research by scientists without access to expensive experimental equipment. Here, we report on our progress towards a publicly open High Throughput Experimental Materials (HTEM) Database (htem.nrel.gov). This database currently contains 140,000 sample entries, characterized by structural (100,000), synthetic (80,000), chemical (70,000), and optoelectronic (50,000) properties of inorganic thin film materials, grouped in >4,000 sample entries across >100 materials systems; more than a half of these data are publicly available. This article shows how the HTEM database may enable scientists to explore materials by browsing web-based user interface and an application programming interface. This paper also describes a HTE approach to generating materials data, and discusses the laboratory information management system (LIMS), that underpin HTEM database. Finally, this manuscript illustrates how advanced machine learning algorithms can be adopted to materials science problems using this open data resource.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Enabling Scalable VQE Simulation on Leading HPC Systems

Large-scale simulations of quantum circuits pose significant challenges, especially in the context of quantum chemistry, due to the number of qubits, circuit depth, and the number of circuits needed per problem. High-performance computing (HPC) systems offer massive computational capabilities that could help overcome these obstacles. We developed a high-performance quantum circuit simulator, called NWQ-Sim, and demonstrate its capability to simulate large quantum chemistry problems on NERSC's Perlmutter supercomputer. Integrating NWQ-Sim with XACC, we have executed QPE and VQE algorithms for downfolded quantum chemistry systems at unprecedented scales. Our work demonstrates the potential of leveraging HPC resources to advance quantum chemistry and other applications of near-term quantum devices.

Wang, Meng↗
DOE OSTI2023

DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This was done using two different approaches: one based on expert opinions, and one based on statistical learning. This GDR submission includes the datasets used to produce the statistical learning-based weights. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. The drawback is that, to apply these types of approaches, a dataset is needed. Therefore, we attempted to build comprehensive standardized datasets mapping anomalies in each exploration dataset to each component of each play. This data was gathered through a literature review focused on magmatic hydrothermal plays along with well-characterized areas where superhot or supercritical conditions are thought to exist. Datasets were assembled for all three play types, but the hydrothermal dataset is the least complete due to its relatively low priority. For each known or assumed resource, the dataset states what anomaly in each exploration dataset is associated with each component of the system. The data is only a semi-quantitative, where values are either high, medium, or low, relative to background levels. In addition, the dataset has significant gaps, as not every possible exploration dataset has been collected and analyzed at every known or suspected geothermal resource area, in the context of all possible play types. The following training sites were used to assemble this dataset: - Conventional magmatic hydrothermal: Akutan (from AK PFA), Oregon Cascades PFA, Glass Buttes OR, Mauna Kea (from HI PFA), Lanai (from HI PFA), Mt St Helens Shear Zone (from WA PFA), Wind River Valley (From WA PFA), Mount Baker (from WA PFA). - Superhot EGS: Newberry (EGS demonstration project), Coso (EGS demonstration project), Geysers (EGS demonstration project), Eastern Snake River Plain (EGS demonstration project), Utah FORGE, Larderello, Kakkonda, Taupo Volcanic Zone, Acoculco, Krafla. - Supercritical: Coso, Geysers, Salton Sea, Larderello, Los Humeros, Taupo Volcanic Zone, Krafla, Reyjanes, Hengill. **Disclaimer: Treat the supercritical fluid anomalies with skepticism. They are based on assumptions due to the general lack of confirmed supercritical fluid encounters and samples at the sites included in this dataset, at the time of assembling the dataset. The main assumption was that the supercritical fluid in a given geothermal system has shared properties with the hydrothermal fluid, which may not be the case in reality. Once the datasets were assembled, principal component analysis (PCA) was applied to each. PCA is an unsupervised statistical learning technique, meaning that labels are not required on the data, that summarized the directions of variance in the data. This approach was chosen because our labels are not certain, i.e., we do not know with 100% confidence that superhot resources exist at all the assumed positive areas. We also do not have data for any known non-geothermal areas, meaning that it would be challenging to apply a supervised learning technique. In order to generate weights from the PCA, an analysis of the PCA loading values was conducted. PCA loading values represent how much a feature is contributing to each principal component, and therefore the overall variance in the data.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Cell type-resolved human lung lipidome reveals cellular cooperation in lung function

Cell type-resolved proteome analyses of the brain, heart and liver have been reported, however a similar effort on the lipidome is currently lacking. Here we applied liquid chromatography-tandem mass spectrometry to characterize the lipidome of major lung cell types isolated from human donors, representing the first lipidome map of any organ. We coupled this with cell type-resolved proteomics of the same samples (available at Lungmap.net). Complementary proteomics analyses substantiated the functional identity of the isolated cells. Lipidomics analyses showed significant variations in the lipidome across major human lung cell types, with differences most evident at the subclass and intra-subclass (i.e. total carbon length of the fatty acid chains) level. Further, lipidomic signatures revealed an overarching posture of high cellular cooperation within the human lung to support critical functions. Our complementary cell type-resolved lipid and protein datasets serve as a rich resource for analyses of human lung function.

Kyle, Jennifer E.↗
NASA NTRS2016

Additive Manufacturing and Characterization of Polylactic Acid (PLA) Composites Containing Metal Reinforcements

Additive manufacturing of polymeric systems using 3D printing has become quite popular recently due to rapid growth and availability of low cost and open source 3D printers. Two widely used 3D printing filaments are based on polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS) systems. PLA is much more environmentally friendly in comparison to ABS since it is made from renewable resources such as corn, sugarcane, and other starches as precursors. Recently, polylactic acid-based metal powder containing composite filaments have emerged which could be utilized for multifunctional applications. The composite filaments have higher density than pure PLA, and the majority of the materials volume is made up of polylactic acid. In order to utilize functionalities of composite filaments, printing behavior and properties of 3-D printed composites need to be characterized and compared with the pure PLA materials. In this study, pure PLA and composite specimens with different metallic reinforcements (Copper, Bronze, Tungsten, Iron, etc) were 3D printed at various layer heights and resulting microstructures and properties were characterized. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) behavior of filaments with different reinforcements were studied. The microscopy results show an increase in porosity between 3-D printed regular PLA and the metal composite PLA samples, which could produce weaker mechanical properties in the metal composite materials. Tensile strength and fracture toughness behavior of specimens as a function of print layer height will be presented.

brass↗
DOE OSTI2021

Plant single-cell solutions for energy and the environment

Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species’ cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Contrasting Mixotrophic Lifestyles Reveal Different Ecological Niches in Two Closely Related Marine Protists

Many marine microbial eukaryotes combine photosynthetic with phagotrophic nutrition, but incomplete understanding of such mixotrophic protists, their functional diversity, and underlying physiological mechanisms limits the assessment and modeling of their roles in present and future ocean ecosystems. We developed an experimental system to study responses of mixotrophic protists to availability of living prey and light, and used it to characterize contrasting physiological strategies in two stramenopiles in the genus Ochromonas . We show that oceanic isolate CCMP 1393 is an obligate mixotroph, requiring both light and prey as complementary resources. Interdependence of photosynthesis and heterotrophy in CCMP 1393 comprises a significant role of mitochondrial respiration in photosynthetic electron transport. In contrast, coastal isolate CCMP 2951 is a facultative mixotroph that can substitute photosynthesis by phagotrophy and hence grow purely heterotrophically in darkness. In contrast to CCMP 1393, CCMP 2951 also exhibits a marked photoprotection response that integrates non‐photochemical quenching and mitochondrial respiration as electron sink for photosynthetically produced reducing equivalents. Facultative mixotrophs similar to CCMP 2951 might be well adapted to variable environments, while obligate mixotrophs similar to CCMP 1393 appear capable of resource efficient growth in oligotrophic ocean environments. Thus, the responses of these phylogenetically close protists to the availability of different resources reveals niche differentiation that influences impacts in food webs and leads to opposing carbon cycle roles.

Marine & Freshwater Biology↗
DOE OSTI2026

Modelling belowground plant acclimation to low soil nitrogen – a heuristic optimality-based approach

Increased root growth to access greater soil mineral nitrogen resources and increased root exudation to stimulate microbial mineralization of soil organic nitrogen are widely observed plant acclimations to nitrogen limitation. However, their quantitative contribution to plant growth and ecosystem productivity remains largely elusive. Here, we present a novel optimality-based eco-evolutionary model in which plants dynamically regulate carbon partitioning between root growth and exudation to maximize their aboveground growth. Our simulations indicated that the availability of soil mineral and organic nitrogen as well as plant nitrogen demand and nitrogen uptake capacity shape optimal carbon partitioning between root growth and exudation. The simulated carbon allocation patterns aligned with empirical studies on belowground plant responses to varying soil nitrogen resources. Our eco-evolutionary approach represents a paradigmatic change in modelling plant nitrogen foraging, which is essential to generate hypotheses on optimal plant acclimation in future soil environments characterized by more erratic nitrogen availability.

Chakrawal, Arjun (ORCID:0000000345724347)↗