Multiphase Materials Research Articles

Reproducing hydrodynamics and elastic objects: A hybrid mesh-free model framework for dynamic multi-phase flows

Reproducing Hydrodynamics and Elastic Objects (RHEO) is a new meshfree modeling framework for simulating complex multi-phase flows of fluids and solids. RHEO is implemented within the open-source Large-Scale Atomic/Molecular Massively Parallel Simulator particle dynamics code and couples a reproducing kernel smoothed particle hydrodynamics scheme for modeling fluid flow and heat transfer with a bonded particle model for modeling breakable elastic bodies. The resulting scheme provides a robust framework for simulating multi-phase material systems with complex and evolving boundaries and interfaces. RHEO collects many advanced mesh-free modeling features into a centralized, modular, and easily extensible package, including heat transport, reversible melting and solidification, particle distribution regularization, and user adjustable kernel accuracy. We report comprehensive tests of RHEO's accuracy and convergence for common benchmark flows of bulk fluids, boundary driven flows, and complex fluid/solid systems. A series of multi-phase systems are highlighted, including a bouncing water balloon, the fracture and flow of a brittle egg, melting of a free-standing solid beam, and conductive cooling and solidification of an extruded polymer during 3D printing.

A finite element based approach for nonlocal stress analysis for multi-phase materials and composites

AbstractThis study proposes a numerical method for calculating the stress fields in nano-scale multi-phase/composite materials, where the classical continuum theory is inadequate due to the small-scale effects, including intermolecular spaces. The method focuses on weakly nonlocal and inhomogeneous materials and involves post-processing the local stresses obtained using a conventional finite element approach, applying the classical continuum theory to calculate the nonlocal stresses. The capabilities of this method are demonstrated through some numerical examples, namely, a two-dimensional case with a circular inclusion and some commonly used scenarios to model nanocomposites. Representative volume elements of various nanocomposites, including epoxy-based materials reinforced with fumed silica, silica (Nanopox F700), and rubber (Albipox 1000) are subjected to uniaxial tensile deformation combined with periodic boundary conditions. The local and nonlocal stress fields are computed through numerical simulations and after post-processing are compared with each other. The results acquired through the nonlocal theory exhibit a softening effect, resulting in reduced stress concentration and less of a discontinuous behaviour. This research contributes to the literature by proposing an efficient and standardised numerical method for analysing the small-scale stress distribution in small-scale multi-phase materials, providing a method for more accurate design in the nano-scale regime. This proposed method is also easy to implement in standard finite element software that employs classical continuum theory.

Synthesis of group-IV ternary and binary semiconductors using epitaxy of GeH3Cl and SnH4

Ge1−x−ySixSny alloys were grown on Ge buffers via reactions of SnH4 and GeH3Cl. The latter is a new CVD source designed for epitaxial development of group-IV semiconductors under low thermal budgets and CMOS-compatible conditions. The Ge1−x−ySixSny films were produced at very low temperatures between 160 and 200 °C with 3%–5% Si and ∼5%–11% Sn. The films were characterized using an array of structural probes that include Rutherford backscattering, x-ray photoelectron spectroscopy, high-resolution x-ray diffraction, scanning transmission electron microscopy, and atomic force microscopy. These studies indicate that the films are strained to Ge and exhibit defect-free microstructures, flat surfaces, homogeneous compositions, and sharp interfaces. Raman was used to determine the compositional dependence of the vibrational modes indicating atomic distributions indistinguishable from those obtained when using high-order Ge hydrides. For a better understanding of the growth mechanisms, a parallel study was conducted to investigate the GeH3Cl applicability for synthesis of binary Ge1−ySny films. These grew strained to Ge, but with reduced Sn compositions and lower thicknesses relative to Ge1−x−ySixSny. Bypassing the Ge buffers led to Ge1−ySny-on-Si films with compositions and thicknesses comparable to Ge1−ySny-on-Ge; but their strains were mostly relaxed. Efforts to increase the concentration and thickness of Ge1−ySny-on-Si resulted in multiphase materials containing large amounts of interstitial Sn. These outcomes suggest that the incorporation of even small Si amounts in Ge1−x−ySixSny might compensate for the large Ge–Sn mismatch by lowering bond strains. Such an effect reduces strain energy, enhances stability, promotes higher Sn incorporation, and increases critical thickness.

Non-local optical response of a multi-phased quantum material

Non-local optical response of a multi-phased quantum material

Experimental and 3D mesoscopic numerical simulation study of kinetic projectile penetrating into concrete

Concrete is a multiphase composite material composed of mortar, aggregate, and interface transition zone (ITZ). The mesoscopic components of concrete have an important influence on its anti-penetration performance. In this study, a series of penetration experiments with large-caliber ogive-nosed projectiles penetrating concrete targets are carried out. The test results show that the damage to the concrete target consists of crater and tunnel zones and increases with increasing impact velocity. Then, a local background grid method is proposed to establish a 3D mesoscopic model of concrete, based on the arrangement characteristics of the sequence number of the finite elements. Compared with the traditional 3D mesoscopic concrete modeling method, the proposed method can effectively improve the modeling efficiency. Subsequently, numerical simulations are performed based on the 3D mesoscopic model, with the simulation and experimental results in good agreement, verifying the effectiveness of the model. Finally, the verified 3D mesoscopic model is employed to investigate the effects of shape, volume fraction, size interval, and strength of the concrete aggregates on the depth of penetration (DOP) and deflection of the projectile. The simulation results indicate that the shape of the aggregate has a negligible effect on both uniaxial compressive strength and DOP. Therefore, spherical aggregates are used to improve modeling efficiency. Increasing the volume fraction and strength of the aggregates can significantly enhance the anti-penetration performance of concrete. The influence of aggregate size interval on DOP is slight, but it has a significant impact on projectile and trajectory deflection at the same aggregate volume fraction. The uneven lateral resistance on both sides of the projectile, caused by the random distribution of aggregates, is a major factor in deflection.

Probing the influence of composition and cross-linking degree on single-chain nanoparticles from poly(tetrahydrofuran-ran-epichlorohydrin) copolymers: Insights from neutron scattering, calorimetry, and dielectric spectroscopy

The industrial sector has made significant strides in the development of multicomponent and multiphasic polymer materials, including polymer blends, composites (such as nanocomposites), and various copolymers. Random copolymers, characterized by their statistical arrangement of repeating units, are particularly noteworthy due to their tunability from amorphous to semicrystalline states. In this study, we focus on poly(tetrahydrofuran-ran-epichlorohydrin) (P(THF-ran-ECH)) copolymers, which serve as precursors for single-chain nanoparticles (SCNPs). These SCNP-based materials are of particular interest as they bridge the gap between traditional polymers and colloids. This research comprehensively investigates how the type and degree of internal cross-linking influence the structure and dynamics of P(THF-ran-ECH) copolymers and their SCNPs. Techniques such as quasielastic neutron scattering (QENS), differential scanning calorimetry (DSC), and broadband dielectric spectroscopy (BDS) were employed to study copolymers with varying compositions and levels of cross-linking. By analyzing two samples with different epichlorohydrin (ECH) contents (13 mol% and 27 mol%), we aim to control crystallization and explore its effects on dynamic behavior. Our results show that both the composition and the degree of cross-linking significantly impact the dynamics of the SCNPs, with SCNPs exhibiting slower dynamics compared to their precursor copolymers. Furthermore, semicrystalline samples display faster dynamics in SCNPs than amorphous samples. These findings provide valuable insights for the design and optimization of advanced multicomponent polymer systems.

Incorporation of SnSe2/SnO2 heterostructures in carbon nanotubes for excellent lithium storage performance

As a new type of negative electrode material, tin-based material exhibits a high theoretical capacity. However, tin-based anode materials always undergo severe volume change upon alloying reaction during lithium insertion and extraction, which leads to the pulverization of the active materials and poor electrochemical performance, seriously hampering its practical application. In this work, oxygen-containing group functionalized carbon nanotubes (FCNTs) were facilely obtained, and the three-dimensional crosslinked SnSe2-SnO2@FCNTs multiphase materials were prepared by solvothermal and high-temperature heat treatment. The formation of Sn-O-C bonds from oxygen-containing functional groups of FCNTs combined with Sn can promote the electric connection and integrity of the composites. The implanted defects in FCNTs can not only be beneficial to anchoring SnO2 and SnSe2 nanoparticles, but also helpful to the penetration of Li+ ions into the electrodes from electrolyte. In addition, the large Fermi energy difference between SnSe2 and SnO2 nanoparticles results in the formation of a built-in electric field at the interface of the multiphase materials, accelerating the diffusion of ions. The smaller size of the multiphase materials leads to significant pseudocapacitive behavior, which facilitates the highly reversible surface/interface adsorption. Under the multiple effects of FCNTs, SnSe2, and SnO2, the SnSe2-SnO2@FCNTs multiphase materials exhibited excellent electrochemical performance. At a current density of 0.1A·g-1, a discharge specific capacity of 898.0mAh·g-1 was achieved. When the current density was increased to 2A·g-1, it still exhibited a discharge specific capacity of 443.9mAh·g-1. After a long charge/discharge cycling at 1A·g-1 over 450 cycles, it still showed a specific capacity of ~ 400mAh·g-1. This work significantly demonstrated the enhanced Li-storage performance of SnSe2-SnO2 heterostructures incorporated in the functionalized multi-walled CNTs. This opens a new way to synthesize advanced tin-based materials as high-performance anodes for high-energy density lithium-ion batteries.

A fine-segmentation algorithm for XCT images of multiphase composite building materials based on deep learning

In response to the challenges presented by the variable internal structures and complex components of multiphase composite building materials, this study introduces a novel image segmentation network named UT-FusionNet. Building on the U-Net model, UT-FusionNet integrates Transformer module and tensor concatenation and fusion mechanism to overcome the limitations of convolutional networks in relation to the receptive field. UT-FusionNet is employed to segment CT images of conventional concrete, grout consolidation bodies, and fiber-reinforced concrete. The results demonstrate that UT-FusionNet achieves superior segmentation accuracy and robustness, with Accuracy (ACC), Intersection over Union (IoU) and Dice scores exceeding 90 % across all subtasks. The mean accuracy metrics are 99.44 %, 96.70 %, and 98.31 %, respectively. This innovative end-to-end network offers robust support for detailed structural analysis, damage detection, and digital modeling of multiphase composite building materials through deep learning.

One-pot bioinspired synthesis of PbO/CuO/FeO trimetallic oxide nanocomposite using Vitis vinifera fruit juice for highly sensitive electrochemical detection of 4-Nitrotoluene

The determination of explosive nitroaromatic chemicals has prompted concerns about human safety around the world. In this work, we demonstrate an electrochemical sensor based on trimetallic oxide nanocomposites modified screen-printed carbon electrode (SPCE) for the detection of nitroaromatic compounds. Trimetallic oxide nanocomposites are multiphase materials containing ternary metal oxides. Because of their high specific surface area, superior electron transport capabilities, and favourable catalytic behaviour, they are frequently employed as antibacterial materials, catalysts, and sensors. In order to combat the problems associated with high manufacturing costs, low selectivity, and low sensitivity of conventional sensors, this paper reports on the construction of an electrochemical sensor for 4-nitrotoluene (4-NT) using a trimetallic oxide nano-sensor. The nano-sensor is composed of transition metal oxides copper and iron combined with post-transition lead metal oxide. In this study, we prepared a PbO/CuO/FeO TMO NCs sample with different individual metal oxides synthesized by a green reduction method using Vitis vinifera fruit juice. SEM was used to observe and validate structural and morphological variations brought on by various metal compositions. The four bio-synthesized materials comprise dispersed multiphase matrices containing varying shapes of nanoparticles with different morphologies. The elemental and phase arrangements of the synthesized samples were investigated employing UV, FT-IR, XRD, and EDAX approaches. The findings of the electrochemical measurements indicate that the SPCE modified with PbO/CuO/FeO TMO NCs has enhanced sensing capabilities over CuO, FeO, and PbO NPs for 4-NT; the limit of detection is 4.512 nM and sensitivity is −0.531 μA nM−1 for the developed sensor. Notably, recovery values (99.2–101.7 %) in water samples showed that evaluating interfering species from different contaminants had no effect on the sensing of 4-NT. All of these findings show that the newly developed sensor performs well in terms of reproducibility, selectivity, and sensitivity for the detection of 4-NT

One-Step Molten Salt Method For Synthesis of Perovskite-Like Sr2Nb2O7 and Sr5Nb4O15 Ceramics

Abstract In this study, Sr2Nb2O7 and Sr5Nb4O15 layered perovskite-like ceramics were synthesized by a single process using a one-step molten salt method. By optimizing the key parameters, including the choice of molten salt, reaction temperature and residence time, two materials achieve synchronous production. The crystal structures of the synthesized materials were confirmed by X-ray diffraction. It is proved that it has typical perovskite-like structural characteristics. Scanning electron microscopy reveals the morphology of these materials. Sr2Nb2O7 presents a sheet-based structure, and Sr5Nb4O15 presents a rod-based structure. This study provides an efficient and direct method for the synthesis of perovskite materials. One-step molten salt method has great potential in the synthesis of multiphase materials. These findings are expected to promote the application of perovskite materials in the fields of electronics, optics and catalysis.

Supercapacitor devices based on multiphase MgTiO3 perovskites doped with Mn2+ ions

Recently, perovskites have become a hotspot for researchers attempting to exploit metal and oxygen vacancies in structures of the form MTiO3, facilitating the convenient electron/hole migration, thus displaying interesting properties. Magnesium Titanate (MgTiO3) is a prominent part of the perovskite class, exhibiting remarkable electrical, thermal, and chemical properties. Undoped and Mn-doped MgTiO3 samples were obtained using a solid-state reaction starting from previously synthesized MgO and TiO2 powders, which were separately doped with different Mn ion concentrations. The resulting multiphase materials with a major MgTiO3 phase were thoroughly morpho-structurally analyzed employing XRD, STEM, Raman, PL, XPS, and EPR spectroscopy. The electrochemical results indicate that they show superior performance when used as electrode materials for supercapacitor application due to the high defect concentration as shown in EPR and PL spectroscopy and the ferroelectric behavior observed in XPS and XRD. When used in symmetric and asymmetric supercapacitor devices, they show promising results, with specific capacity values reaching up to 109 F/g for the symmetric and 609 F/g for the asymmetric devices, while energy and power density values reached 84.7 Wh/kg and 90.8 kW/kg respectively, proving a great potential in the energy storage field.

Structural design of hierarchical porous biomass carbon with a built-in electric field for efficient peroxymonosulfate activation

Biomass-derived carbon materials have excellent adsorption capacity and cost-effectiveness, and the electron interactions between multiphase composite materials improve the efficiency of water pollutant removal by advanced oxidation processes (AOPs). Herein, a multistage biochar catalyst in which metallic cobalt-embedded carbon tubes are prepared uniformly on the surface of kapok tubes is designed and fabricated. The closely connected structure grown in situ accelerates electron migration and forms a directional transfer electric field. The N-doped carbon nanotube encapsulated Co nanoparticles growth on the kapok biochar/PMS (Co-N-KBC/PMS) system removes tetracycline hydrochloride (TCH) at a rate 11.8 times higher than that of KBC/PMS. Free radicals (SO4•−, •OH, and •O2–) and non-free radicals (1O2) are generated in conjunction with electron transfer during PMS activation. The cobalt sites and C=O groups are possible active sites. Density-functional theory (DFT) calculations verify the built-in electric field from N-KBC to the Co surface, which accelerates electron transfer and improves TCH removal. The results reveal an effective strategy to activate PMS and address environmental remediation by utilizing carbon materials derived from biomass.

Multiphase soft metal enabled high-performance fabric-based wearable energy harvesting

Highly efficient and flexible power sources have always been the focus and goal in the field of wearable electronics. However, the existing wearable power sources are limited by their large size, high weight, electrolyte leakage, and poor mechanical compliance, which seriously hinders their practical applications. Herein, we propose a novel strategy to achieve and demonstrate a fabric-based high-performance wearable triboelectric nanogenerator (TENG) structure. The metals of gallium (Ga), bismuth (Bi), indium (In), and tin (Sn) are mixed according to specific mass ratios, and then they are transformed in liquid phase to form room-temperature multiphase soft metals of GaBiInSn. The material exhibits both metallic and fluidic properties, and possesses a characteristic of multiphase structure. The GaBiInSn material is directly deposited between polytetrafluoroethylene (PTFE) layers and nonwoven fabrics to establish multi-level conductive and frictional interfaces, creating charge transfer and solid-liquid hybrid dielectric layers. Therefore, the thin film-type triboelectric nanogenerators with a structure of PTFE/GaBiInSn/nonwoven fabric (LM-P-TENGs) is manufactured. The LM-P-TENGs can be integrated onto fabrics without compromising their breathability, comfortableness, and flexibility. Particularly, LM-P-TENGs efficiently convert the mechanical energy of human limb movements into sustainable electrical energy output. Under the human limb mechanical triggering conditions, LM-P-TENG achieves a champion specific open-circuit voltage up to 900 V, peak short-circuit current density of 43.3 mA/m2, and high power density of 12.56 W/m2. This work demonstrates the application potential of room-temperature multiphase soft materials in flexible wearable power sources, while introducing a novel power supply mode for wearable electronics. Additionally, the LM-P-TENGs also present applications in self-powered wearables, medical biosensing systems, human-machine interaction systems, near-eye display systems, etc. for the flexible electronics.

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li7La3Zr2O12-LiCoO2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li7La3Zr2O12-LiCoO2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. Our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

A dichotomous angle refinement discrete material optimization method for fiber composite materials

The discrete material optimization method optimizes the distribution of materials by setting candidate materials using a multi-phase material penalty model. Addressing the issue of reduced efficiency in fiber orientation optimization due to a large number of candidate materials, this paper proposes a dichotomous angle refinement discrete material optimization method to enhance solution speed. This method leverages the efficiency of the bisection approach to rapidly refine the angle in discrete optimization results, thereby narrowing the range of candidate fiber orientations. Furthermore, by introducing fiber orientations perpendicular to the optimized orientation, it mitigates potential local optimization issues during the optimization process, thereby enhancing the method’s optimization capability. Compared to traditional discrete material optimization methods, this method employs a special dichotomy method to determine the candidate materials for each element, thereby decreasing the number of design variables. This method demonstrates higher computational efficiency when solving fiber orientation optimization problems with a large number of candidate materials. Several numerical examples provided in the paper validate the efficiency and stability of the proposed method in addressing optimization problems.

Sequential dual-scale approach for microstructure-informed ductile fracture prediction

This study presents a novel dual-scale finite element method to establish a microstructure-informed ductile fracture criterion for ferrite–martensite dual-phase (DP) steel. At the macroscale, an anisotropic plasticity model with rate-dependent hardening was employed to simulate the material's deformation history. Simultaneously, at the microscale, a dislocation density-based crystal plasticity model was utilized to simulate deformation within a representative volume element (RVE) of the dual-phase steel, constructed using tomography aided by a plasma-focused ion beam/electron backscatter diffraction system.The material properties of the ferrite and martensite phases were determined through X-ray diffraction (XRD) analysis and load-displacement measurements obtained via nanoindentation for each phase. The RVE simulation results were validated against experimentally measured mechanical properties and microstructural changes. The local deformation history at the fracture initiation site, extracted from the macroscale model, was used as boundary conditions for the microscale RVE simulation; sequential dual-scale approach. The models were applied to specimens with varying notch radii, generating different local stress triaxialities and accumulated shear strains at fracture onset. This process allowed the establishment of a ductile fracture criterion, which was further tested in a hole expansion experiment, demonstrating close alignment with experimental data.This sequential dual-scale analysis effectively predicts the deformation behavior of multiphase metallic materials by incorporating realistic microstructures while minimizing computational costs. Consequently, the proposed ductile fracture prediction technique offers a robust method with broad applicability across various metallic materials.

Microstructural behavior of CNT-PDMS thin-films for multifunctional systems

Heterogeneous ribbed and non-ribbed carbon nanotube (CNT)-PDMS thin-film systems manufactured by large-scale rolling exhibit large-strain and high strain-rate characteristics with favorable surface behaviors, such as superhydrophobicity and drag reduction. However, it is not well understood how the multi-phase microstructure and material properties of non-ribbed thin-films are related to the surface material behavior and fracture. Hence, the objective of this investigation is to characterize the large-strain mechanical behavior and the microstructure of various CNT-PDMS compositions to understand how the CNT loading, agglomeration, distribution, and orientation affect the mechanical behavior and fracture of CNT-PDMS unribbed systems. Non-ribbed thin tensile testing specimens were fabricated for neat PDMS and CNT-PDMS with different weight CNT distributions to understand non-ribbed behavior. The ultimate strain, strength, and global stress–strain behavior were obtained by uniaxial mechanical testing. Scanning electron microscopy (SEM) of the fracture surface was also obtained for each sample to analyze the microstructure and relate the damage mode to the different weight distributions. Based on these experimental measurements and observations, large-strain, hyperelastic and hyper-viscoelastic material models were used to characterize the material behavior. The hyper-viscoelastic material model was shown to provide the most accurate material description of the thin-film behavior of the viscoelastic PDMS with the high-strength CNTs.

The mechanical coupling effect of α and β phases in Ti6Al4V alloy undergoing laser shock peening: A molecular dynamics study

In the dual- or multi-phase metallic materials, the influence of different microstructural constituents on the plastic strain/stress distribution is still an area of great controversy. Herein, the heterogeneous deformation behavior of α and β phases in Ti6Al4V duplex titanium alloy undergoing laser shock peening (LSP) has been investigated by molecular dynamics simulations, and the corresponding typical microstructural features are characterized at varied strains. Also, the relationship between the theoretical microstructural morphologies and the micro stress is revealed. It evidently indicates that, the grain refinement process can be summarized as: (i) dislocation motions1 interacting with deformation twins in α phases, (ii) a combination of dislocation propagations and the deformation-induced phase transition from β phase to α phase. In addition, unlike the α single-phase titanium alloy, the representative stress – strain curve of α + β titanium alloy presents a gentle fluctuation trend with smaller amplitude value, suggesting an occurrence of the coupling deformation behavior between α and β phases. The initial interfacial dislocation nucleation prefers to site in the α/α interface rather than the α/β interface, then emitting to the interior of α grains. Features of dislocation slip, twin growth, stacking fault, and phase transformation dominate the release of LSP-generated micro stress, while grain and interphase boundaries, as well as dislocation locks, contribute to the increment of the LSP-generated micro stress.

Flash sintering mechanism in multiphase materials system of copper smelting slags

Flash sintering (FS) is of great interest today, as it allows the production of high-density ceramics in seconds at lower temperatures than conventional sintering. In this study, the effects of conventional sintering at 1250°C for 4 h and FS at various electric fields (12.5, 25, 50 and 75 V/mm) on copper smelting slag (CSS), which is a multiphase material system, are investigated. The results show that FS occurs at substantially lower temperatures with much shorter times than conventional sintering, in conjunction with improved density and hardness values for CSS. The optimum condition for better densification is observed for the sample applied the 25 V/mm electric field in 554 s, and the maximum power density of about 76.49 mW/mm3. On the other hand, the shortest FS duration is achieved with the sample applied 75 V/mm in 114 s. Flash sintering at lower temperatures also stabilizedthe magnetite-hematite the phase transition, which arouses at higher temperatures. Overall, FS has made a huge contribution to reducing sintering time and temperature while providing better microstructure integrity and mechanical properties in multiphase materials systems.

Synchrotron Micro-X-ray Diffraction in Transmission Geometry: A New Approach to Study Polychrome Stratigraphies in Cultural Heritage

In cultural heritage, paint stratigraphies are complex systems typically consisting of various paint layers with fine crystalline phases mixed with coarse pigment and filler grains. This complexity poses significant challenges for X-ray diffraction (XRD) analysis. In this work, we employed synchrotron radiation micro-X-ray diffraction in transmission geometry (SR-µTXRD) with linear mapping to develop a novel approach for studying the crystalline phases (pigments and fillers) in mock-up paint stratigraphies. A targeted approach was followed for qualitative, quantitative, and microstructural analysis, combining signals from micrometric crystallites and coarse single crystals as well as from randomly oriented and iso-oriented crystalline phases. This allows for identifying, localizing, and quantifying these phases even in low fractions and distinguishes the same phases across different layers with varying grain sizes or spatial orientations. Critical analysis of 2D XRD patterns, coupled with full-profile fitting performed by the Rietveld method, provides insights into material preparation (e.g., grinding), painting technique (e.g., color palette, use of fillers, brushing), and crystallo-chemical modifications over time. This analytical approach, integrating spatially resolved investigation with high-quality phase characterization, enhances the potential of specific XRD methodologies for a 2D investigation of multi-phase materials in cultural heritage, even without dedicated micro-mapping techniques.