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DOE OSTI2024

Neural simulation-based inference of the neutron star equation of state directly from telescope spectra

Neutron stars provide a unique opportunity to study strongly interacting matter under extreme density conditions. The intricacies of matter inside neutron stars and their equation of state are not directly visible, but determine bulk properties, such as mass and radius, which affect the star's thermal X-ray emissions. However, the telescope spectra of these emissions are also affected by the stellar distance, hydrogen column, and effective surface temperature, which are not always well-constrained. Uncertainties on these nuisance parameters must be accounted for when making a robust estimation of the equation of state. In this study, we develop a novel methodology that, for the first time, can infer the full posterior distribution of both the equation of state and nuisance parameters directly from telescope observations. This method relies on the use of neural likelihood estimation, in which normalizing flows use samples of simulated telescope data to learn the likelihood of the neutron star spectra as a function of these parameters, coupled with Hamiltonian Monte Carlo methods to efficiently sample from the corresponding posterior distribution. Our approach surpasses the accuracy of previous methods, improves the interpretability of the results by providing access to the full posterior distribution, and naturally scales to a growing number of neutron star observations expected in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Editorial: Functionalization of porous materials for sustainable energy applications

Global energy demands are shifting toward a more sustainable future, with the goal of achieving carbon neutrality by 2050. Emerging technologies are driving this transition. The industry, academia, government, non-profit organizations, and the broader community are collaboratively working to reduce greenhouse gas (GHG) emissions and address climate change to ensure a sustainable future. According to the International Energy Agency, in 2022, the production, transportation, and processing of oil and gas resulted in 5.1 billion tons of CO 2 -equivalent emissions, representing nearly 15% of all energy-related GHG emissions. Moreover, the end-use of oil and gas accounted for an additional 40% of emissions. The IEA’s Net Zero Emissions by 2050 Scenario calls for immediate, collective action from the industry, transportation and other stakeholders to mitigate these emissions. In this effort, the development of energy materials will play a critical role in reducing emissions. Among these, porous materials offer an innovative solution, leveraging their high surface area, adjustable pore sizes, and chemical versatility to address these pressing challenges effectively. By carefully designing their nanostructures, the architecture and properties of these materials can be tailored for specific applications. Key factors such as chemical composition, particle size, pore distribution, and surface area optimization enhance the reactivity and energy conversion efficiency. Additionally, pre- and post-functionalization processes can introduce targeted chemical properties, further improving their performance. This Research Topic explores recent advancements in energy and materials science through four scholarly papers, showcasing innovative solutions for sustainable energy technologies while providing valuable insights into the unique properties and structure of porous materials (Figure 1). Li et al. present their work on highly defective NiFeV layered triple hydroxides, highlighting enhanced electrocatalytic activity and stability for oxygen evolution reactions (OER). Kovalskii et al. contribute a mini-review on hydrogen storage using hexagonal boron nitride (h-BN) and BN-based materials, offering an insightful overview of these promising materials. Chava et al. discuss their recent achievements in ceramic electrolytes used for improvement of performance of solid-state batteries. Lastly, Li et al. review the properties of porous materials with a focus on shrinkage behavior during the drying process, shedding light on key considerations for material design.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Decomposing Cloud Radiative Feedbacks by Cloud-Top Phase

Changes in cloud scattering properties and emissivity that arise from atmospheric warming cause substantial radiative feedbacks in model projections of anthropogenic climate change, and the relative importance of the underlying mechanisms is poorly understood. One leading hypothesis is that ice-to-liquid conversions cause clouds to optically thicken, producing a major negative feedback. We test this hypothesis by developing a method to decompose cloud radiative feedbacks by cloud-top phase. The method is applied to an ensemble of six state-of-the-art global climate models run with prescribed sea surface temperature. In these simulations, the global mean of the net cloud scattering and emissivity feedback from cloud-phase conversions ranges from −0.17 to −0.01 W m −2 K −1 , while the overall net cloud feedback ranges from 0.02 to 0.91 W m −2 K −1 . The multimodel mean of the cloud scattering and emissivity feedback from cloud-phase conversions is approximately 19% of the magnitude of the multimodel mean of the overall cloud feedback (−0.10 vs 0.52 W m −2 K −1 ). These results indicate that cloud-phase conversions cause a robust negative feedback by changing cloud scattering and emissivity, but this mechanism makes a modest contribution to the overall cloud feedback at the global scale.

Climate change↗

DOE OSTI2025

Heating of Cs2Te photocathode via field emission and radiofrequency pulsed heating: Implication toward breakdown

The occurrence of radiofrequency (RF) breakdown limits operational electromagnetic gradients in accelerator structures. Experimental evidence often suggests that breakdown events are associated with temperature and dark current spikes on the surface of RF devices. In the past decade, there has been increased interest in unveiling the mechanism behind breakdown initiation in metal copper and copper alloys; however, efforts regarding a breakdown phenomenon in photocathode-relevant semiconductors have been more limited. In this work, we explore field-emission-assisted heating via Nottingham and Joule processes, as a possible candidate for breakdown initiation. For this, field emission from an intrinsic Cs2Te ultrathin film coated on a copper substrate was modeled within the Stratton–Baskin–Lvov–Fursey formalism, describing the processes and effects in the bulk and on the surface of a photocathode exposed to high RF electromagnetic fields. It is shown that a field-emission characteristic deviates significantly from the classical Fowler–Nordheim (FN) theory, whereby predicting that dark current is orders of magnitude lower than the one expected by FN law. Conventional pulsed heating was also found to impose negligible heating to the photocathode. Both conclusions suggest that a Cs2Te photocathode coated on a metal substrate would be insensitive to catastrophic thermal-material runaway breakdown, unlike what is observed for metal surfaces. Finally, a few unconventional breakdown candidate scenarios are identified and discussed, including thermoelastic deformation and avalanche breakdown.

Shinohara, Ryo (ORCID:0000000276995732)↗

DOE OSTI2024

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability

Abstract Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH 4 ) emissions; however, no earth system model (ESM) has represented lake CH 4 dynamics. To fill this gap, we refined a process‐based lake biogeochemical model to simulate global lake CH 4 emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non‐linear CH 4 oxidation kinetics, and the coupling of sediment carbon pools with in‐lake primary production and terrigenous carbon loadings. We compiled a lake CH 4 data set for model validation. The model shows promising performance in capturing the seasonal and inter‐annual variabilities of CH 4 emissions at 10 representative lakes for different lake types and the variations in mean annual CH 4 emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH 4 diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH 4 diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH 4 outgassing events in non‐floodplain lakes and the seasonal variability of CH 4 ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH 4 emissions and climate‐CH 4 feedback.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Effects of oxidation and impurities in lithium surfaces on the emitting wall plasma sheath

The use of lithium as a surface coating in fusion devices improves the plasma performance, but the change in the wall properties affects the secondary electron emission properties of the material. Lithium oxidizes easily, which drives the emission yield well above unity. We present here simulations demonstrating the change in the sheath structure from monotonic to the nonmonotonic space-charge limited sheath using an energy-dependent data-driven emission model, which self-consistently captures both secondary emission and backscattering populations. Increased secondary electron emission from the material has ramifications for the degradation and erosion of the wall. The results show that the oxidation leads to an increased electron energy flux into the wall and a reduced ion energy flux. The net transfer of energy to the surface is significantly greater for the oxidized case than for the pure lithium case. High backscattering rates of low-energy particles lead to a high re-emission rate at the wall.

Fusion reactors↗

DOE OSTI2026

Depth-Dependent Emission from Silver Dopants in Single CdSe Nanoplatelets

Dopants in semiconductor nanostructures offer tremendous control over electronic, optical, and magnetic properties beyond what is achievable in bulk materials. We demonstrate that the broad dopant emission in semiconductor nanoplatelets effectively maps the electron wave function across the nanoplatelet thickness. Both the emission energy and lifetime of the dopant transition depend strongly on the depth of the dopant within the nanoplatelet. This dependence arises from the electrostatic self-interaction of the charged dopant, which varies with proximity to the dielectric discontinuity at the nanoplatelet surface. Through comprehensive single-particle spectroscopy of silver-doped CdSe nanoplatelets, we verify that acceptors near the center emit at higher energies with shorter lifetimes, while those near the surface emit at lower energies with longer lifetimes. This spatial mapping also reveals unusual two-color emission from individual nanoplatelets, with enhanced Auger recombination yielding exceptional photon antibunching (>90% purity) at room temperature, suggesting potential applications in quantum information technologies.

cadmium selenide↗

DOE OSTI2025

Structure and Dynamics of CO 2 at the Air–Water Interface from Classical and Neural Network Potentials

The accurate description of the structure and dynamics of CO 2 at the instantaneous air–water interface, along with the effects of surface fluctuations on the CO 2 -transport processes, is essential for the development of negative emission technologies aimed at minimizing climate change. In this study, we performed molecular dynamics simulations of CO 2 at the air–water interface using neural network potentials (NNPs) trained on ab initio data generated through density-functional-theory-based molecular dynamics simulations. We compared these results with classical force fields to assess their performance in modeling interfacial CO 2 behavior. Our findings revealed that the asymmetric interactions, coupled with thermal surface fluctuations at the air–water interface, significantly influence CO 2 transport into the aqueous phase. The simulations demonstrate that classical force fields underestimate both the free energy of CO 2 transport and the strength of its interactions at the interface compared with the neural network potentials. In conclusion, the free energy and the interfacial dynamics of CO 2 are primarily influenced by the distribution of water within the instantaneous interfacial water layer, responsible for creating an asymmetric intermolecular interaction environment within the interfacial region.

Ab initio molecular dynamics↗

DOE OSTI2025

Large emissions of CO 2 and CH 4 due to active-layer warming in Arctic tundra

Climate warming may accelerate decomposition of Arctic soil carbon, but few controlled experiments have manipulated the entire active layer. To determine surface-atmosphere fluxes of carbon dioxide and methane under anticipated end-of-century warming, here we used heating rods to warm (by 3.8 °C) to the depth of permafrost in polygonal tundra in $Utqia\dot{g}vik$ (formerly Barrow), Alaska and measured fluxes over two growing seasons. We show that ecosystem respiration is ~30% higher in warmed plots than in control plots (0.99 μmol m -2 s -1 versus 0.67 μmol m -2 s -1 , p < 0.0001, n = 79). Additionally, the observed temperature sensitivity (Q 10 of 2.8) is higher than that imposed for soil in Earth system models or reported by arctic experiments warming only the surface. A shoulder-season warming experiment revealed that rapid snow melt, which is becoming a more common event, can result in large methane emissions that may have otherwise been oxidized to carbon dioxide. Thus, warming promotes greenhouse gas emissions from the whole, deepening active layer and may contribute to climate change amplification.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Shrub Expansion Can Counteract Carbon Losses From Warming Tundra

Arctic warming is causing substantial compositional, structural, and functional changes in tundra vegetation including shrub and tree-line expansion and densification. However, predicting the carbon trajectories of the changing Arctic is challenging due to interacting feedbacks between vegetation composition and structure, and surface characteristics. We conduct a sensitivity analysis of the current-date to 2100 projected surface energy fluxes, soil carbon pools, and CO 2 fluxes to different shrub expansion rates under future emission scenarios (intermediate—RCP4.5, and high—RCP8.5) using the Arctic-focused configuration of E3SM Land Model (ELM). We focus on Trail Valley Creek (TVC), an upland tundra site in the western Canadian Arctic, which is experiencing shrub densification and expansion. We find that shrub expansion did not significantly alter the modeled surface energy and water budgets. However, the carbon balance was sensitive to shrub expansion, which drove higher rates of carbon sequestration as a consequence of higher shrubification rates. Thus, at low shrub expansion rates, the site would become a carbon source, especially under RCP8.5, due to higher temperatures, which deepen the active layer and enhance soil respiration. At higher shrub expansion rates, TVC would become a net CO 2 sink under both Representative Concentration Pathway scenarios due to higher shrub productivity outweighing temperature-driven respiration increase. Our simulations highlight the effect of shrub expansion on Arctic ecosystem carbon fluxes and stocks. We predict that at TVC, shrubification rate would interact with climate change intensity to determine whether the site would become a carbon sink or source under projected future climate.

Yazbeck, Theresia [The Ohio State Univ., Columbus,↗

DOE OSTI2026

The role of local shipping emissions in aerosol-cloud interactions in the central Arctic

Arctic shipping is projected to increase as sea ice retreats, yet the impact of modern low-sulfur ship emissions on Arctic clouds and radiation remain poorly constrained. We use year-long in situ observations from the MOSAiC expedition to characterize ship-aerosol-cloud interactions for an icebreaker burning ultra-low sulfur fuel (0.1% mass per mass). Exhaust plumes were found to be strongly enriched in Aitken-mode particles, organic aerosol, and black carbon, but showed no detectable enhancement in particulate sulfate. Despite reduced hygroscopicity relative to ambient aerosols, ship emissions substantially increased local cloud condensation nuclei concentrations. A droplet activation parameterization was applied to quantify responses in cloud droplet number concentration ( N d ) to ship-induced perturbations in low-level Arctic clouds. In winter, abundant background accumulation-mode particles from Arctic haze supplied nearly all cloud droplets, while additional particles from ship emissions had little impact on N d . In contrast, during summer months, when unperturbed background aerosol concentrations are low, ship emissions nearly doubled N d compared to average background conditions and increased N d by a factor of five compared to very clean background conditions (25th percentile of background aerosol number concentrations). Longwave radiative transfer simulations for typical conditions of summer Arctic low-level clouds/fog suggest that these ship-induced increases in N d locally (i.e. <100 km downwind) lead to enhanced net surface longwave fluxes and consequent warming, primarily for optically thin clouds (liquid water path (LWP) ⩽ 30 g·m −2 ). For LWP = 10 g · m −2 , ship emissions lead to an increase of 1 W · m −2 in cloud longwave forcing at the surface compared to average unperturbed conditions (+7% relative increase), and up to 4 W · m −2 when compared to very clean background conditions (+22% relative increase). Even ultra-low sulfur fuel emissions can therefore locally and episodically modify Arctic cloud microphysics and radiative properties, especially during summer, implying that future increases in Arctic shipping could have non-negligible regional climate impacts.

Arctic↗

DOE OSTI2025

Assessing the climate impact of an improved volcanic sulfate aerosol representation in E3SM

Accurately simulating historical surface temperature variations is essential for evaluating climate models, yet many struggle to reproduce the mid-20th-century temperature trends associated with significant volcanic eruptions. This study examines the impact of volcanic sulfate aerosol representation on these biases using the Energy Exascale Earth System Model (E3SM). The standard CMIP6 protocol prescribes volcanic forcing through radiative perturbations, omitting volcanic aerosol–cloud interactions (VACIs). Here, we implement an emission-based approach with an updated volcanic eruption inventory that directly incorporates volcanic sulfur dioxide (SO 2 ) emissions, enabling a more process-based representation of volcanic forcing. This approach leads to improved surface temperature variability and a modest reduction in cold biases between 1940 and 1980 compared to the CMIP6 setup. Additionally, we assess cloud property responses to a more realistic volcanic sulfate aerosol representation, which weakens cloud-induced cooling during periods of lower volcanic activity. However, despite these refinements, a significant temperature cold bias remains, indicating that further improvements in atmospheric chemistry, aerosol microphysics, cloud processes, and model parameterizations are needed to fully resolve this issue in E3SM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Spatiotemporal Dynamics of the Relative Abundance of Soil Nutrient‐Degrading Enzyme‐Encoding Genes Across Continental US Ecoregions

Understanding the spatiotemporal patterns in the relative abundance of soil extracellular enzyme‐encoding genes is critical for predicting microbial responses to environmental change and their potential role in nutrient cycling. Yet, integrating novel metagenomic observations with spatiotemporal environmental gradients to infer regional patterns and future trajectories has remained unclear. To address this gap, we applied a machine learning (ML) approach, integrating soil metagenomic data with environmental variables—soil properties, topography, vegetation, and climate—to predict the relative abundance of enzyme‐encoding genes for soil carbon (C), nitrogen (N), and phosphorus (P) across surface soils of the continental United States. We assessed potential responses under future emission scenarios (SSP2‐4.5 and SSP5‐8.5) by comparing a baseline (1985–2014) to a future period (2071–2100). The ML model explained 57%–63% of baseline variation. Precipitation was identified as the most influential factor for the relative abundance of C‐ and N‐degrading enzyme‐encoding genes, while slope length, representing horizontal distance that water can travel downslope, was the primary driver for P‐degrading enzyme‐encoding genes abundance. Projections revealed spatially heterogeneous shifts across continental US ecoregions: the relative abundance of C‐ and N‐degrading enzyme‐encoding genes decreased in wetter ecoregions and increased in drier ecoregions under future climate, while P‐degrading enzyme‐encoding genes abundance decreased significantly in semiarid and Mediterranean ecoregions. This study demonstrates the utility of metagenomic data for mapping soil genetic potential and predicting its regional response to environmental change, to inform ecosystem management strategies.

extracellular enzyme-encoding genes↗

DOE OSTI2026

The effectiveness of D 2 pellet and gas injection in reducing intra-ELM tungsten erosion and heat flux in the DIII-D small angle slot divertor

Edge localized modes (ELMs) in H-mode plasmas can melt and erode plasma-facing components (PFCs) and lead to impurities in the core, reducing confinement. This study analyzes the use of D 2 pellet and gas injection for ELM mitigation on the DIII-D tokamak during the 2022 Small Angle Slot V-shaped Tungsten (W) (SAS-VW) divertor campaign, reducing W erosion and heat flux during ELMs. D α (656 nm) and WI (400.9 nm) filterscopes and Langmuir probes provide photon emission and electron density/temperature to estimate W atom erosion using the S/XB method, while surface eroding thermocouples measured ELM peak heat flux at the outer strike point (OSP). Thomson Scattering measurements of pedestal T e and n e provided input to predict W divertor erosion and heat flux during ELMs via the Free-Streaming plus Recycling Model (FSRM). While a greater D 2 mass injection rate decreased the ELM peak heat flux, the impact on W erosion was not monotonic. The average ‘large’ intra-ELM W erosion was lower for plasma shots with D 2 mass injection compared to the plasma shots without any D 2 mass injection in the SAS-VW divertor. However, plasma shots did not see significant changes in ‘large’ intra-ELM W divertor erosion as the D 2 mass injection rate increased. On average, the FSRM overestimated SAS-VW experimental intra-ELM W erosion by a factor of 6.9, but the overestimation is reduced to a factor of 3.6 with the implication of C deposition effects. Generally, experimentally measured and predicted quantities were worse for plasma shots with a lower D 2 mass injection rate and corresponding higher plasma carbon (C) impurity percentage (f C ). The discrepancies are postulated to be due to C/W material mixing, for which a simple analytic mixed-material model is presented. These results highlight the importance of incorporating and improving the robustness of a mixed-material layer model in the analysis of PFC erosion on present and future tokamak devices.

Carbon (C)↗

DOE OSTI2025

Climate-focused Life Cycle Assessments of Biochar Production by an ARTi Pyrolysis Reactor and an Air Burners CharBoss® Air Curtain Incinerator

This report presents a limited, dynamic, consequential life cycle assessment (LCA) to compare the climate impacts of two biochar production methods using wood as a feedstock. The two methods are a pyrolysis reactor supplied by ARTi (Des Moines, IA, https://www.arti.com/) and a T26 CharBoss® air curtain incinerator supplied by Air Burners, Inc. (Palm City, FL, https://airburners.com/). The underlying LCA methodology is described in a chapter by Singh et al. (2024) and implemented in the form of a workbook freely available as online Supplementary Material for the chapter. For the convenience of the reader, a pre-print version of the relevant portions of Singh et al. (2024) is attached as Appendix A to this report. Specific assumptions and calculations to obtain the input parameters used in this LCA for each production method are described in the Methodology section below. This implementation of the LCA considers emissions associated with biomass loading, comminution and conversion, biochar decay in soil, and the production and use of bioenergy generated during the conversion process. The LCA is “limited” in that upstream emissions associated with biomass production, harvest, transportation, and land-use change, as well as embodied emissions in equipment and facilities are not considered. Similarly, downstream emissions from biochar transport and incorporation into soil (i.e., tillage), and the impact of biochar soil amendments on soil greenhouse gas (GHG) emissions (other than CO 2 from biochar decay in soil), soil organic carbon stocks, crop response, and surface albedo are not considered. As the intent is to compare different biochar production methods in a simple unbiased manner, the primary alternative biomass pathway for the LCA is immaculate combustion, which is the hypothetical instantaneous and complete conversion of carbon in the biomass to CO 2 at time zero without generation of any other greenhouse gases or aerosols (GHGAs) or any useful bioenergy. Use of this pathway provides relative values for the production methods and, when the embodied emissions are similar and the same feedstock is used, these relative values are reasonable approximations for those attained with a full LCA.

09 BIOMASS FUELS↗

DOE OSTI2024

Modelling of the electron cyclotron emission burst from a laboratory tokamak plasma with loss-cone maser instability

The maser instability associated with the loss-cone distribution has been widely invoked to explain the radio bursts observed in the astrophysical plasma environment, such as aurora and corona. In the laboratory plasma of a tokamak, events reminiscent of these radio bursts have also been frequently observed as an electron cyclotron emission (ECE) burst in the microwave range (~2f ce near the last closed flux surface) during transient magnetohydrodynamic events. These bursts have a short duration of ~10 μs and display a radiation spectrum corresponding to a radiation temperature T e,rad of over 30 keV while the edge thermal electron temperature T e is only in the range of 1 keV. Suprathermal electrons can be generated through magnetic reconnection, and a loss-cone distribution can be generated through open stochastic field lines in the magnetic mirror of the near-edge region of a tokamak plasma. Radiation modelling shows that a sharp distribution gradient ∂f/∂v ⊥ > 0 at the loss-cone boundary can cause a negative absorption of ECE radiation through the maser instability. The negative absorption then amplifies the radiation so that the microwave intensity is significantly stronger than the thermal value. The significant T e,rad from the simulations suggests the potential role of the loss-cone maser instability in generating the ECE burst in a tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Effect of CO 2 Concentration on the Microbial Activity of Orenia metallireducens (Strain Z6) in Surface Inert Materials

Carbon dioxide (CO 2 ) sequestration has garnered widespread attention as a key strategy for mitigating CO 2 emissions and combating the greenhouse effect. However, the mechanisms underlying the interactions between CO 2 , widespread siliceous minerals and biological processes remain unclear. The present study explored the potential impacts of different CO 2 concentrations on microbial activity, environmental conditions and their feedback on the fate of CO 2 . A total of 20 experimental conditions was created, with the variables including different natural and synthetic siliceous minerals (e.g., quartz sand and a type of commercial glass beads), the presence or absence of the iron-reducing microorganism Orenia metallireducens (strain Z6) and varying CO 2 concentrations (0%, 20%, 50%, 100%) in the presence of ferrihydrite and pyruvate. Geochemical, microbial and mineralogical analyses revealed that elevated CO 2 concentrations significantly inhibited microbial Fe(III) reduction and pyruvate metabolism. Interestingly, compared to cultures without mineral amendments or those with glass beads alone, the addition of quartz sand enabled strain Z6 to better withstand the environmental stress caused by elevated CO 2 , promoting pyruvate fermentation and iron reduction. In addition to an increased pH, the formation of siderite, hematite and vivianite was also observed in the bioactive systems. Although both glass beads and quartz sand were primarily composed of silica, differences in the mineral structure, elemental composition and acid neutralization capacity rendered quartz sand more chemically active and unexpectedly led to greater CO 2 sequestration.

CO2 stress↗

DOE OSTI2025

Dual interfacial H-bonding-enhanced deep-blue hybrid copper–iodide LEDs

Solution-processed light-emitting diodes based on non-toxic copper–iodide hybrids are a compelling solution for efficient and stable deep-blue lighting, owing to their tunability, high photoluminescence efficiency and environmental sustainability. Here we present a hybrid copper–iodide that shows near-unity photoluminescence quantum yield (99.6%) with an emission wavelength of 449 nm and colour coordinates (0.147, 0.087), alongside its emission mechanism and charge transport characteristics. Here, we use the thin film of this hybrid as the sole active emissive layer to fabricate deep-blue light-emitting diodes and subsequently enhance the device performance through a dual interfacial hydrogen-bond passivation strategy. This synergetic surface modification approach, integrating a hydrogen-bond-acceptor self-assembled monolayer with an ultrathin polymethyl methacrylate capping layer, effectively passivates both heterojunctions of the copper–iodide hybrid emissive layer and optimizes charge injections. We achieve a maximum external quantum efficiency of 12.57%, a maximum luminance of 3,970.30 cd m −2 with colour coordinates (0.147, 0.091) and an excellent operational stability (half-lifetime) of 204 hours under ambient conditions. We further showcase a large-area device of 4 cm 2 that maintains high efficiency. Our findings reveal the potential of copper–iodide-based hybrid materials for applications in solid-state lighting and display technologies, offering a versatile strategy for enhancing device performances.

14 SOLAR ENERGY↗