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At least 217 records · Page 12

Microscale Imaging of Thermal Conductivity Suppression at Grain Boundaries

Abstract Grain‐boundary engineering is an effective strategy to tune the thermal conductivity of materials, leading to improved performance in thermoelectric, thermal‐barrier coatings, and thermal management applications. Despite the central importance to thermal transport, a clear understanding of how grain boundaries modulate the microscale heat flow is missing, owing to the scarcity of local investigations. Here, thermal imaging of individual grain boundaries is demonstrated in thermoelectric SnTe via spatially resolved frequency‐domain thermoreflectance. Measurements with microscale resolution reveal local suppressions in thermal conductivity at grain boundaries. Also, the grain‐boundary thermal resistance – extracted by employing a Gibbs excess approach – is found to be correlated with the grain‐boundary misorientation angle. Extracting thermal properties, including thermal boundary resistances, from microscale imaging can provide comprehensive understanding of how microstructure affects heat transport, crucially impacting the materials design of high‐performance thermal‐management and energy‐conversion devices.

36 MATERIALS SCIENCE↗

Manifold learning for coarse-graining atomistic simulations: Application to amorphous solids

In this work, we introduce a generalized machine learning framework to probabilistically parameterize upper-scale models in the form of nonlinear PDEs consistent with a continuum theory, based on coarse-grained atomistic simulation data of mechanical deformation and flow processes. The proposed framework utilizes a hypothesized coarse-graining methodology with manifold learning and surrogate-based optimization techniques. Coarse-grained high-dimensional data describing quantities of interest of the multiscale models are projected onto a nonlinear manifold whose geometric and topological structure is exploited for measuring behavioral discrepancies in the form of manifold distances. A surrogate model is constructed using Gaussian process regression to identify a mapping between stochastic parameters and distances. Derivative-free optimization is employed to adaptively identify a unique set of parameters of the upper-scale model capable of rapidly reproducing the system's behavior while maintaining consistency with coarse-grained atomic-level simulations. The proposed method is applied to learn the parameters of the shear transformation zone (STZ) theory of plasticity that describes plastic deformation in amorphous solids as well as coarse-graining parameters needed to translate between atomistic and continuum representations. We show that the methodology is able to successfully link coarse-grained microscale simulations to macroscale observables and achieve a high-level of parity between the models across scales.

36 MATERIALS SCIENCE↗

Insights into factors that affect non-Arrhenius migration of a simulated incoherent Σ3 grain boundary

Non-Arrhenius grain boundary migration, sometimes referred to as antithermal migration where temperature and GB velocity values are inversely related to each other, is examined in an incoherent twin Σ3 [111] 60° (11 8 5) nickel grain boundary. Molecular dynamics is used to simulate migration and examine the effect of various factors on the migration, including interatomic potential, system size, driving force, and variation of atomic grain boundary structure. A classical model for grain boundary migration, in its unsimplified form, is used to analyze the results. The grain boundaries exhibit migration mechanisms with very low apparent barrier heights to migration. As a result, the boundaries migrate quickly but exhibit a velocity saturation similar to that of dislocations. Furthermore, the various interatomic potentials exhibit different migration velocities, but their similarities suggest they all predict similar overall behaviors of migration. The variation of atomic structure in the same incoherent twin grain boundary leads to diverse behaviors with barrier heights that vary from non-Arrhenius to Arrhenius migration. Facet nucleation is confirmed not to be a requirement for this boundary based on an examination of simulation cell size; however, the presence and/or interaction between numerous facets does suggest a slowing and increased barrier height to migration for larger boundaries.

36 MATERIALS SCIENCE↗

High temperature stabilization of ultrafine grain tungsten alloys through synergistic compositional complexities

Thermally-stabilized fine-grained microstructures in tungsten provide a pathway to harnessing enhanced properties such as a reduced ductile-to-brittle transition temperature and improved strength while mitigating the adverse effects of grain growth and recrystallization. Here, in this study, we employ a material design strategy that relies on grain boundary segregation in the nanocrystalline state driven by alloy thermodynamics balanced with impurity scavenging through in situ formation of kinetically-stabilizing metal carbides. A W-Ti-Cr alloy is designed through lattice Monte Carlo methods and subsequently synthesized in a single-phase nanocrystalline state, which upon annealing, evolves into an ultrafine grained microstructure containing chromium grain boundary segregation collectively with a dispersed TiX (X=C,O) phase through the reaction of titanium with carbon and oxygen impurities. In situ synchrotron X-ray diffraction experiments demonstrate that increased Ti promotes stabilization across a larger temperature range but with diminishing returns above 10 at.% Ti. Long-term stability was confirmed through the retention of the ultrafine grained microstructure for a total of 8 days (192 h) at 1300 °C without grain/carbide growth and/or recrystallization. Our results demonstrate that, through strategic tailoring of composition and microstructure, one can harness the benefits of both thermodynamic and kinetic stabilization mechanisms, opening pathways for future alloy formulations that expand the window of stability.

36 MATERIALS SCIENCE↗

A Generalized Grain-Scale Model for the Non-Plasma and Plasma-Assisted Hydrogen Direct Reduction of Iron Ore

Direct Reduction of Iron ore using hydrogen (H-DRI) is a promising pathway towards efficient steelmaking and accurate predictive models are a necessity for scale-up and optimization of this technology. However, accurate models of this process remain limited because existing models oversimplify grain-scale phenomena, such as nonlinearity inside grain, self-sufficient porosity, surface reactions, and the role of plasma species. These phenomena are important for flash steelmaking and plasma-assisted H-DRI processes. To address this need, we present a phenomenological model for simulating H-DRI at the scale of a single micron-sized grain of the iron ore. We call this the Transient Reactive Grain Model (TRGM). TRGM incorporates key physical process: gas species transport, a chemical kinetics of material conversion, nanopore structural evolution and, adsorption-desorption surface kinetics at the reactive nanopore surface. The important contribution of this work is that the model provides a dependence on different reductant species, specifically hydrogen atoms versus molecules, so that role of hydrogen plasma reduction can be clarified compared to the use of pure hydrogen gas reduction. TRGM predictions agree well with experimental data for both molecular H2 reduction of Fe2O3 and plasma hydrogen reduction of Fe3O4. Results reveal species concentration gradients with a diffuse reaction zone, and enhanced hydrogen diffusion at the grain outer surface due to evolving porosity. These findings challenge common assumptions in existing models, including sharp reaction fronts, quasi-steady diffusion and kinetics, and the neglect of surface chemistry. As a generalized grain-scale model for H-DRI processes, TRGM has practical applications in flash steelmaking and in-flight reduction using both molecular and plasma hydrogen.

08 HYDROGEN↗

The effect of microstructure on the relationship between grain boundary sliding and slip transmission in high purity aluminum

The relationship between grain boundary sliding (GBS) and slip transmission is investigated experimentally at grain boundaries in 99.99% aluminum with a through-thickness, coarse grained microstructure deformed in tension at 190 °C. Using scanning electron microscope enabled digital image correlation (SEM-DIC) and electron backscatter diffraction (EBSD), high resolution strain fields and microstructural information were measured to examine the influence of microstructural neighborhoods on interactions between GBS and slip transmission and strain localization. Several distinct cases are presented that highlight important microstructural factors that govern deformation near grain boundaries. The findings include (1) direct transmission and GBS were anti-compatible and facilitated by opposing boundary types (low misorientation and high energy grain boundaries respectively); (2) increased GBS activity was correlated with decreased indirect transmission behavior; (3) GBS accommodation at triple junctions was enabled by intragranular plasticity; and (4) the local intragranular plastic strain discontinuity between grains determined the magnitude of GBS gradients. Finally, this work provides insight into the nature of these mechanisms and can be used to identify strain transfer criteria that can lead to improved GBS-sensitive crystal plasticity models.

36 MATERIALS SCIENCE↗

Experimental characterization and atomistic simulation of grain boundary segregation in Mg-Y alloys

As a rare earth solute element in Mg alloys, Y has the beneficial effects of increasing both the strength and the ductility as well as weakening the crystallographic texture. To achieve a more fundamental understanding on how Y addition affects the microstructural evolution and mechanical properties, the Y segregation behavior at grain boundaries was investigated in Mg-1wt.%Y and Mg-7wt.%Y alloys at different conditions. The segregation intensity and its dependence on the grain boundary misorientation angle were experimentally characterized and computationally predicted. Strong segregation at grain boundaries was observed in both low and high Y-containing alloys. Y segregation was found to remain in alloy Mg-7Y after high-temperature annealing heat treatment at 540 °C. No direct correlation between the Y segregation intensity and the grain boundary misorientation angle could be established based on either the experimental characterization or the atomistic simulation with a spectral model. We thus conclude that grain boundary segregation of Y is independent of grain boundary misorientation angle.

Grain boundary↗

Meshfree simulation and prediction of recrystallized grain size in friction stir processed 316L stainless steel

Friction stir processing (FSP) is a promising solid-phase microstructural modification technique that can repair and enhance damaged stainless steel surfaces exposed to harsh environments. The quality of the repaired material is closely correlated to the recrystallized grain size in the stir zone (SZ), which is influenced by the thermomechanical conditions dictated by FSP process parameters. Thus, establishing a reliable relationship between these parameters and recrystallized grain size in the SZ is crucial for optimizing repair quality. However, existing experimental approaches often rely on indirect temperatures measured far from the SZ, along with rough strain rate estimations, which are imprecise and time-consuming. Meanwhile, existing mesh-based modeling methods usually face numerical challenges when dealing with the large material deformations inherent in FSP. Here, to address these issues, this study introduces a meshfree process model for FSP based on the smoothed particle hydrodynamics (SPH) method, aimed at predicting process conditions under different parameters. The model is validated using experimental data from 11 combinations of tool traverse and rotation speeds on 316 L stainless steel. Correlations between process parameters, material flow, temperature, strain, strain rate, and recrystallized grain size are revealed through SPH simulations and electron backscatter diffraction (EBSD) imaging. The results show that in situ SZ temperatures range from 1071 to 1322°C, which exceed the tool temperature by over 300°C. Furthermore, SZ temperature, strain rate, and grain size increase monotonically with higher tool temperature and faster traverse speed. A relationship is then established between the model-predicted Zener-Hollomon parameter and the recrystallized grain size based on EBSD data, expressed as ln(d) = -0.364 ln(Z) + 14.673. Finally, this relationship exhibits satisfactory accuracy with errors of less than 26.9% in predicting grain sizes at various SZ locations, which offers valuable insights for optimizing FSP repair processes for 316 L stainless steel.

316L stainless steel↗

Molecular dynamics studies of helium bubble effects on grain boundary fracture vulnerabilities in an Fe 70 Ni 11 Cr 19 –1%H austenitic stainless steel

Comprehensive molecular dynamics tensile test simulations have been performed to study the delamination processes of seven different grain boundaries / cleavage planes (Σ1{111}, Σ3{111}, Σ5{100}, Σ7{111}, Σ9{411}, Σ11{311}, and R{100}/{411}) containing a helium bubble. Combinations of a variety of conditions are explored including different strain rates, system dimensions, bubble density, bubble radius, bubble pressure, and temperature. We found that in general, grain boundaries absorb less energies with decreasing strain rate but increasing bubble areal density, bubble pressure, bubble radius, and temperature. The propensity of grain boundary delamination is sensitive to grain boundary type: The random grain boundary R{100}/{411} is one of the most brittle boundaries whereas the Σ1{111} cleavage plane and the Σ3{111} twin boundary are two of the toughest boundaries. The sorted list of grain boundary fracture vulnerability obtained from our dynamic tensile test simulations differs from the one obtained from our decohesion energy calculations, confirming the important role of plastic deformation during fracture. Finally, detailed mechanistic analyses are performed to interpret the simulated results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Anisotropic Hot Spot Formation at a Grain Boundary in Shock-Compressed TATB High Explosive Crystal

Secondary high explosives (HEs) exhibit rich microstructure that promotes the formation of hot spots responsible for detonation initiation, but the role of microstructural interfaces remains poorly quantified. To this end, we develop extensions for the generalized crystal-cutting method (GCCM) to prepare molecular dynamics (MD) simulation cells containing grain boundaries (GBs) and other crystal–crystal interfaces with prescribed tilt and twist orientations. Using the GCCM, we perform MD simulations of shock interactions with a GB between the (001) and (100) crystal facets in the secondary HE TATB (1,3,5-triamino-2,4,6-trinitrobenzene). Our MD simulations reveal a strong directional dependence to the formation of a hot spot at the GB interface. In particular, transmission of the shock from the (001) grain to the (100) grain yields a hot spot in the (100) grain at the GB interface, whereas no hot spot is produced when an equivalent shock transits the GB in the opposite direction. We trace the origin of this GB anisotropy to three dominant factors: (1) the intrinsic differences in shock-deformation mechanisms and wave structures for the bulk (100) and (001) grains, which leads to distinct geometries and mechanical impedances upon shock arrival to the GB depending on which grains are donor or acceptor for the transmitted shock; (2) the different time intervals separating the initial shock rise and the formation of steady wave structures in the respective donor–acceptor configurations; and (3) the differences in time scales required to re-establish local thermal equilibrium. Interfacial hot spots form when these factors combine to impede development of a steady two-wave structure and instead induce a localized, pseudosingly shocked region that undergoes a higher rate of work production (resulting in a higher temperature) compared to when the steady two-wave structure develops further from the interface. The extensions to the GCCM approach presented here are anticipated to facilitate a wide range of MD studies that focus on understanding the role of crystal–crystal interfaces in molecular materials.

organic↗

Reversible Changes in the Grain Structure and Conductivity in a Block Copolymer Electrolyte

Here, we study the phase behavior of a triblock organic–inorganic hybrid copolymer, poly(polyhedral oligomeric silsesquioxane)-b-poly(ethylene oxide)-b-poly(polyhedral oligomeric silsesquioxane) (POSS-PEO-POSS)/lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt mixture, as a function of temperature. The polymer exhibits a lamellar morphology both in the neat state and in the presence of salt. However, the average grain size increases substantially when the electrolyte is heated above 113 °C. The grain structure of this sample changes reversibly with temperature, that is, smaller grains reappear when the electrolyte is cooled below 113 °C. While annealing block copolymers at high temperatures often leads to an increase in the grain size, this change is generally irreversible. The reason for the reversible change in the grain structure of the POSS-PEO-POSS/LiTFSI electrolyte is discussed. The ionic conductivity of the electrolyte also exhibits reversible changes in this temperature window. Knowledge of the grain structure is crucial for understanding ion transport in nanostructured electrolytes.

25 ENERGY STORAGE↗

Nanoscale Imaging and Measurements of Grain Boundary Thermal Resistance in Ceramics with Scanning Thermal Wave Microscopy

Material thermal conductivity is a key factor in various applications, from thermal management to energy harvesting. With microstructure engineering being a widely used method for customizing material properties, including thermal properties, understanding and controlling the role of extended phonon-scattering defects, like grain boundaries, is crucial for efficient material design. However, systematic studies are still lacking primarily due to limited tools. In this study, we demonstrate an approach for measuring grain boundary thermal resistance by probing the propagation of thermal waves across grain boundaries with a temperature-sensitive scanning probe. The method, implemented with a spatial resolution of about 100 nm on finely grained Nb-substituted SrTiO 3 ceramics, achieves a detectability of about 2 × 10 –8 K m 2 W –1 , suitable for chalcogenide-based thermoelectrics. The measurements indicated that the thermal resistance of the majority of grain boundaries in the STiO 3 ceramics is below this value. While there are challenges in improving sensitivity, considering spatial resolution and the amount of material involved in the detection, the sensitivity of the scanning probe method is comparable to that of optical thermoreflectance techniques, and the method opens up an avenue to characterize thermal resistance at the level of single grain boundaries and domain walls in a spectrum of microstructured materials.

36 MATERIALS SCIENCE↗

Physics-informed machine learning analysis for nanoscale grain mapping by synchrotron Laue microdiffraction

Understanding the grain morphology, orientation distribution and crystal structure of nanocrystals is essential for optimizing the mechanical and physical properties of functional materials. Synchrotron X-ray Laue microdiffraction is a powerful technique for characterizing crystal structures and orientation mapping using focused X-rays. However, when the grain sizes are smaller than the beam size, mixed peaks in the Laue pattern from neighboring grains limit the resolution of grain morphology mapping. We propose a physics-informed machine learning (PIML) approach that combines a convolutional neural network feature extractor with a physics-informed filtering algorithm to overcome the spatial resolution limits of X-rays, achieving nanoscale resolution for grain mapping. Our PIML method successfully resolves the grain size, orientation distribution and morphology of Au nanocrystals through synchrotron microdiffraction scans, showing good agreement with electron backscatter diffraction results. This PIML-assisted synchrotron microdiffraction analysis can be generalized to other diffraction-based probes, enabling the characterization of nanosized structures with micrometre-sized probes.

X-ray crystallography↗

Colossal Grains for a New Structural Paradigm in Thin-Film Photovoltaics

II-VI based thin-film photovoltaics (PV) have experienced substantial commercial success on a foundation of fast large-scale deposition and processing. This type of processing, regardless of material type, nearly always results in small grain (nm to several um diameters) polycrystalline material that, if not for effective grain boundary (GB) and defect passivation, would severely limit PV performance. In the case of CdTe based PV technology, the nearly ubiquitous CdCl2 treatment is used, in part, to passivate the polycrystalline p-type absorber even though Cl is known to (and used to) compensate p-type II-VI materials. Given that VOC is still the most limited performance metric and it can only be improved through higher p-type absorber concentrations, CdCl2 treatments may be holding the technology back. In this talk, we will discuss results related to a process by which small grain CdSeTe material is rapidly transformed into very large grain material (100-1000um diameters, Fig. 1a). This explosive recrystallization, which we have termed colossal grain growth (CGG), occurs by a Cl free process with thin films (<10um) deposited using the same fast deposition techniques the industry has relied on for more than a decade. Our modeling suggests that GB recombination becomes significantly less important at these grain sizes and thus may eliminate the need for a CdCl2 treatment. This result is complimented by previous results of epitaxial growth at high rates on single crystal seed layers. Thin CdSeTe CGG seed layers can be used for rapid epitaxy of CdTe to complete a standard device stack (Fig.1b). This is an optimistic view and the current limitations and challenges related to this process and these materials will also be discussed, including alloy and substrate roughness sensitivity, intragrain material quality, and complex defect chemistry. These challenges are not insignificant but overcoming them may enable a new structural paradigm for thin-film PV.

CdTe↗

Data associated with “Different methods of estimating riverbed sediment grain size diverge at the basin scale ” (v2)

This data package is associated with the publication “Different methods of estimating riverbed sediment grain size diverge at the basin scale” published in Frontiers in Earth Science (Regier et al., 2025). The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (d50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual methods to measure d50 are time-consuming and ignore larger grains, while model-based methods to estimate d50 often over-generalize basin characteristics, and therefore cannot accurately represent site-scale heterogeneity. Here, we apply a machine learning-enabled photogrammetry methodology (You Only Look Once, or YOLO) for estimating d50 for grains > 2 mm based on images collected from streams and rivers throughout the Yakima River Basin (YRB). To understand how such methods may help bridge the gaps in resolution and accuracy between manual and catchment characteristics model-based d50 estimates, we compared YOLO d50 values to manual and model-based estimates across the YRB. We found distinct differences among methods for d50 averages and variability, and relationships between d50 estimates and basin characteristics. Source images can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052. This data package was originally published in May 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. In addition to the readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) and subfolders containing data, figures, and scripts. The data folder contains datasets used for the analyses in the manuscript in image, text-delimited or geospatially-referenced formats. The figures folder contains the figures from the manuscript in different formats. The scripts folder contains all of the scripts used to complete the analyses in the manuscript. All files are .csv, .rds, .dbf, .prj, .shp, .shx, .jpg, .png, .R, .Rproj, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Grain size estimation in fluvial gravel bars using uncrewed aerial vehicles: A comparison between methods based on imagery and topography

Abstract Grain size assessments are necessary for understanding the various geomorphological, hydrological and ecological processes that occur within rivers. Recent research has shown that the application of Structure‐from‐Motion (SfM) photogrammetry to imagery from uncrewed aerial vehicles (UAVs) shows promise for rapidly characterising grain sizes along rivers in comparison to traditional field‐based methods. Here, we evaluated the applicability of different methods for estimating grain sizes in gravel bars along a study reach in the Olentangy River in Columbus, Ohio. We collected imagery of these gravel bars with a UAV and processed those images with SfM photogrammetry software to produce three‐dimensional point clouds and orthomosaics. Our evaluation compared statistical models calibrated on topographic roughness, which was computed from the point clouds, and to those based on image texture, which was computed from the orthomosaics. Our results showed that statistical models calibrated on image texture were more accurate than those based on topographic roughness. This might be because of site‐specific patterns of grain size, shape and imbrication. Such patterns would have complicated the detection of topographic signatures associated with individual grains. Our work illustrates that UAV‐SfM approaches show potential to be used as an accessible method for characterising surface grain sizes along rivers at higher spatial and temporal resolutions than those provided by traditional methods.

Wong, Tyler↗

Evaluating the grain-scale deformation behavior of a single-phase FCC high entropy alloy using synchrotron high energy diffraction microscopy

We report although the deformation behavior of high-entropy alloys (HEAs) has been extensively studied at the macroscale, many important properties have yet to be explored for these alloys at the microscale, thus hampering accurate prediction of damage and failure processes. Synchrotron high-energy diffraction microscopy (HEDM) and fast-Fourier transform-based crystal plasticity modeling was conducted to investigate the three-dimensional (3D) grain-resolved micromechanical response for approximately 1,900 constituent grains within a single-phase FCC HEA up to 1% applied strain. The evolution of grain-resolved elastic strains, lattice reorientations, and maximum resolved shear stresses (mRSS) were evaluated to quantify elastic, yield, and fully plastic behavior. Overall, the initial critical resolved shear stress (CRSS), determined via in situ HEDM and companion modeling, was found to be > 20% higher than estimated using the classical polycrystalline Taylor factor (M = 3.06). However, a descriptive parameter based on the average grain-resolved Taylor factor ($\overline{M}$) was found to show excellent agreement with plastic yielding behavior observed within HEDM datasets. Noticeable deviations in HEDM lattice reorientations compared to both EVP-FFT simulations and classical predictions for FCC polycrystals were discovered, highlighting the complexity in correlating local lattice reorientations, Taylor, and Schmid factors with plastic response for this material at the grain-scale. Therefore, it is anticipated that the overall trends and parameter identification of 3D grain-resolved properties in this study can serve as an important foundation for continued mesoscale investigation on both well-established and newly developed Cantor-like HEAs.

36 MATERIALS SCIENCE↗

Sensitivity of cellular automata grain structure predictions for high solidification rates

Understanding as-solidified grain structure development during constrained (G 0) alloy solidification conditions is a necessary component of understanding the larger process-microstructure relationships during additive manufacturing (AM) processing. This study applies a cellular automata (CA) model, for static solidification velocities and thermal gradients on the order of those expected in AM melt pools, to investigate grain shape development across ranges of input parameters governing temperature field evolution, nucleation, and growth. Variation in nucleated grain shape from columnar to equiaxed as a function of thermal gradient and nucleation density is modeled with CA and verified against the established transition model of Hunt and Gaumann. Furthermore, while thermal conditions and nucleation density are shown to have the largest roles on microstructure development, the sensitivity of grain structure was very unevenly distributed across parameter space. In particular, it was found that microstructure is very sensitive to mean nucleation undercooling and the interfacial response function in process space regimes near grain structure transitions, but entirely controlled by a combination of thermal gradient, solidification velocity, and nucleation density away from such transitions. The understanding of grain shape sensitivity obtained through CA modeling, particularly at large thermal gradient and nucleation density, will be necessary for accurate microstructure prediction during the extreme processing conditions and large input parameter uncertainty common to AM.

36 MATERIALS SCIENCE↗