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At least 19 records

Numerical design considerations for vapor transport deposition of metal-halide perovskite thin films

While metal-halide perovskites (MHPs) offer high efficiency and potential application in single junction and tandem solar cells, challenges remain in translating solution-based methods to commercial-scale production. Vapor transport deposition (VTD) offers advantages such as precise control over film composition and purity, as well as the possibility of achieving high thin film deposition rates for scale-up. In this work, a numerical model is developed to simulate the deposition process, analyzing the impact of parameters including source material temperature, carrier gas and dilution gas flow rates, and chamber pressure to optimize deposition rates and film uniformity. Geometrical parameters, such as throw distance, are also found to significantly affect rate and uniformity. Furthermore, the modeling results presented here offer valuable insight for improving the scalability of VTD for the processing of metal-halide perovskites.

Chemical vapor deposition

The mechanism of hydroxyapatite coatings degradation at high substrate temperatures

Physical vapor deposition methods used for hydroxyapatite (HA) coatings typically require elevated substrate temperatures and post-deposition annealing to induce crystallization. However, such thermal treatments can degrade both the mechanical integrity and bioactivity of the coating, particularly when substrate temperatures exceed 500 °C. The mechanisms underlying these phenomena remain insufficiently understood. In this study, HA thin films were deposited on silicon and Ti6Al4V substrates using pulsed laser deposition and were systematically characterized to elucidate these mechanisms. XPS and SIMS analyses revealed a temperature-dependent loss of OH − and PO 4 3− groups, an increased Ca/P ratio, and the formation of interfacial oxides, all of which contribute to weakened adhesion. To clarify the temperature-dependent decline in bioactivity, protein adsorption behavior was analyzed using a Kramers-type kinetic framework; the fitted desorption kinetics indicate that coatings deposited near ∼500 °C provide the most stable protein attachment, whereas higher temperatures accelerate desorption due to dehydroxylation and carbonate substitution. Together, these findings provide mechanistic insight into the thermal degradation of HA coatings and offer a framework for optimizing deposition parameters to preserve stoichiometry, adhesion, and bioactivity for long-term biomedical applications.

Kylychbekov, Salizhan [Univ. of Oxford (United Kin

Nb 3 Sn coating of SRF cavity by cosputtering from a composite target

Here, we deposited an Nb 3 Sn film on the inner surface of a 2.6 GHz Nb superconducting radio frequency cavity by cosputtering using a composite of Nb and Sn tube targets in a DC cylindrical magnetron sputtering system, followed by the thermal annealing of the coated cavity. An aluminum mockup cavity, replicating a 2.6 GHz Nb SRF cavity geometry, was utilized to optimize deposition parameters, resulting in cosputtered Nb–Sn films with an Sn content of 32–42 at. % on the beam tubes and equator positions. Several annealing conditions were investigated to improve the surface homogeneity of the Nb 3 Sn film. The best cosputtered Nb–Sn film was achieved after annealing at 600 °C for 6 h, followed by annealing at 950 °C for 1 h. The best process was applied to a Nb cavity, which was RF tested in a cryogenic dewar. RF testing of the Nb 3 Sn-coated cavity demonstrated a superconducting transition temperature of 17.78 K. The Nb 3 Sn cavity underwent light Sn recoating, followed by additional RF testing, resulting in the enhancement of the RF performance, primarily due to the improved surface homogeneity of the Nb 3 Sn coating.

Nb3Sn film

Temperature‐Dependent Crystallization in Two‐Step Perovskite Deposition Revealed by In Situ GIWAXS and Machine Learning‐Guided Analysis

The performance and stability of perovskite solar cells are strongly governed by the crystallization behavior of their active layer. In two-step sequential deposition, early-stage film formation plays a decisive role in determining final phase purity and device quality. Guided by a data-driven analysis of nearly 39 000 devices in the FAIR perovskite database, we identified solvent-mediated quenching and thermal processing as key variables affecting power conversion efficiency (PCE), particularly in two-step fabrication. Here, to investigate these effects in real time, we designed and implemented a custom-built, temperature-controlled spin-coating system, enabling precise thermal modulation during precursor deposition. Using this platform, we performed in situ GIWAXS measurements to study the crystallization dynamics of FA 0.5 MA 0.5 PbI 3 films over a temperature range of 30°C–90°C. Our results reveal a non-monotonic relationship between spin-coating temperature and α-phase formation, governed by the interplay between precursor interdiffusion, PbI 2 crystallinity, and δ-phase suppression. The custom thermal control enabled us to isolate and quantify these competing effects during the earliest stages of film formation, providing mechanistic insight into how spin-coating temperature governs both phase purity and kinetic pathways in two-step perovskite systems. Temperature-dependent SEM and photovoltaic device measurements further demonstrate that early-stage crystallization pathways directly translate into differences in morphology, charge-transport continuity, and device performance. These findings inform targeted strategies for optimizing deposition protocols to balance rapid nucleation, phase stability, and device performance.

Saadawy, Ahmed [King Fahd University of Petroleum

Assessment of Blocking Contacts in Suppressing Polarization Effects in CsPbBr 3 Perovskite Detectors

The CsPbBr 3 perovskite has garnered significant attention as a room-temperature semiconductor for hard radiation detection due to straightforward synthesis, scalable crystal growth, low cost, and excellent energy resolution. However, despite these advantages, at ambient temperature, CsPbBr 3 devices may experience performance deterioration and irreversible failure due to “polarization” induced by electromigration of ions to electrical connections on the device. In this study, we tested several contact materials and their optimization deposition techniques to assess the stability of high-performance CsPbBr 3 γ-ray detectors. Metals, with low work functions (Ti, In, Sn, Sb, Pb, Bi, Al, Au, and TiC) and high-work-function (Au or Pt) contacts, were used to form different Schottky junctions using vacuum thermal evaporation, electron-beam evaporation, and sputtering methods. These detectors were tested in intermittent and continuous modes to assess their stability. Among the tested detectors, the Bi/CLB/Pt electrode configuration demonstrated superior stability, operating effectively for 11 months under periodic testing and 16 days under continuous testing. In contrast, other configurations functioned only for a few months under intermittent conditions. Upon incorporating a ~40-nm-thick TiC passivation layer on the anode side (Bi/TiC/CLB/Pt), the CLB device operated continuously for 36 days without degradation. In many cases, the failure mode of the devices was due to the degradation of the anode. Here, the chemical changes in the fresh and deteriorated anodes were characterized using scanning electron microscopy and energydispersive X-ray spectroscopy

CsPbBr3 perovskite

Co-sputter deposition of Nb₃Sn layer into SRF cavity using Nb-Sn composite target

Nb₃Sn, with its superior superconducting critical temperature (Tc ~18.3 K) and superheating field (Hsh ~400 mT), is considered a promising material for superconducting radiofrequency (SRF) cavities, offering enhanced cryogenic performance compared to bulk niobium cavities. A Nb₃Sn coating technique has been developed for Nb SRF cavities using co-sputtering of Nb-Sn composite target in a DC cylindrical magnetron sputtering system. The composite target configuration and discharge conditions for co-sputtering were optimized to deposit Nb-Sn films on flat Nb substrates, followed by annealing to form Nb₃Sn. Multiple strategies have been explored to improve the surface homogeneity of the Nb₃Sn coating, including optimizing a two-step annealing process, annealing in Sn vapor, and a light Sn recoating process. A 1.5 µm Nb-Sn co-sputtered film was deposited on the interior of a 2.6 GHz Nb SRF cavity and annealed at 600 °C for 6 h, followed by 950 °C for 1 h. Cryogenic RF testing of the annealed cavity demonstrated a Tc of 17.8 K, confirming the formation of Nb₃Sn. Then, the annealed cavity underwent a light recoating treatment and attained a quality factor (Q0) of 8.5E+08 at 2.0 K.

Accelerator Physics

Surrogate models to optimize plasma-assisted atomic layer deposition in high aspect ratio features

In this work, we explore surrogate models to optimize plasma enhanced atomic layer deposition (PEALD) in high aspect ratio features. In plasma-based processes such as PEALD and atomic layer etching (ALE), surface recombination can dominate the reactivity of plasma species with the surface, which can lead to unfeasibly long exposure times to achieve full conformality inside nanostructures like high aspect ratio vias. Using a synthetic dataset based on simulations of PEALD, we train artificial neural networks to predict saturation times based on cross section thickness data obtained for partially coated conditions. The results obtained show that just two experiments in undersaturated conditions contain enough information to predict saturation times within 10% of the ground truth. A surrogate model trained to determine whether surface recombination dominates the plasma–surface interactions in a PEALD process achieves 99% accuracy. This demonstrates that machine learning can provide a new pathway to accelerate the optimization of PEALD processes in areas such as microelectronics. Our approach can be easily extended to ALE and more complex structures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Multi-physics melt pool modeling and process optimization for laser direct energy deposition of Nb-based refractory C103: Defect formation, geometric precision, and process mapping

Recent developments in additive manufacturing (AM) technology have reignited interest in the fabrication of the Nb-based refractory C103 alloy offering solutions to the challenges posed by traditional manufacturing methods. However, the limited numerical and experimental studies on laser direct energy deposition (DED) of C103 have hindered the understanding of the relationships between process parameters and build quality. This has made it challenging to consistently produce parts with the desired quality and microstructure suitable for critical applications. In this study, we focus on optimizing the laser DED process for C103 by employing a hybrid approach that combines experimental techniques and computational fluid dynamics (CFD). This approach facilitates the development of process maps for defect detection and geometric precision. To achieve this, multi-layer C103 samples were fabricated using laser DED under various process parameters, enabling the creation of a process map for defect detection. Additionally, a multi-physics, multiphase simulation framework was developed within a high-performance computing (HPC) environment to establish process maps for geometric precision. Using these process maps, printability windows were identified for achieving both the desired geometric accuracy and defect-free prints. It was observed that prints with a power-to-velocity (P/V) ratio close to unity resulted in defect-free outcomes. This study provides a foundation for reducing design lead time and rejected parts, ultimately optimizing the laser DED process for C103.

Defect formation and geometric precision

Establishing Pb-203 production from electrodeposited Tl targets at Brookhaven National Laboratory

Background: Promising developments in Pb-212 radiopharmaceutical therapies have increased demand for Pb-203 diagnostic agents. Building on previous work from various isotope production facilities, this study optimized Pb-203 production from electrodeposited Tl targets at Brookhaven National Laboratory (BNL). The additional supply of Pb-203 may help meet growing preclinical and clinical demands. Results: Two Tl targets were irradiated at the Brookhaven Linac Isotope Producer facility with 30 ± 1 MeV protons, measured using previously published cross section data. Distribution coefficients for Pb Resin in acetate media were investigated for both Na + and K + cations, where potassium acetate was ~ 4 times more effective at stripping Pb from the Pb Resin. The Tl electrodeposition was optimized to deposit 350 mg of Tl (~ 60 mg/cm 2 ) on Au backing in under 6 h. The proposed separation process was completed in < 1.5 h and achieved > 98% and 92 ± 3% recovery of Tl and Pb, respectively, with an overall Tl-Pb separation factor of 6 × 10 5 . The experimentally measured half-life of Pb-203 was 52.4 ± 0.7 h, agreeing with 51.93 ± 0.02 h reported by the National Nuclear Data Center. The radioisotopic purity of the Pb fraction at 24 h post end of bombardment (EOB) from a 24 h irradiation was 66% Pb-203, 28% Pb-201, and 6% Pb-200. Following chemical separation, the Pb-203 produced in this work (21 MBq Pb-203 EOB) achieved apparent molar activities of 10 ± 5 and 0.9 ± 0.5 GBq/µmol for [ 203 Pb]Pb-DOTAM and [ 203 Pb]Pb-DO3A, respectively, decay corrected to EOB. Data derived from this work suggests BNL can produce > 10’s GBq Pb-203 with > 99% radiochemical and radioisotopic purity from Tl-205 for worldwide distribution. Conclusions: The production and separation of Pb-203 from natural Tl target material was successfully demonstrated at BNL. Existing methods were adapted and optimized for the facilities at BNL. Results from this work will guide future large-scale Pb-203 production opportunities at BNL for clinical applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA

Interactive multiscale modeling to bridge atomic properties and electrochemical performance in Li-CO 2 battery design

Li-CO 2 batteries are promising energy storage systems due to their high theoretical energy density and CO 2 fixation capability, relying on reversible Li 2 CO 3 /C formation during discharge/charge cycles. Here, we present a multiscale modeling framework integrating Density Functional Theory (DFT), Ab-Initio Molecular Dynamics (AIMD), classical Molecular Dynamics (MD), and Finite Element Analysis (FEA) to investigate atomic and cell-level properties. The considered Li-CO 2 battery consists of a lithium metal anode, an ionic liquid electrolyte, and a carbon cloth cathode with Sb 0.67 Bi 1.33 Te 3 catalyst. DFT and AIMD determined the electrical conductivities of Sb 0.67 Bi 1.33 Te 3 and Li 2 CO 3 using the Kubo–Greenwood formalism and studied the CO 2 reduction mechanism on the cathode catalyst. MD simulations calculated the CO 2 diffusion coefficient, Li + transference number, ionic conductivity, and Li + solvation structure. The FEA model, parameterized with atomistic simulation data, reproduced the available experimental voltage–capacity profile at 1 mA/cm 2 and revealed spatio-temporal variations in Li 2 CO 3 /C deposition, porosity, and CO 2 concentration dependence on discharge rates in the cathode. Accordingly, Li 2 CO 3 can form large and thin film deposits, leading to dispersed and local porosity changes at 0.1 mA/cm 2 and 1 mA/cm 2 , respectively. The capacity decreases exponentially from 81,570 mAh/g at 0.1 mA/cm 2 to 6200 mAh/g at 1 mA/cm 2 , due to pore clogging from excessive discharge product deposition that limits CO 2 transport to the cathode interior. Therefore, the performance of Li-CO 2 batteries can be improved by enhancing CO 2 transport, regulating Li 2 CO 3 deposition, and optimizing cathode architecture.

Battery performance

Optimized NiTe 2 /Ni back contacts via chemical deposition for high performance CdTe solar cells

The development of efficient and stable back contacts remains a major challenge in achieving high performance and long-term stability of CdTe thin-film solar cells. Here, this work revisits the formation of NiTe 2 by chemical bath deposition (CBD) as a back contact for CdTe devices. An optimized CBD recipe, based on high-purity precursors and the addition of copper chloride directly into the bath, was developed and applied to fabricate Cu-doped CdTe solar cells. A modified Cu-free methodology was also applied to Group V doped absorbers. The process included pinhole filling, ion milling, CBD, annealing, and sputtering to form a low-barrier back contact. Devices fabricated using this method achieved consistent open-circuit voltages (V oc ) above 800 mV and fill factors (FF) exceeding 70%. The best Cu-doped devices reached power conversion efficiencies (PCE) above 18 %, and preliminary results with Group V-doped material demonstrated compatibility of the method with high-efficiency, state-of-the-art CdTe devices. This study shows that NiTe 2 /Ni back contacts, formed via an optimized chemical process followed by sputtering of Ni, represent a promising pathway for achieving low-barrier and potentially stable back contacts in modern CdTe photovoltaics.

14 SOLAR ENERGY

High-Energy and High-Power NMP-Free, Designer NMC 811 Cathodes with Ultra-Thick Architectures Processed by Electrophoretic Deposition

This project focused on electrode engineering and reducing the weight of inactive components in the battery cells. Additionally, the project focused on optimizing the ‘electrophoretic deposition’ technique developed by PPG industries for aqueous processing of electrodes. During this project team has screened several binders suitable for electrophoretic deposition of electrodes. Additionally, we developed a nice strategy to deposit a low cost and scalable oxide coating on the surface of cathode materials. ORNL team performed the research under this CRADA at DOE’s Battery Manufacturing Facility (BMF) at ORNL.

99 GENERAL AND MISCELLANEOUS

High-Energy and High-Power NMP-Free, Designer NMC 811 Cathodes with Ultra-Thick Architectures Processed by Electrophoretic Deposition

This project focused on electrode engineering and reducing the weight of inactive components in the battery cells. Additionally, the project focused on optimizing the ‘electrophoretic deposition’ technique developed by PPG industries for aqueous processing of electrodes. During this project team has screened several binders suitable for electrophoretic deposition of electrodes. Additionally, we developed a nice strategy to deposit a low cost and scalable oxide coating on the surface of cathode materials. ORNL team performed the research under this CRADA at DOE’s Battery Manufacturing Facility (BMF) at ORNL.

25 ENERGY STORAGE

Polarized Photocathodes development for the EIC: Optimizing Spin and Quantum Efficiency

GaAs/GaAsP superlattice photocathodes play a critical role for producing highly polarized electron beams for the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. The electron pre-injector for the EIC requires electron bunches with high bunch charge (1-2 nC) and high polarization, from GaAs-based superlattice photocathode. Herein, we have systematically investigated a range of GaAs/GaAsP superlattice photocathodes fabricated via molecular beam epitaxy (MBE) and metal-organic chemical vapor deposition (MOCVD). Through optimization of pre-cleaning procedures and surface doping conditions, we aim to identify the most promising photocathode configurations for future EIC operations. To enhance the quantum efficiency (QE), a Distributed Bragg Reflector structure is frequently incorporated beneath the superlattice. While this approach effectively increases QE, it also introduces additional complexities that can adversely influence spin polarization and the spectral response at specific laser wavelengths. This note provides an overview of superlattice GaAs development and outlines the EIC team’s ongoing efforts to address related challenges and advance high-performance photocathode development tailored for the EIC. Over five years of multi-institutional collaboration and measurements of about 50 SL-GaAs samples, our analysis presents statistics on samples exhibiting high ESP and high QE. It will help to set the initial ESP requirements for the EIC project.

43 PARTICLE ACCELERATORS

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry

Rapid Screening of Single-Atom Catalyst Synthesis Conditions Using ToF-SIMS and Facet-Dependent Single-Crystal Substrates

Single-atom catalysts (SACs) offer superior catalytic performance compared to traditional nanoparticle catalysts but are challenging to develop because of the need for extensive optimization and specialized characterization techniques. Here, this study presents a rapid and versatile method for detecting synthesis conditions and elucidating deposition mechanisms of SACs on various substrates. By depositing active elements (Au, Cu, Ni and Rh) on facet-specific single-crystalline substrates (CeO 2 , TiO 2 , MgO and Al 2 O 3 ) and employing time-of-flight secondary ion mass spectroscopy (ToF-SIMS), we assessed facet-dependent deposition behaviors and identified optimal conditions for solution-based SAC synthesis. On CeO 2 and TiO 2 , we confirmed facet-dependent deposition, primarily influenced by oxygen vacancy density and photocatalytic activity, respectively. MgO exhibited the formation of metal oxide/hydroxide clusters for all active elements, and the degree of clustering for Cu and Ni was correlated with the facet hydrolysis susceptibility. Notably, Au and Rh deposition on MgO was facet-independent, attributed to the formation of hydroxide species in solution. Al 2 O 3 , due to its chemical stability and lack of surface defects, did not show active element deposition. This study not only provides a time and cost-efficient method for prescreening SAC synthesis conditions, but it also provides valuable insights into the various deposition mechanisms governing SAC formation on different substrates, paving the way for the rational design of tailored SACs for various catalytic applications.

ToF-SIMS

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE

Scalable Solution-Processed Electrolyte Membranes with Optimized Microstructure for High-Performance Protonic Ceramic Electrochemical Cells

Proton-conducting electrochemical cells (PCECs) are promising for efficient hydrogen production, but achieving dense, uniform, thin electrolyte layers remains a key challenge, particularly for scalable fabrication. Here, we present a solution-processed deposition approach with a mechanistically optimized slurry for uniform electrolyte formation. By tailoring particle size distribution, solid loading, and solvent/additive balance, we regulated wetting behavior and evaporation kinetics of the electrolyte slurry to promote homogeneous electrolyte particle packing. These features facilitate tight grain boundary contact and early stage neck growth during sintering, eliminating residual porosity, and improving mechanical integrity. The resulting ∼15 μm thick electrolyte shows high density, strong electrode adhesion, and stable interfaces outperforming the previously reported spray-based fabricated electrolyte by about 31% at 600 °C in FC mode. Single cells deliver 0.962 W cm –2 at 600 °C in fuel cell mode and 1.31 A cm –2 at 1.3 V in electrolysis mode, maintaining robust performance over 100 h with negligible degradation (≤0.02% h –1 ) in each mode. Scale-up to 2.5 cm diameter substrates confirmed reproducible densification and geometric stability. This work demonstrates a cost-effective, scalable route where control over particle-fluid interactions and drying dynamics enables a superior electrolyte microstructure and high PCEC performance.

dense microstructure