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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Preparing large area of thermochromic nanocomposite films for smart window application

The challenges posed by high building energy bill necessitate proactive implementation of energy-efficient strategies to minimize the uses of both electricity and heating gas and promote the use of free solar energy sources. "Smart" window films/glass, leveraging thermochromic vanadium dioxide (VO 2 ), offer an adaptive approach to harness solar energy, significantly reducing the thermal load of buildings. This is achieved by reflecting the infrared portion of the solar spectrum through a phase transition in the monoclinic M-phase (M) of VO 2 induced by heating. In this study, a scalable continuous flow synthesis process invented by Argonne was employed to explore a wide parameter space, targeting the controlled synthesis of monoclinic VO 2 (M) nanoparticles with well-controlled sizes and morphologies. Additionally, a doping strategy and surface modifications were utilized for high-throughput tuning of the metal-to-insulator transition temperature. Strategies to enhance the solar modulation properties of VO 2 nanoparticles in polymer films were investigated through (i) morphological transformation from spherical to nanorod structures, (ii) surface modification with low refractive index ligands, and (iii) incorporation of additional thermochromic materials for improved solar energy modulation and aesthetically appealing colors in smart films. Furthermore, the study outlines scaling-up synthesis methods for VO 2 nanoparticles in a continuous flow reactor using hydrazine monohydrate. This comprehensive investigation provides valuable insights into the upscaling synthesis and design of advanced VO 2 /polymer composite smart window films with enhanced functionality, solar energy modulation and visible light transmittance, driving the technology a step close for industrial application.

14 SOLAR ENERGY↗
DOE OSTI2022

Autonomous Wireless Technology Detection in Seamless IoT Applications

The ever-increasing use of Internet of Things (IoT) devices results in the implementation of multiple wireless technologies that would not only cater their data rate requirements but also support various applications. To optimize the energy efficiency and security of the wireless transmission, it is imperative to identify the wireless technologies in various IoT implementations. Many of the existing approaches are based on measuring only the receiving signal strength indicator (RSSI). However, such approaches may not work well because of transmit power control and complex channel variations among different wireless technologies. In this article, we propose an autonomous wireless detection scheme that considers multiple distinguishable physical (PHY)-layer settings for real-time identification of wireless technologies for real-time applications. Specifically, the proposed scheme relies on the PHY-layer measurements of the targeted spectrum. Transmission settings, such as bandwidth, carrier frequency, and RSSI are estimated from the raw in-phase and quadrature-phase (I/Q) measurements. In addition, a symbol-level extraction scheme is implemented to extract unique features of modulation settings. These aforementioned features are applied to a machine learning process to identify the received wireless technologies. Compared with raw I/Q measurements, the extracted features are much simplified and, thus, the machine learning classifier can be designed with a simple structure for fast processing on IoT nodes. Finally, the proposed schemes are primarily evaluated theoretically, followed by implementing them on a USRP software-defined radio (SDR)-based hardware testbed. The evaluation results demonstrate high accuracy in the real-time detection of different wireless technologies for seamless IoT applications.

42 ENGINEERING↗
DOE OSTI2024

A Digital Twin Framework for Liquid-cooled Supercomputers as Demonstrated at Exascale

We present ExaDigiT, an open-source framework for developing comprehensive digital twins of liquid-cooled supercomputers. It integrates three main modules: (1) a resource allocator and power simulator, (2) a transient thermo-fluidic cooling model, and (3) an augmented reality model of the supercomputer and central energy plant. The framework enables the study of "what-if" scenarios, system optimizations, and virtual prototyping of future systems. Using Frontier as a case study, we demonstrate the framework's capabilities by replaying six months of system telemetry for systematic verification and validation. Such a comprehensive analysis of a liquid-cooled exascale supercomputer is the first of its kind. ExaDigiT elucidates complex transient cooling system dynamics, runs synthetic or real workloads, and predicts energy losses due to rectification and voltage conversion. Throughout our paper, we present lessons learned to benefit HPC practitioners developing similar digital twins. We envision the digital twin will be a key enabler for sustainable, energy-efficient supercomputing.

Brewer, Wes↗
DOE OSTI2025

Quasi-optical beam tracing module development for millimeter-wave high-wavenumber collective scattering on the NSTX-U and EAST tokamaks

A Python3-based beam tracing code utilizing Quasi-Optics has been developed to track both incident and receiving beams in high-k collective millimeter wave scattering systems within magnetic fusion plasmas. In contrast to existing ray tracing codes that solely consider refraction, this beam tracing code incorporates diffraction phenomena, providing a more comprehensive calculation. Here, this enhanced capability allows for a more accurate calculation of the scattering volume and spatial resolution in high-k collective scattering systems, crucial for evaluating system performance and facilitating data analysis. Unlike Geometrical Optics, Quasi-Optics employs the complex eikonal method, representing a Gaussian beam as a collection of coupled rays to accurately preserve diffraction characteristics. The developed code is intended for application in NSTX-Upgrade and EAST high-k beam tracing analyses, targeting frequencies of 693 GHz and 270 GHz, respectively. The high-k system's primary objective is the observation of electron-scale instabilities. Employing a symplectic integrator, the code ensures numerical accuracy, assessed through the conservation of the Hamiltonian. With its precision and efficiency, the code facilitates rapid inter-shot analyses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Ion‐Conducting, Electron‐Blocking Layer for High‐Performance Solid Electrolytes

Lithium metal batteries bring greater promise for energy density, often relying on solid‐state electrolytes to meet critical benchmarks. However, Li dendrite formation is a prevailing problem that limits the cycle life and Coulombic efficiency of solid‐state Li metal batteries. For the first time, a thin (<100 nm) layer of electronically insulating, ionically conducting lithium phosphorus oxynitride (LiPON) is applied using atomic layer deposition between a Li anode and garnet Li 7 La 3 Zr 2 O 12 (LLZO). The performance of a conformal LiPON layer as an electron barrier in symmetric Li‐LLZO cells is observed through potential step chronoamperometry, galvanostatic cycling, electron microscopy, and various spectroscopic techniques. The LiPON‐coated LLZO achieves 100 times lower electronic conductance than LLZO alone. Cycling carried out at 0.1 mA cm −2 for 100 cycles demonstrates that suppression of electron pathways into the bulk solid electrolyte improves the cycle life of a lithium metal cell. These findings suggest an electronic conductivity effect in solid‐state electrolytes. A strategy is demonstrated to design thin‐film (LiPON)‐modulated bulk solid‐state electrolytes (LLZO) capable of maintaining high ionic conductivity and electrochemical stability while reducing the effective electronic conductivity, which results in significantly decreased dendrite formation, improved cycle life, and greater interfacial integrity between the electrolyte and a Li anode.

Hitz, Emily M.↗
DOE OSTI2021

A comprehensive modeling method for proton exchange membrane electrolyzer development

Hydrogen attracts significant interests as an effective energy carrier that can be derived from renewable sources. Hydrogen production using a proton-exchange membrane (PEM) electrolyzer can efficiently convert renewable power via water splitting in wide scales—from large, centralized generation to on-site production. Mathematical models with multiple scales and fidelities facilitate the continuing improvements of PEM electrolyzer development to improve performance, cost, and reliability. The model scopes and methods are presented in this paper, which also introduces a comprehensive PEM electrolysis modeling tool based on computational fluid dynamics (CFD) software, ANSYS/Fluent. The modeling tool incorporates electrochemical model of a PEM electrolysis cell to simulate the performance of coupled thermal-fluid, species transport, and electrochemical processes in a product-scale cell or stack by leveraging the powerful meshing generation and CFD solver of ANSYS/Fluent. The thermal-fluid modeling includes liquid water/gas two-phase flow and simulates a PEM electrolysis cell by using Fluent user-defined functions as add-on modules accounting for PEM-specific species transport and electrochemical processes. The modeling outcomes expediate PEM electrolyzer scaling up from basic material development and laboratory testing.

08 HYDROGEN↗
DOE OSTI2020

Functional Ion Pair Receptors Targeting Cesium, Lithium, Sulfate, and Uranyl (Final Technical Report)

The major goal of this project was the synthesis and study of receptors for key ions of interest to the DOE mission, namely cesium, lithium, sulfate, hydroxide, carbon dioxide/bicarbonate, and early actinides. The work, fundamental in nature, had as its objective achieving an increased understanding of how changes in receptor design could be used to optimize binding energies, ion specificity, complex structure, extraction efficiency, and substrate release. Within this broad paradigm, particular emphasis was placed on systems that could be used to sense the cesium cation in mixed aqueous media and act as extractants for the lithium cation and, separately, the carbon dioxide/bicarbonate and hydroxide anions in the form of ion pairs likely to be encountered under conditions of putative use in the field. The development of new nitrogen-rich ligands that act as receptors for early, high-valent actinide cations was also a major point of emphasis. The first in-plane actinide complexes were synthesized using a hexa-aza porphyrin analogue. The complexes exhibited an increase in the ligand–metal bonding covalency on passing from thorium(IV) to uranium(IV) to neptunium(IV) and illustrates how the use of appropriate porphyrinoid-like ligands could be used to modulate the covalency interactions between an f-element metal center and a ligand.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Li-ion Battery Material phase prediction through Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are widely adopted in many industrial applications. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Therefore, it can eventually help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. However, these images often suffer from low image contrast between multiple material constituents , making it difficult for humans to distinguish and characterize these constituents through visualization. A minor error in detecting distributions among the material constituents can lead to a high error in the calculated parameters of material properties.We present a novel hierarchical curriculum learning framework to address the complex task of estimating material constituent distribution in battery electrodes. To provide spatially smooth prediction, our framework comprises three modules: (i) an uncertainty-aware model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a technique to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator to appropriately fuse the local and global effects towards obtaining the final distribution.

Tabassum, Anika↗
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 OSTI2021

Operando XAS/SAXS: Guiding Design of Single-Atom and Subnanocluster Catalysts

Single-atom and subnanocluster catalysts (SSCs) represent a highly promising class of low-cost materials with high catalytic activity and high atom-utilization efficiency. However, SSCs are susceptible to undergo restructuring during the reactions. Exploring the active sites of catalysts through in situ characterization techniques plays a critical role in studying reaction mechanism and guiding the design of optimum catalysts. In situ X-ray absorption spectroscopy/small-angle X-ray scattering (XAS/SAXS) is promising and widely used for monitoring electronic structure, atomic configuration, and size changes of SSCs during real-time working conditions. Unfortunately, there is no detailed summary of XAS/SAXS characterization results of SSCs. The recent advances in applying in situ XAS/SAXS to SSCs are thoroughly summarized in this review, including the atomic structure and oxidation state variations under open circuit and realistic reaction conditions. Furthermore, the reversible transformation of single-atom catalysts (SACs) to subnanoclusters/nanoparticles and the application of in situ XAS/SAXS in subnanoclusters are discussed. To conlcude, the outlooks in modulating the SSCs and developing operando XAS/SAXS for SSCs are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Study of Propane Combustion in a Spark-Ignited Cooperative Fuel Research (CFR) Engine

Liquefied petroleum gas (LPG), whose primary composition is propane, is a promising candidate for heavy-duty vehicle applications as a diesel fuel alternative due to its CO 2 reduction potential and high knock resistance. To realize diesel-like efficiencies, spark-ignited LPG engines are proposed to operate near knock-limit over a wide range of operating conditions, which necessitates an investigation of fuel-engine interactions that leads to end-gas autoignition with propane combustion. This work presents both experimental and numerical studies of stoichiometric propane combustion in a sparkignited (SI) cooperative fuel research (CFR) engine. Engine experiments are initially conducted at different compression ratio (CR) values, and the effects of CR on engine combustion are characterized. A three-pressure analysis (TPA) model based on the two-zone combustion concept is developed in GT-Power and validated using test results to estimate in-cylinder wall temperatures, residual gas fraction, etc. This model is further utilized to examine end-gas chemistry by enabling the SI turbulent flame combustion and unburned gas chemical kinetics modules. Finally, a three-dimensional (3D) computational fluid dynamic (CFD) model of the CFR engine is developed in CONVERGE, where the G-equation and SAGE detailed chemical kinetics models are implemented for combustion modeling. Here, a 153 species reduced chemical kinetics mechanism derived from the detailed NUIGMech1.1 mechanism based on the ignition delay and laminar flame speed (LFS) studies is used to generate an LFS lookup table and to describe end-gas autoignition chemistry. Multi-cycle Reynolds-averaged Navier-Stokes (RANS) simulations are then performed for the tested CRs, and the numerical model is shown to be capable of predicting the propane combustion characteristics, particularly the end-gas autoignition behavior.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Automated Data Review of Analytical Laboratory Results at Los Alamos National Laboratory - 20299

Newport News Nuclear BWXT-Los Alamos, LLC (N3B) collects samples in support of the U.S. Department of Energy's (DOE) Office of Environmental Management (EM) Los Alamos Legacy Cleanup Contract (LLCC). N3B receives and reviews over 1.6 million sample data points annually in support of various ongoing environmental monitoring and remediation projects of the LLCC. N3B must demonstrate and document that reported external analytical laboratory data produced for the LLCC are of sufficient quality to fulfill their intended purpose and to support defensible decision making as described in EPA QA/G4 Guidance for the Data Quality Objectives Process 1994. In 2018, N3B assumed management of the LLCC along with the Environmental Information Management (EIM) database that contains all historical and current environmental data associated with the LLCC. The entire EIM database is shared between N3B, Triad National Security, LLC (Triad), and New Mexico Environment Department (NMED). These three parties jointly manage the database, its configuration, and changes / updates. All environmental data that are entered into EIM are updated and available, on a daily basis, in the linked public database Intellus New Mexico (Intellus). The quality and defensibility of the environmental data generated from sampling activities is a key component of an effective remediation process. Providing quality data is accomplished through a data assessment process that includes examination, verification, and validation. Examination is the assessment of completeness of the deliverables, identification of any reporting errors, and determining the usability of the data based on the laboratory's evaluation of its data as described in the case narrative received with the data. Verification consists of an evaluation of the Electronic Data Deliverables (EDD) data report to determine the extent to which the external analytical laboratories met method and contract-specific quality control and reporting requirements. Validation consists of determining the data quality and the extent to which the external analytical laboratories accurately and completely reported all sample and quality control results and satisfied all contract requirements. EIM contains an automatic Data Validation Module which performs automated data review (DVM ADR). DVM ADR is a tool to assist in the validation process. When DVM ADR is used in conjunction with manual examination of sample data packages, the combination of the two will meet and exceed the requirements of verification. N3B recognized an opportunity for process improvement, focusing on DVM ADR configuration and enhancements in EIM. Testing EIM's configuration provided proof of the DVM ADR's capabilities and flexibility to accurately perform routine data checks based on analytical methods and regulatory requirements. In addition, the DVM ADR module was improved through enhancements for all analytes, particularly upgrades for radiochemistry data. Extensive testing of the DVM ADR module occurred using EDDs from actual laboratory analyses on the EIM testing site. During this process, N3B manipulated EDD information to verify that the actual outcomes matched the expected outcomes. The results of this testing were shared with the database architects, and configuration improvements were identified to address these results. During this process, N3B identified that the radiochemical DVM ADR capabilities were underutilized, and so enhanced the DVM ADR functionality with respect to radioanalytical assessment. N3B environmental data uploads to Intellus on a daily basis from EIM, once the analytical data undergoes examination and verification. As such, it is important to have a high level of confidence in the quality and defensibility of the data. The process of manual examination, along with the DVM ADR, in conjunction with full validation of a percentage the data specified through the Data Quality Objectives greatly increases efficiency of data review and confidence level of the quality of the data, and gives the project managers, governmental offices, and the public expedited access to high-quality data. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Modulating Energy Level on an A‐D‐A′‐D‐A‐Type Unfused Acceptor by a Benzothiadiazole Core Enables Organic Solar Cells with Simple Procedure and High Performance

Unfused‐ring acceptors (UFAs) have gained considerable research attention as they offer simple chemical structures through simplified synthesis methods, which would boost the commercialization of organic solar cells (OSCs). Recently, a new small molecule acceptor (SMA) named Y6 was reported, yielding high‐performance OSCs. Herein, the Y6‐like A‐DA′D‐A framework is developed to A‐D‐A′‐D‐A‐type backbone adopted in constructing UFAs. Two new Y6‐like UFAs are synthesized within four steps and the effect of noncovalent atoms at the central electron‐deficient core on material properties and device performances is studied. It is found that the introduction of fluorine atoms can bring larger red‐shift in the absorption spectra and better aggregation of the resulting UFA film states compared with those of oxygen atoms. Interestingly, the variations in the noncovalent interaction atoms induce different intermolecular charge transfer between donors and UFAs. When blended with another economical donor, PTQ10, F substitution at the benzothiadiazole ring is more effective than O substitution, leading to the increased short‐circuit current density ( J SC ) and higher efficiency of over 12%, among the best performances of UFA‐based OSCs. This contribution demonstrates the appropriate introduction of noncovalent interaction is a promising method for tuning energy levels, absorption, and aggregation of UFAs for high‐performance OSCs.

Yu, Han↗
DOE OSTI2026

Electronic origin of reorganization energy in interfacial electron transfer

Electron transfer (ET) reactions underpin energy conversion and chemical transformations in both biological and a biological systems. The efficiency of any ET process relies on achieving a desired ET rate within an optimal driving force range. Marcus theory provides a microscopic framework for understanding the activation free energy—and therefore the rate—of ET in terms of a key parameter: the reorganization energy. For electrified solid–liquid interfaces, it has long been conventionally understood that only factors in the electrolyte phase are responsible for determining the reorganization energy and that the electronic density of states (DOS) of the electrode only serves to dictate the number of thermally accessible channels for ET. Here we show instead that the electrode DOS plays a central role in governing the reorganization energy, far outweighing its conventionally assumed role. Using atomically layered heterostructures, we tune the DOS of graphene and measure outer-sphere ET kinetics. We find the ensuing variation in ET rate arises from strong modulation in a reorganization energy associated with image potential localization in the electrode. Here we redefine the traditional paradigm of heterogeneous ET kinetics, revealing a deeper role of the electrode electronic structure in interfacial reactivity.

Electrochemistry↗
DOE OSTI2023

Silver-decorated palladium on carbon catalyst for enhanced ammonium formate dehydrogenation

Palladium (Pd)-based catalysts efficiently convert ammonium formate solution to hydrogen at low temperatures (<100 °C), but they tend to deactivate quickly during stability testing. This manuscript presents a systematic investigation into the catalytic properties of Pd–Ag bimetallic catalysts, focusing on their surface compositions and exploring the mechanisms behind the deactivation of Pd/Ag-based catalysts. Here this study reports a carbon-supported Pd–Ag bimetallic nanoparticle (NP) catalyst obtained through a galvanic replacement method, which showed enhanced formate dehydrogenation performance. The best catalyst, Pd 3 Ag 10 /ACA-G (Pd–Ag bimetallic NPs with a 3 : 10 mass ratio loaded on acid-washed activated carbon, prepared by the galvanic replacement method), presents the highest activity with a TOF of 5202 h -1 (~2.6-fold of commercial Pd/C). The enhanced electron density of Pd–Ag bimetallic nanoparticles, coupled with the advantages of a smaller nanoparticle size, and the modulation of hydrogen adsorption energy through the Ag/Pd surface alloy on the Ag/Pd(111) facet, collectively resulted in experimentally higher turnover rates of hydrogen production. The changes on the catalyst surface, including surface Ag fraction decrease, NP size growth, and O-containing species (carboxylate, etc.) adsorption, gradually resulted in catalyst deactivation.

08 HYDROGEN↗
DOE OSTI2021

Gene family expansions and transcriptome signatures uncover fungal adaptations to wood decay

Because they comprise some of the most efficient wood-decayers, Polyporales fungi impact carbon cycling in forest environment. Despite continuous discoveries on the enzymatic machinery involved in wood decomposition, the vision on their evolutionary adaptation to wood decay and genome diversity remains incomplete. We combined the genome sequence information from 50 Polyporales species, including 26 newly sequenced genomes and sought for genomic and functional adaptations to wood decay through the analysis of genome composition and transcriptome responses to different carbon sources. The genomes of Polyporales from different phylogenetic clades showed poor conservation in macrosynteny, indicative of genome rearrangements. We observed different gene family expansion/contraction histories for plant cell wall degrading enzymes in core polyporoids and phlebioids and captured expansions for genes involved in signalling and regulation in the lineages of white rotters. Furthermore, we identified conserved cupredoxins, thaumatin-like proteins and lytic polysaccharide monooxygenases with a yet uncharacterized appended module as new candidate players in wood decomposition. Given the current need for enzymatic toolkits dedicated to the transformation of renewable carbon sources, the observed genomic diversity among Polyporales strengthens the relevance of mining Polyporales biodiversity to understand the molecular mechanisms of wood decay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Natural switches in behaviour rapidly modulate hippocampal coding

Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat. Hippocampal CA1 neurons represented the bat’s own position when flying alone (place coding). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast—as fast as 100 ms—which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗