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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Multi-modal characterization of nitrate reduction nano-catalysts with periodic strain distribution

Strain engineering serves as a pivotal strategy to optimize catalytic activity in electrocatalysis. However, the catalyst sizes under industrial conditions are usually large and even beyond nanometer regime. The critical methodological limitations on strain imaging of such catalysts with both large field of view and high spatial resolution obscure the mechanistic understanding of strain-performance correlations. Here, we present an optimized four-dimensional scanning transmission electron microscopy (4D-STEM) method to acquire strain mapping of both bulk and surface across particles up to 500 nm with 0.6 nm spatial resolution and 0.55% precision. We observe the ripple-like periodic strain coupled with elemental fluctuations inside a perovskite-type hydroxide CuCoSn(OH) 6 and find it correlated to electrocatalytic nitrate reduction (NO 3 – RR) absorption energy to achieve the 92.6% Faradaic efficiency and long-term test over 1000 h at membrane electrode assembly (MEA) for ammonia electrosynthesis. This universal framework design offers a practical method that not only develops an advanced measurement combining multi-modal characterization techniques but also reveals the intrinsic structure-property constitutive law of industry-level catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

An Innovative High Throughput Genome Releaser for Rapid and Efficient PCR Screening

High-throughput PCR screening is vital in synthetic biology and metabolic engineering as it allows researchers to rapidly analyze and detect numerous targeted genetic mutation in the genome. Current challenges for high-throughput PCR screening in synthetic biology include efficiently preparing genomic DNA, optimizing protocols for diverse sample types, managing contamination risks, and effectively analyzing the large volumes of data generated while ensuring consistent and accurate results. In this study, we present the development of a High Throughput Genome Releaser (HTGR), an innovative device addressing common challenges in screening PCR. This genome DNA releaser is designed based on a squash method for rapid, cost-effective, and efficient DNA release, optimized for subsequent PCR reactions. After experimenting with various synthetic materials, we selected a plastic that closely replicates the smooth surface and compression properties of microscope slides, ensuring reliable performance. We engineered a device featuring a 96-Well Plate and a shear applicator, operable both manually and automatically, and compatible with standard liquid-handling robot platform. This compatibility enhances ease of use in high-throughput PCR workflows. Additionally, we developed software to support its automatic functions. Our results demonstrated that the specially engineered 96-Well Plate and HTGR can effectively squash fungal spores , which release enough genome DNA for PCR screening. The genome releaser facilitates the preparation of PCR-amplifiable genomic DNA substrate from 96 samples within minutes, eliminates the need for extraction buffers, and is adaptable to a wide range of microorganisms and cells, which could significantly advance biomanufacturing processes.

Yuan, Guoliang [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2025

Review of High-Throughput Surface Treatments for Microlens Arrays

Microlenses are increasingly being integrated into modern manufactured devices. From printed security devices and screens to solar panels and microscopes, these optical materials offer high control over light focusing. Thus, understanding how to treat the surfaces of these fragile, transparent devices on an integrated manufacturing line is essential. Here, in this study, we review the surface treatments for the following application categories: cleaning, increasing surface energy, decreasing surface energy, and tunable surface modifications. This overview describes methods available for the large-scale manufacturing of microlens arrays and the potential impact of those treatments on common optical surfaces. Objectives and qualitative compatibility parameters are compared, and outlooks are provided for further study to aid in streamlining the method selection and process optimization for microlenses and similar optical components.

lens manufacturing↗
DOE OSTI2026

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗
DOE OSTI2026

Virtual Growth of SRF Materials: A Machine Learning Approach to Predict the Crystalline Structural Ordering in Nb Surface Oxides

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Unlisted, US, IL; Fermilab]↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
DOE OSTI2024

Integrating the Design of Desalination Technologies into Produced Water Network Optimization

The oil and gas energy sector uses billions of gallons of water for hydraulic fracturing each year to extract oil and gas. The water injected into the ground for fracturing along with naturally occur-ring formation water from the oil wells surfaces back in the form of produced water. Produced water can contain high concentrations of total dissolved solids and is unfit for reuse outside the oil and gas industry without desalination. In semi-arid shale plays, produced water desalination for beneficial reuse could play a crucial role in alleviating water shortages and addressing extreme drought conditions. In this paper we co-optimize the design and operation of desalination technologies along with operational decisions across produced water networks. A multi-period produced water network model with simplified split-fraction-based desalination nodes is developed. Rigorous steady-state desalination mathematical models based on mechanical vapor recompression are developed and embedded at the desalination sites in the network model. An optimal common design is ensured across all periods using global capacity constraints. The solution approach is demonstrated for multi-period planning problems on networks from the PARETO open-source library. Model formulation and challenges associated with scalability are discussed.

Naik, Sakshi↗
DOE OSTI2024

eReaxFF force field development for BaZr 0.8 Y 0.2 O 3-δ solid oxide electrolysis cells applications

The use of solid-oxide materials in electrocatalysis applications, especially in hydrogen-evolution reactions, is promising. However, further improvements are warranted to overcome the fundamental bottlenecks to enhancing the performance of solid-oxide electrolysis cells (SOECs), which is directly linked to the more-refined fundamental understanding of complex physical and chemical phenomena and mass exchanges that take place at the surfaces and in the bulk of electrocatalysis materials. Here, we developed an eReaxFF force field for barium zirconate doped with 20 mol% of yttrium, BaZr 0.8 Y 0.2 O 3-δ (BZY20) to enable a systematic, large-length-scale, and longer-timescale atomistic simulation of solid-oxide electrocatalysis for hydrogen generation. All parameters for the eReaxFF were optimized to reproduce quantum-mechanical (QM) calculations on relevant condensed phase and cluster systems describing oxygen vacancies, vacancy migrations, electron localization, water adsorption, water splitting, and hydrogen generation on the surfaces of the BZY20 solid oxide. Using the developed force field, we performed both zero-voltage (excess electrons absent) and non-zero-voltage (excess electrons present) molecular dynamics simulations to observe water adsorption, water splitting, proton migration, oxygen-vacancy migrations, and eventual hydrogen-production reactions. Based on investigations offered in the present study, we conclude that the eReaxFF force field-based approach can enable computationally efficient simulations for electron conductivity, electron leakage, and other non-zero-voltage effects on the solid oxide materials using the explicit-electron concept. Moreover, we demonstrate how the eReaxFF force field-based atomistic-simulation approach can enhance our understanding of processes in SOEC applications and potentially other renewable-energy applications.

08 HYDROGEN↗
DOE OSTI2025

Current-Regulated Arc Modulator Optimization

n this study, the performance of a current-regulated arc modulator was investigated with a focus on its role in initiating and sustaining plasma discharge within the Magnetron Body of the LINAC system. The analysis centered on how switching components, circuit topology, and feedback loop architecture influence critical factors such as energy efficiency, discharge stability, and long-term plasma containment. Particular attention was given to variations in pulse termination behavior, as observed through oscilloscope traces, which revealed inconsistencies affecting the duty factor and cathode temperature. These fluctuations have downstream effects on the cesium-coated cathode surface, thereby impacting H⁻ ion production and beam reliability. Simulation-based testing in LTspice was used to evaluate noise suppression techniques and arc current regulation schemes, revealing how optimized snubber networks, improved pulse shaping, and feedback stability can mitigate modulator-induced noise. The results ide

Campos, Nathan↗
DOE OSTI2025

Use of Frit‐Disc Crucible Sets to Make Solution Growth More Quantitative and Versatile

The recent availability of step‐edge, frit‐disc crucible sets (generally sold as Canfield Crucible Sets or CCS) has led to multiple innovations associated with the group's use of solution growth. The use of CCS allows for the clean separation of liquid from solid phases during the growth process. This clean separation enables the reuse of the decanted liquid, either allowing for simple, economic, savings associated with recycling expensive precursor elements or allowing for the fractionation of a growth into multiple, small steps, revealing the progression of multiple solidifications. Clean separation of liquid from solid phases also allows for the determination of the liquidus line (or surface) and the creation, or correction, of composition–temperature phase diagrams. The reuse of clean decanted liquid has also allowed to prepare liquids ideally suited for the growth of large single crystals of specific phases by tuning the composition of the melt to the optimal composition for growth of the desired phase, often with reduced nucleation sites. Finally, it is discussed how solution growth and CCS use can be harnessed to provide a plethora of composition–temperature data points defining liquidus lines or surfaces with differing degrees of precision to either test or anchor artificial intelligence and/or machine‐learning‐based attempts to augment and extend the limited experimentally determined database.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Perspectives and challenges of ultra-high temperature ceramics for fusion plasma-facing applications

Ultra-high temperature ceramics (UHTCs) offer several potential advantages as plasma-facing components (PFCs) in fusion reactors due to their extreme melting points, tailorable thermal conductivity, and attractive unirradiated mechanical properties including fracture toughness comparable or superior to tungsten. Here, recent developments and material properties of UHTCs are briefly reviewed, along with an overview of limited studies on their responses to neutron irradiation and an evaluation of plasma-surface interactions. Five key research pathways, primarily focused on irradiation effects, for advancing UHTCs in PFC applications are discussed: (1) assessing irradiation effects on the coupled thermal–mechanical performance (2) addressing the lack of studies on irradiation, plasma-surface interactions, and their synergistic effects; (3) investigating high-temperature (>1000 °C) neutron irradiation effects critical for PFC performance; (4) optimizing multi-component UHTC compositions or composites to improve thermal or mechanical properties; (5) enhancing radiation resistance to mitigate microcracking and void swelling through strategies such as increasing sink strength by reducing grain size, introducing fine particles, and leveraging complex concentrated alloy concepts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electron cyclotron emission detection of neoclassical tearing modes for control for ITER

Successful operation of ITER requires control of magnetic instabilities including neoclassical tearing modes (NTMs) that can degrade confinement and lead to disruption. Low latency detection by electron cyclotron emission (ECE) diagnostics has been demonstrated in a few current experiments. Using a synthetic diagnostic, we demonstrate low latency NTM detection for ITER with plasmas described by ITER IMAS database scenarios and with realistic limitations imposed on the instrumentation by these high temperature scenarios. 2/1 NTMs are detected 430 ms after magnetic island seeding and before island locking. The radiometer configuration was optimized using simulation, and the smallest detectable island size was explored. Island sizes of ∼3 cm are detectable at the 2/1 surface. The simulated signals incorporate recent physics models for island growth and rotation, which show early locking and continued island growth after locking and before disruption. This work determines limits for ITER ECE spatial resolution imposed by relativistic broadening of channels, which informs hardware design. Real-time detection is demonstrated in hardware that is required by ITER, including on an NI PXI-7853R FPGA system. Development of a synthetic diagnostic and details of the hardware will be discussed.

Cyclotron radiation↗
DOE OSTI2024

Symmetry breaking of fluorophore binding to a G-quadruplex generates an RNA aptamer with picomolar K D

Fluorogenic RNA aptamer tags with high affinity enable RNA purification and imaging. The G-quadruplex (G4) based Mango (M) series of aptamers were selected to bind a thiazole orange based (TO1-Biotin) ligand. Using a chemical biology and reselection approach, we have produced a MII.2 aptamer–ligand complex with a remarkable set of properties: Its unprecedented K D of 45 pM, formaldehyde resistance (8% v/v), temperature stability and ligand photo-recycling properties are all unusual to find simultaneously within a small RNA tag. Crystal structures demonstrate how MII.2, which differs from MII by a single A23U mutation, and modification of the TO1-Biotin ligand to TO1-6A-Biotin achieves these results. MII binds TO1-Biotin heterogeneously via a G4 surface that is surrounded by a stadium of five adenosines. Breaking this pseudo-rotational symmetry results in a highly cooperative and homogeneous ligand binding pocket: A22 of the G4 stadium stacks on the G4 binding surface while the TO1-6A-Biotin ligand completely fills the remaining three quadrants of the G4 ligand binding face. Similar optimization attempts with MIII.1, which already binds TO1-Biotin in a homogeneous manner, did not produce such marked improvements. We use the novel features of the MII.2 complex to demonstrate a powerful optically-based RNA purification system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Optimization of Ag Electrocatalyst Performance for CO2 to CO Conversion: Pairing Atomic Simulations with Experiments

Density-functional theory- based calculations that complement our series of experimental efforts on optimizing Ag electrocatalyst performance for CO2 to CO conversion were presented. Three key findings are drawn out from the combined UHV surface science, STM and electrochemical measurements: (1) Using a series of Ag nanoparticles with 2-6 nm average diameters, CO2 reduction reaction (CO2RR) activity increases, with particle between 2 nm and ∼4 nm demonstrating the highest combination of activity and selectivity; (2) Electronic metal−support interactions (EMSIs) between Ag and C dramatically improve CO2RR performance as evidenced by a scaling relationship between particle size and the relative Ag−C EMSIs strength, which improves the CO2-to-CO Faradaic efficiency of sub-2 nm Ag particles from 2 to ∼100% and increases the CO turnover frequency ∼15-fold compared with similarly sized bare Ag particles; (3) The performance Ag electrocatalysts is improved when supported on S-doped C materials. Computational modeling of 1−10 nm Ag particles predicts a nearly identical size-dependent trend with maximum CO2RR activity predicted for 3.7nm particles. The calculations support the promotional effect of C materials, showing a large charge transfer of 1.02 e from Ag clusters to defective C and a 0.41 eV less endergonic step of forming COOH intermediate on Ag/defective-C compared to the Ag/C system. Calculations indicate a more favorable energetic pathway of CO2-to-CO at the C-S-Ag interface, consistent with experiments.

CO2 utilization↗
DOE OSTI2025

Impact of CuInP 2 S 6 –metal interfaces on the stabilization of polar phases and polarization switching

The multifunctionality of two-dimensional ferroelectric CuInP 2 S 6 (CIPS) arises from the existence of multiple polar phases combined with a high ionic conductivity that facilitates polarization switching in unusual ways. The van der Waals (vdW) layered structure provides ultrathin flakes and ideal interfaces to integrate with other materials for microelectronics and neuromorphic elements. However, device integration necessitates metal contacts to read, write, or transmit signals. In this work, we find that different types of metal–CIPS interfaces strongly impact the stabilization of specific polar phases and the field-induced transitions between the polarization states. Cu electrodes initially suppress the piezoresponse, whereas, at CIPS–Ag interfaces, the electromechanical signal is increased. Under electric fields, the Cu electrodes, Ag electrodes and surrounding CIPS surfaces can show distinct switching behavior as different phases and polarization orientations are stabilized. These findings highlight that metal–CIPS interfaces provide the opportunity to optimize functional material properties.

Ferroelectrics and multiferroics↗
DOE OSTI2025

Three-Dimensional Heat Flux and Thermal Analysis of Angled Tungsten Samples on DIII-D

ITER-grade tungsten and dispersoid-strengthened tungsten samples with the top surface angled at ~15° towards the incident plasma flux were exposed to 9 H-mode discharges with edge-localized modes (ELMs) in the lower divertor of DIII-D tokamak using the Divertor Material Evaluation System (DiMES). Surface damage included cracking and flaking of material on the two samples farthest away from the plasma strike point, and significant melting of the two samples closest to the strike point. Heat flux and thermal analysis tools new to DIII-D have been applied to better understand this material response and to help optimize the exposure conditions for future experiments. SMITER field-line tracing simulations based on IRTV data and EFIT equilibria estimate an average inter-ELM perpendicular heat flux, 𝑞⊥,𝑖nter−𝐸LM , on the angled surfaces of 10.1 – 19.6 MW/m² for a majority of the 9 discharges, increasing to 15.6 – 24.5 MW/m² for the single, higher-power shot where samples melted. Fast camera data showed shallow intra-ELM melting and re-solidification, which transitioned to bulk inter-ELM melting with melt motion in the 𝐽⃗ 𝑥 𝐵⃗ direction. About 50% of the protruding volume of the most affected sample was displaced via melt-motion. SIERRA thermal modeling software was able to reproduce an onset time of melting consistent with fast camera data and final sample conditions, within < 200 ms. Maximum surface temperatures of 3122 K and 2787 K are estimated for the samples farthest away from the strike point, while the closest samples achieve melting at 4067 ms and 4750 ms into the ~5000 ms plasma exposure. A +10% increase in both the SMITER 𝑞⊥,𝑖nter−𝐸LM calculations and the estimated ELM heat loads 𝑞⊥, 𝐸LM was required to achieve this result, which is within the uncertainty of the diagnostic data but likely accounts for non-ideal geometry effects plus other physics uncertainties not included in this first iteration of modeling. This work provided valuable estimates of the 3D temperature evolution to help better understand the observed surface morphology and internal recrystallization of samples, which are discussed in detail in a complementary manuscript [1]. Benchmarking efforts with more diagnosed DIII-D experiments are underway to further refine the SMITER and SIERRA models for DiMES. Future use of these tools will enable researchers to precisely target heat flux exposure conditions in DIII-D to test, but not exceed, the thermomechanical limitations of novel plasma-facing materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

In-situ hydrogen microstructural characterization of Si heterojunction passivation: Addressing V OC degradation and mitigation pathways

Si heterojunction (SHJ) solar cells have demonstrated record efficiency >27%, approaching the theoretical limit of ≈ 29%, primarily due to best surface/interface defect passivation provided by deposited thin layers of hydrogenated amorphous silicon (a-Si:H). Such excellent surface/interface passivation reduces recombination loss and result in >100 mV improvement of cell open circuit voltage (V OC ) to ≈ 750 mV, thus the cell efficiency. However, fielded SHJ modules exhibit loss of V OC and hence efficiency over time in years, presumably due to degradation related to a-Si:H layers. This adversely affects the technology’s market acceptance, and levelized cost of energy (LCOE). It is hypothesized that the origin of a-Si:H degradation is somehow related to the presence of weak Si–Si bonds and hydrogen in a-Si:H films. The objective of this project is to test this hypothesis by directly measuring chemical and structural changes occurring within SHJ component layers and solar cells. This is achieved by developing an innovative in-situ Fourier transform infrared (FTIR) spectrometry apparatus to monitor hydrogen microstructural changes occurring within amorphous silicon and decipher hydrogen evolution kinetics over time when samples are exposed to heat and/or light stress. These in-situ measured hydrogen microstructural changes are correlated to the changes in effective minority carrier lifetime (τ eff ), implied V OC (iV OC ), surface recombination velocity (S), and cell V OC . These mechanistic understandings will provide critical guidance to mitigate the V OC -driven degradation of SHJ solar cell performance. Passivation optimization and degradation analysis of individual SHJ component structures were achieved through systematic deposition of three symmetric structures and the completed SHJ solar cell structure. The three symmetric structures used were intrinsic a-Si:H [(i)a-Si:H] layers in a bilayer structure, intrinsic and p-type doped stacked layers [(i-p)a-Si:H] representing the front heterojunction in the SHJ cell, and intrinsic and n-typed doped stacked layers [(i-n)a-Si:H] representing the back-side back surface field (BSF) in the SHJ cell. State-of-the-art passivation qualities are demonstrated by a champion iV OC of 740 mV for the (i)a-Si:H layers, and the (i-n)a-Si:H symmetric structure. A 725 mV iV OC is observed for the (i-p)a-Si:H symmetric structure. These symmetric passivated SHJ component structures were subsequently subjected to different accelerated lifetime (ALT) stressors to identify which conditions contribute the most to iV OC degradation. Degradation of the thin (10 nm) (i)a-Si:H passivation layers without any additional overlying layers is minimal; complexity of this study arises due to unavoidable surface oxidation of (i)a-Si:H layer during most of the stress application, which is likely irrelevant for a full SHJ cell configuration with overlying protective layers. The iV OC degradation of symmetric structures is found to occur primarily at the (i-p)a-Si:H passivation stack under dark heat stress with associated hydrogen loss from the (p)a-Si:H layer. An activation energy for increase in S (defect creation) of 0.65 eV can be correlated to the activation energy of ≈ 0.4 eV for hydrogen loss from the (i-p)a-Si:H stack. This also suggests the presence of weakly bonded hydrogen in the (p)a-Si:H films, which effuses out of the film stack at such low activation energy. When light and heat stress are applied together, similar hydrogen loss from (i-p)a-Si:H stack is observed, however, does not appreciably degrade iV OC or increase S. This is an important result and departure from direct correlation between hydrogen loss and defect creation. This perhaps indicates additional defect chemistries or annealing that might be occurring in the presence of light requiring further detailed defect measurements. The full SHJ cell structure used for this project is depicted in Fig.1(d). SHJ cells with an initial V OC ≈ 700 mV were fabricated and subjected to similar ALT stress conditions. Cell V OC is found to degrade the most under dark heat stress and is confirmed by observed hydrogen migration out of the (i-p)a-Si:H stack. However, hydrogen cannot escape from the cell stack, it accumulates near the (p)a-Si:H/ITO contact interface, where ITO acts as a barrier preventing hydrogen loss. Furthermore, light-heat combined stress does not degrade V OC appreciably, confirming the occurrence of a defect annealing process.

14 SOLAR ENERGY↗