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At least 487 records · Page 27

Effect of Thermal Aging on Microstructure and Stress Corrosion Cracking Behavior of an Alloy 152 1st Layer Butter Weldment

Nickel-based Alloy 690 and the associated weld Alloys 52 and 152 are typically used for nozzle penetrations in replacement heads for pressurized water reactor (PWR) vessels, because of their excellent overall resistance to general corrosion and environmental degradation, primarily stress corrosion cracking (SCC). However, many of the existing PWRs are expected to operate for 40- 80 years. Likewise, water-cooled small modular reactors (SMRs) will use Ni-Cr alloys and are expected to receive initial operating licenses for 60 years. Hence, the thermal stability of Ni-Cr alloys is critical for the long-term performance of both existing and advanced nuclear power plants, and possibly spent fuel storage containers. The objective of this research is to understand the microstructural changes occurring in high-Cr, Ni-based Alloy 152 weldments during long time exposure to the reactor operating temperatures, and the effect of these changes on the service performance. One area of particular concern is the potential for long range ordering (LRO), i.e. formation of the intermetallic Ni2Cr phase under prolonged exposure to reactor temperatures and/or irradiation, which can increase strength, decrease ductility, and cause dimensional changes or lead to in-service embrittlement of components made with these alloys. Hence, this research focused on the microstructural evolution and the SCC response of Alloy 152 under accelerated thermal aging. The materials studied involved three heats of Alloy 152 used to produce a dissimilar metal weld (DMW) joining an Alloy 690 plate to an Alloy 533 low alloy steel (LAS) plate, thermally aged at three different temperatures (370°C, 400°C and 450°C) for different durations up to 75,000h (equivalent to 60 years of reactor service). The microstructural characterization by means of synchrotron X-ray conducted in small, 0.2 mm - step line scans in the high-deformation regions of the weld root – covering areas spanning from the weld heat affected zone (HAZ) in Alloy 690 to the weld and weld butter on LAS - did not show evidence of LRO in any of the three Alloy 152 heats aged at 370°C and 450°C to an equivalent of 60 years of service. However, the first weld butter layer has high levels of deformation and is highly susceptible to SCC even in its non-aged condition. Nanohardness testing confirmed the extreme hardening with aging (ΔHV ≅ 100) at two locations within this weldment. In absence of LRO, hardening is suspected to be due to thermally-induced Cr carbide precipitation and coarsening. Testing in a primary water environment of the 1st layer of Alloy 152 weld butter aged at 370°C to a 60-year service equivalent revealed a fatigue and corrosion fatigue crack growth responses similar to those measured on the un-aged alloys. Similarly, the SCC CGR response of the aged weld butter does not appear to show a deterioration in performance, however, the difficult-to-test weldment geometry may affect the test results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling Oxygen Partial Pressure in Solid Oxide Electrolysis Cells: The Microstructure Effect

Oxygen partial pressure is an important thermodynamic state variable that affects both the performance and degradation of solid oxide electrolysis cells. In this work, a 3D model developed from Virkar’s 1D model has been applied to reconstructed and synthetic microstructures of Ni-YSZ-GDC-LSCF cell. The effect of the microstructures, including the thickness of the YSZ and GDC layer, and the compositions of the hydrogen and oxygen electrode, on the distribution of oxygen partial pressure has been investigated. The results show that the maximum oxygen partial pressure may occur on the interface between oxygen electrode and GDC layer or between GDC layer and YSZ layer depending on the rate of oxygen ion exchange between GDC and YSZ. A thicker GDC layer lowers the maximum oxygen partial pressure in the cell, while a thicker YSZ layer lowers the maximum oxygen partial pressure in the hydrogen electrode. In addition, the Ni:YSZ ratio and porosity also affects the maximum partial pressure. These findings provide insights on mitigating degradation in solid oxide electrolysis cell by tuning the microstructures.

Lei, Yinkai↗

Microstructural evaluation of the creep behavior in L-PBF Ni-based superalloys

This presentation at ICAM 2024 Conference focuses on the commonalities and differences in the creep rupture behavior and creep mechanisms for three distinct classes of laser powder-bed fusion (L-PBF) Ni-based superalloys (γ’-precipitate strengthened Haynes® 282®, γ’/γ”/δ-precipitate strengthened Alloy 718, and solid-solution strengthened Alloy 625) as compared to conventionally processed counterparts. A comparison of Larson-Miller parameter plots establishes that these alloys perform statistically within the bounds established for the wrought product, despite having dissimilar microstructural features and other artefacts associated with PBF-LB manufacturing and post-processing heat treatment. To understand the failure and the impact of composition, minor phases, and deformation defects on creep behavior, the fractography has been performed and microstructures have been evaluated in detail with SEM-EDS, EBSD, and HAADF-STEM. The underlying diffusional and dislocation creep mechanisms associated with this microstructural evaluation is discussed. This work is supported by NETL-FWP-1022408 Advanced Turbines.

Sudbrack, Chantal↗

Assessment of Microstructure Prediction Capabilities for Powder Bed Fusion Stainless Steel 316

The Advanced Materials and Manufacturing Technologies program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. However, the characteristic process-structure-property relationships of additive manufacturing (AM) materials pose challenges for the qualification and certification of AM nuclear components. In particular, component-scale variations in microstructure and properties can be driven by localized changes in melt pool dynamics due to how process parameters interact with different part geometries. Computational modeling tools can play a crucial role in predicting and controlling this variability. This report presents final results on process modeling tools designed to predict microstructure variability in additively manufactured stainless steel 316 parts. It details the software packages and physical modeling approaches employed to simulate an AM component within an automated process modeling workflow. Results are demonstrated through comparisons between predicted microstructures and experimental measurements across various representative processing conditions. The report concludes by discussing identified challenges and future opportunities for connecting the developed simulation workflow with mechanics simulations for prediction of part performance.

36 MATERIALS SCIENCE↗

Ultra-Fast Laser Fabrication of Alumina Micro-Sample Array and High-Throughput Characterization of Microstructure and Hardness

In the light of recent advances in material informatics, there is a great demand for high-throughput approaches of sample fabrication and property characterization. Currently, no high-throughput approach has been demonstrated for the fast sampling of the microstructure and the correlated properties. In this paper, we demonstrate the ultra-fast fabrication of an alumina sample array and the high-throughput hardness characterization of these sample units. The alumina sample array was fabricated using picosecond (PS) laser micromachining and CO2 laser sintering within a short time (i.e., less than a few minutes). After laser sintering, the hardness of these sample units was characterized using micro-indentation, and the microstructure was observed using scanning electron microscopy (SEM). In each sample unit, the microstructure was uniform for the entire top surface and within about 20 µm depth from the top surface. The relative density (RD) and corresponding micro-hardness of the sample units was found to continuously vary over a wide range from 89% RD with 600 kgf/mm2 hardness to 99% RD with 1609 kgf/mm2 hardness. For these laser-sintered samples, the correlation of hardness and relative density of the alumina matched well with the literature reports on sintered alumina obtained using conventional low-throughput furnace sintering experiments.

36 MATERIALS SCIENCE↗

Predicting Mechanical Properties from Microstructure Images in Fiber-Reinforced Polymers Using Convolutional Neural Networks

Evaluating the mechanical response of fiber-reinforced composites can be extremely time-consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input–output pairs and have exhibited success in composite research. This paper explores a fully convolutional neural network modified from StressNet, which was originally used for linear elastic materials, and extended here for a non-linear finite element (FE) simulation to predict the stress field in 2D slices of segmented tomography images of a fiber-reinforced polymer specimen. The network was trained and evaluated on data generated from the FE simulations of the exact microstructure. The testing results show that the trained network accurately captures the characteristics of the stress distribution, especially on fibers, solely from the segmented microstructure images. The trained model can make predictions within seconds in a single forward pass on an ordinary laptop, given the input microstructure, compared to 92.5 h to run the full FE simulation on a high-performance computing cluster. These results show promise in using ML techniques to conduct fast structural analysis for fiber-reinforced composites and suggest a corollary that the trained model can be used to identify the location of potential damage sites in fiber-reinforced polymers.

Sun, Yixuan (ORCID:0000000311093380)↗

The Effect of Interlayer Delay on the Heat Accumulation, Microstructures, and Properties in Laser Hot Wire Directed Energy Deposition of Ti-6Al-4V Single-Wall

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process–structure–property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process–structure–property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

36 MATERIALS SCIENCE↗

In Situ Prediction of Microstructure and Mechanical Properties in Laser-Remelted Al-Si Alloys: Towards Enhanced Additive Manufacturing

Laser surface remelting of aluminum alloys has emerged as a promising technique to enhance mechanical properties through refined microstructures. This process involves rapid cooling rates ranging from 10 3 to 10 8 °C/s, which increase solid solubility within aluminum alloys, shifting their eutectic composition to a larger value of silicon content. Consequently, the resulting microstructure combines a strengthened aluminum matrix with silicon fibers. This study focuses on the laser scanning of Al-Si aluminum alloy to reduce the size of aluminum matrix spacings and transform fibrous silicon particles from micrometer to nanometer dimensions. Analysis revealed that the eutectic structure contained 17.55% silicon by weight, surpassing the equilibrium eutectic composition of 12.6% silicon. Microstructure dimensions within the molten zones, termed ‘melt pools’, were extensively examined using Scanning Electron Microscopy (SEM) at intervals of approximately 20 μm from the surface. A notable increase in hardness, exceeding 50% compared to the base plate, was observed in the melt pool regions. Thus, it is exemplified that laser surface remelting introduces a novel strengthening mechanism in the alloy. Moreover, this study develops an in situ method for predicting melt pool properties and dimensions. A predictive model is proposed, correlating energy density and spectral signals emitted during laser remelting with mechanical properties and melt pool dimensions. This method significantly reduces characterization time from days to seconds, offering a streamlined approach for future studies in additive manufacturing.

36 MATERIALS SCIENCE↗

Microstructure of Neutron-Irradiated Al 3 Hf-Al Thermal Neutron Absorber Materials

A thermal neutron-absorbing metal matrix composite (MMC) comprised of Al 3 Hf particles in an aluminum matrix was developed to filter out thermal neutrons and create a fast flux environment for material testing in a mixed-spectrum nuclear reactor. Intermetallic Al 3 Hf particles capture thermal neutrons and are embedded in a highly conductive aluminum matrix that provides conductive cooling of the heat generated due to thermal neutron capture by the hafnium. These Al 3 Hf-Al MMCs were fabricated using powder metallurgy via hot pressing. The specimens were neutron-irradiated to between 1.12 and 5.38 dpa and temperatures ranging from 286 °C to 400 °C. The post-irradiation examination included microstructure characterization using transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy. This study reports the microstructural observations of four irradiated samples and one unirradiated control sample. All the samples showed the presence of oxide at the particle–matrix interface. The irradiated specimens revealed needle-like structures that extended from the surface of the Al 3 Hf particles into the Al matrix. An automated segmentation tool was implemented based on a YOLO11 computer vision-based approach to identify dislocation lines and loops in TEM images of the irradiated Al-Al 3 Hf MMCs. This work provides insight into the microstructural stability of Al 3 Hf-Al MMCs under irradiation, supporting their consideration as a novel neutron absorber that enables advanced spectral tailoring.

36 MATERIALS SCIENCE↗

The Influence of Microstructure on TCR for Inkjet-Printed Resistive Temperature Detectors Fabricated Using AgNO 3 /Ethylene-Glycol-Based Inks

This study investigated the influence of microstructure on the performance of Ag inkjet-printed, resistive temperature detectors (RTDs) fabricated using particle-free inks based on a silver nitrate (AgNO 3 ) precursor and ethylene glycol as the ink solvent. Specifically, the temperature coefficient of resistance (TCR) and sensitivity for sensors printed using inks that use monoethylene glycol (mono-EG), diethylene glycol (di-EG), and triethylene glycol (tri-EG) and subjected to a low-pressure argon (Ar) plasma after printing were investigated. Scanning electron microscopy (SEM) confirmed previous findings that microstructure is strongly influenced by the ink solvent, with mono-EG inks producing dense structures, while di- and tri-EG inks produce porous structures, with tri-EG inks yielding the most porous structures. RTD testing revealed that sensors printed using mono-EG ink exhibited the highest TCR (1.7 × 10 -3 /°C), followed by di-EG ink (8.2 × 10 -4 /°C) and tri-EG ink (7.2 × 10 -4 /°C). These findings indicate that porosity exhibits a strong negative influence on TCR. Sensitivity was not strongly influenced by microstructure but rather by the resistance of RTD. The highest sensitivity (0.84 Ω/°C) was observed for an RTD printed using mono-EG ink but not under plasma exposure conditions that yield the highest TCR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing Microstructure-induced Swelling & Thermal Property Changes in Ion-Irradiated Oxide Fuels using Laser-generated Surface Acoustic Waves

Radiation of fuel rods with neutrons during a fission reaction in a nuclear reactor is known to affect the material microstructure of the fuel as a result of fission fragment damage, and lead to the formation of atomic-level defects such as voids, dislocation loops, and lattice swelling from fission-gas release. A consequence of the radiation-induced damage in nuclear fuels is the drastic alteration of material properties, in particular, the reduction of the thermal conductivity – a key parameter that governs the transport of thermal energy released from fissile fuel atoms to the surrounding coolant. Swelling can induce high stresses and ultimate failure of the cladding. A fundamental understanding of the role of radiation-induced damage on the thermal transport and mechanical properties of nuclear fuels is therefore critical for efficient, reliable and safe operation of a nuclear power plant. As opposed to conventional post-irradiation examination techniques that are often time-consuming and require significant sample preparation, laser-based characterization methods have emerged as promising non-contact, non-destructive tools to measure the evolution of microstructure-induced material property changes. Moreover, laser methods offer the promise of in-situ characterization while the material is being irradiated. This project aims to develop an improved understanding of the impact of radiation-induced changes to material microstructure on the thermal and elastic properties of nuclear materials. A laser ultrasonic technique, known as the transient grating (TG) spectroscopy method, is used to simultaneously measure thermal diffusivity and elastic properties in unirradiated and ion-irradiated oxide nuclear fuel samples. The results will complement on-going investigations on electron- and phonon-mediated thermal transport in nuclear materials and will provide foundational work for incorporating the influence of defects in fuel performance codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Microstructural characterization of nuclear graphite: from the microscale to the nanoscale

Multiple reactor designs use graphite as a moderator of the nuclear reactions and as structural support. During the lifetime of the reactor, multiple aging factors such as neutron irradiation, oxidation, and temperature along with others induce changes in the microstructure and crystal lattice of graphite components. The pore morphology and crystal structure of some phases in graphite can be used to trace the evolution of irradiation defects and mechanical properties of graphite. We present a combination of results from several microscopy techniques to investigate the differences between nuclear graphite grades and the effects of neutron irradiation and oxidation at multiple length scales. This multiscale approach is needed to understand the microstructural variations caused by the raw materials and manufacturing processes as well as how the different phases of graphite are affected by the reactor environment. The results provide insight into the oxidation- and radiation-induced changes of graphite and create a robust baseline of microstructure information that can be used for the selection of materials for the next generation of nuclear power stations. Moreover, the experiments conducted in this work provide an overview of the advantages and limitations of the most common techniques used to characterize nuclear graphite and how these techniques might be applied to study other carbon-based materials used in the nuclear industry.

Arregui Mena, Jose'↗

Microstructural Topology as a Prescriptor for Quantum Coherence: Towards A Unified Framework for Decoherence in Superconducting Qubits

In superconducting quantum circuits, decoherence improvements are frequently obtained through process interventions that simultaneously modify surface chemistry, microstructural topology, and device geometry, leaving mechanistic attribution structurally underdetermined. Predictive materials engineering requires measurable structural statistics to be separated from geometry-dependent coupling coefficients into independently testable factors. We introduce the concept of classical and quantum microstructure. In that context, we formulate a channel-wise separable framework for decoherence in superconducting transmon qubits in which each loss channel is described by a reduced prescriptor. Here, a channel-specific microstructural state variable is determined independently of device geometry, and a geometry-dependent coupling functional is computable from field solutions without reference to surface chemistry. We derive this product form from a spatially resolved kernel representation and establish a perturbative separability criterion that defines the regime where independent variation of the variables is valid. The framework specifies five prescriptor classes for dominant loss pathways in transmon-class devices. Falsifiability is operationalized through a pre-committed 2x2 experimental protocol in which the variables must satisfy independent ratio checks within propagated uncertainty. A Minimum-Dataset Specification standardizes reporting for cross-laboratory inference. Part I establishes the conceptual and mathematical architecture; coordinated experimental validation is reserved for Part II.

Dravid, Vinayak P. [Northwestern U.]↗

Microstructural Characterization of AGR-2 TRISO-coated Particle Buffer, IPyC, and Buffer-IPyC Interfaces

Investigating the microstructural, mechanical, and chemical behaviors of Tristructural Isotropic (TRISO) fuel particles is vital for its qualification and use in advanced reactors. Central to the study of TRISO particles is understanding the silicon carbide (SiC) layer's ability to confine fission products, with failure mechanisms linked to chemical degradation following mechanical degradation of the buffer and IPyC layers. Research has been done to quantify the micro-tensile properties of the buffer, inner pyrolytic carbon (IPyC), and buffer-IPyC interlayer regions and their interactions within both irradiated and un-irradiated TRISO particles. Techniques such as atom probe tomography (APT) and transmission electron microscopy (TEM) have also been deployed to examine microstructural defects and fission product distribution in detail. The goal is to understand layer delamination, establish connections between microstructure and mechanical attributes, and inform computational predictions of fuel performance. This work may help refine predictive models of TRISO fuel behavior and facilitating its certification for use in advanced reactors.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Anisotropic physics-regularized interpretable machine learning of microstructure evolution

Anisotropic Physics-Regularized Interpretable Machine Learning Microstructure Evolution (APRIMME) is a general-purpose machine learning solution for grain growth simulations. In prior work, PRIMME employed a deep neural network to predict site-specific migration as a function of its neighboring sites to model normal, isotropic, grain growth behavior. This work aims to extend this method by incorporating grain boundary misorientation-based grain growth behavior. APRIMME is trained on anisotropic simulations created using the Monte Carlo-Potts (MCP) model. Furthermore, the results of this work are compared statistically using grain radius, number of sides per grain, mean neighborhood misorientations, and the standard deviation of triple junction dihedral angles, and are found to match in most cases. The exceptions are small and seem to be related to two causes: (1) the deterministic model of APRIMME is learning from the stochastic simulations of MCP, which seems to accentuate triple junction behaviors; and, (2) a bias against very small grains is made evident in a quicker decrease in grains than expected at the beginning of an APRIMME simulation. APRIMME is also evaluated for its general ability to capture anisotropic grain growth behavior by first investigating different test case initial conditions, including a circle grain, three grain, and hexagonal grain microstructures.

36 MATERIALS SCIENCE↗

SOC Microstructural Property Estimator

This pre-trained ML model is a tool that uses basic compositional parameters for porous solid oxide cell (SOC) electrodes - the phase fractions and mean particle/pore diameters – as inputs and uses them to estimate additional electrochemical performance parameters: active (i.e., connected) TPB density, all tortuosity factors, and phase pair specific interfacial areas. The electrode is assumed to be composed of two solid phases and a pore phase. The property calculations are performed using neural network regression models trained on a large bank of synthetic electrode microstructural data that NETL has generated using the program DREAM3D (that bank is also hosted on EDX: https://edx.netl.doe.gov/dataset/soc-synthetic-microstructure-bank). This means the generated parameters are based on training from actual measured properties from 3D microstructures, not estimated from geometric simplifications. This tool was developed and is intended to replace percolation theory calculations in models that use hypothetical electrode properties. An example use case would be running SOC performance simulations across a parametric sweep of electrode designs (e.g., varying phase fractions and particle sizes) and assessing how it impacts the electrochemical performance of the SOC. Within the parameter space of the training data (statistics of that parameter space is provided in the readme file), this model achieves sub-5% mean absolute percent errors, an order of magnitude less error than percolation theory across the same parameter space. However, be aware that this tool was developed with parametric simulations in mind, and users are encouraged to assess accuracy for their own specific use case rather than taking accuracy metrics at face value. More info, including a usage guide, is in the included readme file. This tool should be cited with the DOI number provided.

Electrode Microstructure↗

Passivation‐Induced Species Dynamics and Microstructural Evolution in Solid‐State Lithium–Sulfur Cathodes

Solid-state lithium–sulfur (SSLS) batteries offer high theoretical energy density, yet their practical viability is hindered by poor sulfur utilization and limited rechargeability. At the core of this challenge lies the passivating nature of Li 2 S, which restricts ionic and electronic transport, suppresses interfacial activity, and severely impedes the reversibility of electrochemical reactions. In this study, we elucidate the mechanistic origins of these limitations by resolving how charge and discharge species form, grow, and spatially evolve within the cathode microstructure under varied current densities and electrode compositions. By resolving the species distribution at the particle scale and coupling it with Raman spectroscopy and X-ray diffraction, we demonstrate how Li 2 S formation induces localized surface passivation that progressively limits electrochemical accessibility within the cathode microstructure. Sulfur utilization is found to be strongly governed by the interplay between sulfur loading, residual porosity, and interfacial architecture. High sulfur contents result in buried, electrochemically isolated domains due to poor solid electrolyte (SE) percolation, while low sulfur contents trigger SE degradation via parasitic reactions. The resulting sulfur-porosity maps delineate the mechanistic boundaries between reversible and transport-limited regimes, offering actionable design guidance for SSLS cathodes with enhanced sulfur utilization.

electrode microstructure↗

Microstructure of Methylammonium Lead iodide Perovskite Thin Films: A Comprehensive Study of the Strain and Texture

Controlling the microstructure of hybrid halide perovskite thin films is essential for optimizing their performance in optoelectronic devices. It is well established that the strain state of the perovskite layer affects its stability. Likewise, the orientation of the perovskite lattice is a determining parameter as these materials have shown pronounced anisotropies in their physical and mechanical properties. In this work, the authors focus on the understanding of the mechanisms that govern the strain and texture observed in MAPbI 3 thin films deposited on various oxide substrates. A thorough study of the evolution of the strain of the perovskite layer upon cooling down to room temperature from the crystallization temperature (100 °C) shows an essentially relaxed behavior of the perovskite layers. This result contradicts the commonly accepted hypothesis according to which MAPbI 3 layers synthesized above ambient temperature are strained due to the large mismatch in the thermal expansion coefficients of the perovskite and its substrate. The texture in MAPbI 3 layers is investigated by means of synchrotron full-field diffraction X-ray microscopy. This technique allows the direct observation of the [hh0] and [00l]-oriented domains at the origin of the observed textures, demonstrating both their twin and ferroelastic nature. The stability of the different domain orientations is investigated by DFT calculations, illustrating the determining role of the chemical environment at the film-substrate interface. PbI 2- terminated surfaces are found to favor the [hh0] orientations while for MAI-terminated ones, both [hh0] and [00l] domains are equally stabilized. The different results constitute an important step of clarification and understanding from the perspective of controlling the microstructure of perovskite layers.

36 MATERIALS SCIENCE↗