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DOE OSTI2022

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗

DOE OSTI2024

A semi–automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves

Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

A Technique for the Quantitative Characterization of Weld Microstructure and Application to Mo Welds

The choice of weld parameters determines the size, shape, and curvature of grains in the fusion zone (FZ) and heat-affected zone (HAZ) of welds while the mechanical properties of the welds are correlated to this microstructure. Here, a new technique to quantitatively evaluate these microstructural characteristics in both zones of welds has been applied to molybdenum gas tungsten arc welds fabricated using different weld parameters. Trends in microstructural characteristics in the FZ and HAZ were evaluated and correlated with changes to heat input, weld speed, and weld technique. The use of this approach showed that a 20 pct decrease in heat input caused a 20 pct decrease in the number of FZ grains with aspect ratios ≥ 4. The orientations of the FZ grain segments as a function of distance from the FZ centerline were significantly affected by the weld speed and its effect on weld pool shape. A 50 pct increase in weld speed caused a 20 pct decrease in grain segments orientated 60 to 90 deg from the normal to the direction of welding. This technique also captured differences in grain sizes and grain size anisotropy in the FZ between welds made with a constant current, pulsed current, and use of a 4-pole-magnetic oscillator.

36 MATERIALS SCIENCE↗

DOE OSTI2022

An investigation of the multi-mode Richtmyer-Meshkov instability at a gas/HE interface using Pagosa

Here, in this work, we present a hydrocode Pagosa and explore the Richtmyer-Meshkov Instability (RMI) at an air/high explosive (HE) interface for the first time that is important but has not received much attention yet in the high explosive safety field. Thus, the presented Pagosa can be expected to predict the whole deflagration-to-detonation transition (DDT) process in future. In Pagosa, spatial discretization is implemented on cubic staggered grids by computing different variables at the vertex and the cell center, respectively, a special operator-splitting technique is employed to reduce the computational cost, and an artificial viscosity is added to handle the discontinuous shock waves in our simulations. To quantitatively evaluate the capability of Pagosa to solve these kinds of instabilities, the single mode Rayleigh-Taylor instability (RTI) and the multimode RMI at an air/SF 6 interface are first performed, respectively. The Pagosa results are compared with the related numerical solutions in the existing references and the experimental result. Moreover, a theoretical derivation of growth of RTI is also provided based on our numerical method. Subsequently, we explore the multi-mode RMI at an air/HE interface as well as the effects of several factors using Pagosa. Numerical results show that Pagosa is a powerful toolset to generate the right structures and the amplitude of RTI and RMI at an air/SF 6 interface. The solid HE can be penetrated by a strong shock wave and forms RMI deformations. The RMI at an air/HE interface behaves very different than at an air/SF 6 interface, periodic, decreased oscillation is observed due to material character, and is very sensitive to the initial simulation settings, that is, a tiny change in physical quantities will lead to a remarkable RMI structure, which is also observed in a shock bubble interaction. The findings in this work are significant, and will present a new insight for the high explosive field.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Corrosion of rebar in concrete. Part III: Artificial Neural Network analysis of chloride threshold data

Active corrosion of carbon steel in reinforced concrete occurs when the chloride ion concentration exceeds the chloride threshold (CT). CT is affected by many physical and chemical parameters including primary variables (pH, corrosion potential, breakdown potential, and temperature) and secondary variables (cemenet composition, concreete porosity, and water/cement ratio). A Kohonen-self organized map (KSOM) and regression artificial neural network (ANN) coupled methodology was developed to find the missing values of independent variables in the sparse database and for quantitatively evaluating the effects of these variables on CT values that are expressed in %TotalCl/cem (or %FreeCl/cem), and [Cl - ]/[OH - ].

36 MATERIALS SCIENCE↗

DOE OSTI2020

Unraveling Na and F coupling effects in stabilizing Li, Mn-rich layered oxide cathodes via local ordering modification

Regardless of the prevailing capacity and energy density of lithium, manganese-rich layered oxide (LMR-NMC) cathodes, continuous decay of voltage and overall energy density during cycling hinders this material from commercialization in Li-ion batteries. Although significant work focuses on single doping of Na and F, analysis in portraying the benefit of these ions in diminishing the structural distortion during activation cycle is in doubt. In this study, the effects of co-doping Na and F into the LMR-NMC structure in stabilizing the structure and mitigating oxygen loss during the first cycle are closely examined via in situ x-ray measurements. Na and F co-doping shows a 30% lower degree of Li + /Ni 2+ mixing in the Li layer (C2/m structure), 50% reduced Debye-Waller factor of Mn-O bonding, increase reversible TM migration, and faster Li diffusion relative to the pristine material. Due to the utilization of Ni redox chemistry below 4.4 V, less oxygen redox is required for charge compensation at high voltage. This study offers the first instance to quantitatively evaluate the effects of co-doping Na and F in LMR-NMC cathode in order to minimize voltage degradation by altering the local ordering of O3-type structure, which may rationalize strategies to overcome the issues of the material.

25 ENERGY STORAGE↗

DOE OSTI2026

Discovery of nanopore filling by gypsum in wellbore cement exposed to 17 MPa CO 2 under geologic carbon storage conditions

Here, this study investigates the pore structure evolution of the reaction zones in wellbore cement samples exposed to a CO 2 -rich solution in equilibrium with 17 MPa supercritical CO 2 over 14 days. Through advanced characterization methods of field emission SEM, Quantitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN), and micro-CT, a new mechanism of CO 2 -cement reaction involving filling of nanopores in the interior of cement by gypsum was revealed. Gypsum was formed by the liberation of SO 4 2− from ettringite (AFt) and monosulfate (AFm) caused by a decrease in pH. Based on these experimental observations, a new CO 2 -cement reaction model that incorporates four distinct reaction zones is developed. This model provides a comprehensive framework for understanding the spatial and temporal distribution of minerals in cement due to high pressure CO 2 —cement reactions. This study demonstrates that the major damage induced by high pressure CO 2 alteration occurs in the most exterior region of the cement. The interior region of the cement maintains its integrity due to nanopore filling by gypsum.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Thermal Processing Conditions for the Synthesis of Near Theoretical Density Li 5 La 3 Ta 2 O 12 Ceramics for Ceramic Dual-Mode Detectors

A family of Li-containing garnet compounds, extensively investigated for Li-ion solid electrolyte applications, show great potential to be developed into transparent ceramic dual-mode scintillators. In particular, Li 5 La 3 Ta 2 O 12 (LLTaO) shows promise as an efficient dual-mode scintillator due to its high Li content, high density, non-hygroscopicity, and high effective-Z. Often the synthesis of LLTaO ceramics involves solid state processing techniques starting with oxide and carbonate powders, calcining, sintering for the removal of residual porosity, and post-processing. This study focuses on two objectives: (1) establishing thermal processing boundary conditions for a flexible alkoxide-based sol-gel method for synthesizing fine-grained powders; and (2), consolidating powders via hot-pressing to form high-density ceramics. In this study, near single-phase ceramics were achieved by hot-pressing sol-gel powders with varying amounts of excess Li. Rietveld refinements were used to analyze X-ray diffraction data and provide a quantitative evaluation of the phases present in the hot pressed ceramics. Some of the diffraction data showed large low angle peak asymmetry, suggesting the presence of two cubic Li 5 La 3 Ta 2 O 12 garnet phases with different lattice parameters. Depending on the synthesis and processing conditions, the refinement revealed ~ 90 wt% concentration of a phase with a ≈ 12.8 Å and ~ 10 wt% concentration of a phase with a ≈ 12.9 Å, indicating a remaining excess of Li in the hot pressed ceramics in the large lattice parameter phase. These synthesis experiments allowed for the determination of a baseline for Li loss during hot-pressing. X-ray excited radioluminescence and photoluminescence excitation and emission spectra were obtained from the hot pressed ceramics. In conclusion, the measured emission spectra featured broad tantalate emission and line emissions likely from a rare-earth impurity.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Parameterization of the Stoner-Wohlfarth model of magnetic hysteresis

The Stoner-Wohlfarth (SW) is the most used model of magnetic hysteresis, but its computation is time-consuming. We approximate piecewise this model by easy-to-compute analytic functions. Overall, our parametrization is suitable for fast quantitative evaluations and fitting experimental data, which we exemplify. Applicability of this parametrization is as broad as that of the SW model, which can be extended to include more parameters.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Single particle impact explorations on the role of powder heat treatments in cold spray: Effects of strength and oxide structure

In cold spray, the optimization of the powder feedstock for improving the final properties of the coating and for improving the process itself are two different objectives. This paper explores the latter, studying the relationship between powder pre-heat treatment and the kinetic bonding between the individual particles and the substrate. Using a laser-induced particle impact test (LIPIT), we investigate the effect of different heat treatments on the critical adhesion velocity of Al 6061. Although heat treatments change the strength of the powders as well as the thickness of the native oxide layer each by as much as ∼50 %, the critical adhesion velocity remains constant to within only ∼10 %. A deeper analysis reveals that these two factors change in somewhat complementary ways for the heat treatments explored here, leading to counteracting effects. By quantitatively evaluating these two microstructural factors in tandem, we find that they are roughly equally important in determining the critical adhesion velocity. These observations thus provide insight for the development of new heat treatment regimens that might lower the adhesion velocity.

Al 6061↗

DOE OSTI2021

In-situ ion irradiation study of alloy 709 stainless steels with different processing histories

Alloy 709 stainless steel (A709 SS) has gained an increased interest in nuclear applications due to its advanced properties at high temperatures over the widely used Type 316 SS. However, how this alloy behaves under irradiation with concurrent environmental factors, such as mechanical deformation and/or thermal annealing, has not been studied. In this work, we used in-situ ion irradiation inside a transmission electron microscope (TEM) to investigate the effects of irradiation on the microstructures of A709 SS samples with different prior processing histories, including as-received, annealed, and creep-deformed. It was found that, compared to room temperature irradiation, 600 degrees C irradiation led to larger dislocation loop sizes and lower loop densities. Furthermore, with 600 degrees C irradiation, the creep-deformed sample, which had the highest precipitate density and the highest dislocation density, had the smallest loop size and the lowest loop density compared to others. This observation has been rationalized with quantitative evaluation of the sink strength factors in each sample. This study shows that in-service deformation can significantly affect the irradiation performance in structural materials at reactor operating conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Mechanical properties and strengthening mechanisms of cold sprayed Al-Mg alloys

This paper investigates the mechanical properties and strengthening mechanisms of cold sprayed Al-Mg alloys as a function of Mg content. Cold spray (CS) is a solid-state deposition process that can be used as a repair technique for structural components. However, the limited ductility of cold sprayed materials is an unsettled issue in CS community. Herein, reproducible, and significantly increased elongation to failure (∼15%) in as-deposited conditions is reported in CS Al-Mg binary alloys with low Mg content (≤ 2.5 wt%). Furthermore, reducing Mg content down to 2.5 wt% in CS Al-Mg binary alloys demonstrated comparable mechanical strength to its wrought counterparts. Strengthening mechanisms were analyzed in wrought and CS Al-Mg alloys based upon microstructural characteristics, such as grain size, Mg solute concentration, and dislocation density. A quantitative evaluation of yield strength revealed that grain boundary strengthening is predominant in CS Al-Mg alloys as compared with their wrought counterparts. When comparing among CS Al-Mg binary alloys of different compositions, Mg solute concentration, and dislocation density governed mechanical strength. In conclusion, the underlying mechanism for the variation of mechanical properties and strengthening mechanisms is discussed in terms of these microstructural characteristics.

Additive manufacturing↗

DOE OSTI2025

Decoupling thermal and irradiation effects on grain boundary segregation

Radiation-induced segregation (RIS) is most often measured by peak solute concentration at a boundary. However, this may give an incomplete picture of segregation quantity and phenomena. Radiation-induced and thermal segregation at grain boundaries was investigated in Fe-9.6 at.% Cr after 9 MeV Fe 3+ ion irradiation at 400 °C. The experimental results were compared to kinetic Monte Carlo (KMC) simulations. The study revealed that Cr enrichment (peak segregation) at the grain boundaries was comparable in both the irradiated and non-irradiated conditions, although irradiation resulted in broader segregation profiles in both experiments and simulations, indicating an overall increase in grain boundary segregation due to irradiation. This broadening is attributed to back diffusion into the grain interior. While it is an established phenomenon, this study offers a quantitative evaluation using experimental data and KMC modeling. Further, these results emphasize the importance of analyzing the entire segregation profile and decoupling the thermal and irradiation contributions to solute segregation.

Grain boundary segregation↗

DOE OSTI2021

A systems engineering framework for the optimization of food supply chains under circular economy considerations

The current linear “take-make-waste-extractive” model leads to the depletion of natural resources and environmental degradation. Circular Economy (CE) aims to address these impacts by building supply chains that are restorative, regenerative, and environmentally benign. This can be achieved through the re-utilization of products and materials, the extensive usage of renewable energy sources, and ultimately by closing any open material loops. Such a transition towards environmental, economic and social advancements requires analytical tools for quantitative evaluation of the alternative pathways. Here, in this work, we present a novel CE system engineering framework and decision-making tool for the modeling and optimization of food supply chains. First, the alternative pathways for the production of the desired product and the valorization of wastes and by-products are identified. Then, a Resource-Task-Network representation that captures all these pathways is utilized, based on which a mixed-integer linear programming model is developed. This approach allows the holistic modeling and optimization of the entire food supply chain, taking into account any of its special characteristics, potential constraints as well as different objectives. Considering that typically CE introduces multiple, often conflicting objectives, we deploy here a multi-objective optimization strategy for trade-off analysis. A representative case study for the supply chain of coffee is discussed, illustrating the steps and the applicability of the framework. Single and multi-objective optimization formulations under five different coffee-product demand scenarios are presented. The production of instant coffee as the only final product is shown to be the least energy and environmental efficient scenario. On the contrary, the production solely of whole beans sets a hypothetical upper bound on the optimal energy and environmental utilization. In both problems presented, the amount of energy generated is significant due to the utilization of waste generated for the production of excess energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Exciton Delocalization in Indolenine Squaraine Aggregates Templated by DNA Holliday Junction Scaffolds

Exciton delocalization plays a prominent role in the photophysics of molecular aggregates, ultimately governing their particular function or application. DNA is a compelling scaffold in which to template molecular aggregates and promote exciton delocalization. As individual dye molecules are the basis of exciton delocalization in molecular aggregates, their judicious selection is important. Motivated by their excellent photostability and spectral properties, here we examine the ability of squaraine dyes to undergo exciton delocalization when aggregated via a DNA Holliday junction (HJ) template. A commercially available indolenine squaraine dye was chosen for the study given its strong structural resemblance to Cy5, a commercially available cyanine dye previously shown to undergo exciton delocalization in DNA HJs. Three types of DNA-dye aggregate configurations—transverse dimer, adjacent dimer, and tetramer—were investigated. Signatures of exciton delocalization were observed in all squaraine-DNA aggregates. Specifically, strong blue shift and Davydov splitting were observed in steady-state absorption spectroscopy and exciton-induced features were evident in circular dichroism spectroscopy. Strongly suppressed fluorescence emission provided additional, indirect evidence for exciton delocalization in the DNA-templated squaraine dye aggregates. To quantitatively evaluate and directly compare the excitonic Coulombic coupling responsible for exciton delocalization, the strength of excitonic hopping interactions between the dyes were obtained by simultaneous fitting the experimental steady-state absorption and CD spectra via a Holstein-like Hamiltonian in which, following the theoretical approach of Kühn, Renger, and May, the dominant vibrational mode is explicitly considered. The excitonic hopping strength within indolenine squaraines was found to be comparable to that of the analogous Cy5 DNA-templated aggregate. The squaraine aggregates adopted primarily an H-type (dyes oriented parallel to each other) spatial arrangement. Extracted geometric details of dye mutual orientation in the aggregates enabled close comparison of aggregate configurations and the elucidation of the influence of dye angular relationship on excitonic hopping interactions in squaraine aggregates. Furthermore, these results encourage the application of squaraine-based aggregates in next generation systems driven by molecular excitons.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Decoupling Carrier Dynamics and Energy Transport in Ultrafast Near-Field Nanoscopy

Ultrafast near-field optical nanoscopy has emerged as a powerful platform to characterize low-dimensional materials. While analytical and numerical models have been established to account for photoexcited carrier dynamics, quantitative evaluation of the associated pulsed laser heating remains elusive. Here, we decouple the photocarrier density and temperature increase in near-field nanoscopy by integrating the two-temperature model (TTM) with finite-difference time-domain (FDTD) simulations. These results reveal that the electron–phonon coupling in a silicon film after femtosecond laser excitation is most pronounced within approximately 3 ps–substantially shorter than the photocarrier decay time scale at tens of picoseconds. Moreover, the coupled TTM-FDTD method indicates that ultrafast laser heating can cause up to a 14% variation in the near-field signal at a 220 μJ/cm 2 pump pulse fluence. Our numerical results are further validated by transient experiments, highlighting the potential of this method for investigations of carrier and thermal phenomena in emerging nanomaterials and nanodevices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Controlling and Optimizing Photoinduced Charge Transfer across Ultrathin Silica Separation Membrane with Embedded Molecular Wires for Artificial Photosynthesis

Ultrathin amorphous silica membranes with embedded organic molecular wires (oligo( p -phenylenevinylene), three aryl units) provide chemical separation of incompatible catalytic environments of CO 2 reduction and H 2 O oxidation while maintaining electronic and protonic coupling between them. For an efficient nanoscale artificial photosystem, important performance criteria are high rate and directionality of charge flow. Here, the visible-light-induced charge flow from an anchored Ru bipyridyl light absorber across the silica nanomembrane to Co 3 O 4 water oxidation catalyst is quantitatively evaluated by photocurrent measurements. Charge transfer rates increase linearly with wire density, with 5 nm -2 identified as an optimal target. Accurate measurement of wire and light absorber densities is accomplished by the polarized FT-IRRAS method. Guided by density functional theory (DFT) calculations, four wire derivatives featuring electron-donating (methoxy) and -withdrawing groups (sulfonate, perfluorophenyl) with highest occupied molecular orbital (HOMO) potentials ranging from 1.48 to 0.64 V vs NHE were synthesized and photocurrents evaluated. Charge transfer rates increase sharply with increasing driving force for hole transfer from the excited light absorber to the embedded wire, followed by a decrease as the HOMO potential of the wire moves beyond the Co 3 O 4 valence band level toward more negative values, pointing to an optimal wire HOMO potential around 1.3 V vs NHE. Comparison with photocurrents of samples without nanomembrane indicates that silica layers with optimized wires are able to approach undiminished electron flux at typical solar intensities. Combined with the established high proton conductivity and small-molecule blocking property, the charge transfer measurements demonstrate that oxidation and reduction catalysis can be efficiently integrated on the nanoscale under separation by an ultrathin silica membrane.

photocurrent measurements↗

DOE OSTI2024

Understanding Process–Structure Relationships during Lamination of Halide Perovskite Interfaces

Fabrication of halide perovskite (HP) solar cells typically involves the sequential deposition of multiple layers to create a device stack, which is limited by the thermal and chemical incompatibility of top contact layers with the underlying HP semiconductor. One emerging strategy to overcome these restrictions on material selection and processing conditions is lamination, where two half-stacks are independently processed and then diffusion bonded to complete the device. Lamination reduces the processing constraints on the top side of the solar cell to allow new device designs, expanded use of deposition methods, and self-encapsulation of devices. While laminated perovskite solar cells with high efficiencies and novel interlayer combinations have been demonstrated, there is a limited understanding of how the lamination process parameters affect the diffusion-bond quality and material properties of the resulting HP layer. In this study, we systematically vary temperature, pressure, and time during lamination and quantify the resulting impacts on bonded area, grain domain size, and photoluminescence. A design of experiments is performed, and statistical analysis of the experimental results is used to quantitatively evaluate the resulting process–structure–property relationships. The lamination temperature is found to be the key parameter controlling these properties. Furthermore, a temperature of 150 °C enables successful bonding over 95% of the substrate area and also results in increases in apparent grain domain size and photoluminescence intensity. Based on these insights, the lamination temperature of functional perovskite solar cell devices is varied, demonstrating the importance of the resulting bond quality on device performance metrics.

14 SOLAR ENERGY↗