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At least 721 records · Page 40

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DOE OSTI2020

Synthesis, transport properties and electronic structure of p-type Cu 1+x Mn 2–x InTe 4 ( x = 0, 0.2, 0.3)

The synthesis, electronic structure and temperature dependent transport properties of polycrystalline Cu 1+x Mn 2–x InTe 4 (x = 0, 0.2, 0.3) are reported for the first time. These quaternary chalcogenides were synthesized by direct reaction of the elements, followed by solid state annealing and hot press densification. The thermal conductivity is low for all specimens and intrinsic to the material system. Furthermore, the off-stoichiometry specimens illustrate the sensitivity of the transport properties to stoichiometry, with a greater than two-orders-of magnitude increase in carrier concentration with increased Cu content. First principles calculations of the electronic structure are also reported, and are in agreement with the experimental data. Here, this fundamental investigation shows the potential towards further optimization of the electrical properties that, in addition to the intrinsically low thermal conductivity, provides a basis for further research into the viability of this material system for potential energy-related applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor.

25 ENERGY STORAGE↗

DOE OSTI2014

Tailoring of crystal phase and Néel temperature of cobalt monoxides nanocrystals with synthetic approach conditions

Cobalt monoxide (CoO) nanocrystals were synthesized by thermal decomposition of cobalt oleate precursor in a high boiling point organic solvent 1-octadecene. The X-ray diffraction pattern and transmission electron microscopy studies suggest that pure face-centered-cubic (fcc) phase of CoO can be synthesized in the temperature range of 569–575 K. Thermolysis product at higher synthesis temperature 585 K is a mixture of fcc and hexagonal-closed-packed (hcp) phases. These nanocrystals are single crystals of CoO and exhibit mixture of two types of morphologies; one is nearly spherical with 5–25 nm diameter, and other one is 5–10 nm thick flake. The pure fcc-CoO nanocrystals show enhanced, and mixture of fcc- and hcp-CoO nanocrystals show reduced antiferromagnetic ordering temperature. Such results provide new opportunities for optimizing and enhancing the properties and performance of cobalt oxide nanomaterials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2015

SU-E-T-663: Radiation Properties of a Water-Equivalent Material Formulated Using the Stoichiometric Analysis Method in Heavy Charged Particle Therapy

Purpose: A material has been designed to be employed as water-equivalent in particle therapy using a previously established stoichiometric analysis method (SAM). After manufacturing, experimental verification of the material’s water-equivalent path length (WEPL) and analysis of its total inelastic nuclear interaction cross sections for proton beams were performed. Methods: Using the SAM, we optimized the material composed of three base materials, i.e., polyurethane, calcium carbonate and microspheres. From the elemental composition of the compound, electron density, linear attenuation coefficients, particle stopping powers and inelastic nuclear cross sections for protons using data from ICRU 63 were calculated. The calculations were then compared to Hounsfield units (HUs) measured with 350 mAs at 80, 100, 120 and 140 kV and the WEPLs measured with three different ions: proton (106.8 MeV/u), helium (107.93 MeV/u) and carbon (200.3 MeV/u). Results: The material’s measured HUs (0.7±3.0 to 2.6±6.2 HU) as well as its calculated relative electron density (1.0001) are in close agreement with water as reference. The WEPLs measured on a 20.00 mm thick target were 20.16±0.12, 20.29±0.12 and 20.38±0.12 mmH2O for proton, helium and carbon ions, respectively. Within measurement uncertainties, these values verified the calculated WEPLs of 20.28 mmH2O (proton), 20.28 mmH2O (helium) and 20.26 mmH2O (carbon). Moreover, the calculated proton inelastic cross sections of the material differed only by 0.89% (100 MeV/u) and 0.01% (200 MeV/u) when compared to water. Conclusion: The SAM is capable of optimizing material with defined properties, e.g., HU, electron density, WEPL and inelastic nuclear interaction cross section for particle therapy. Such material will have a wide range of applications amongst others absolute dosimetry. This work was supported by grant ZIM KF2137107AK4 from the German Federal Ministry for Economic Affairs and Energy.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2025

RTx-303, an Orally Bioavailable Polθ Polymerase Inhibitor That Potentiates PARP Inhibitors in BRCA Mutant Tumors

Abstract DNA polymerase θ (Polθ) is a polymerase-helicase fusion protein that is synthetically lethal with homologous recombination (HR) factors, such as BRCA1/2, and confers resistance to PARP inhibitors (PARPi) and other genotoxic cancer therapies. Previously developed Polθ polymerase (Polθ-pol) inhibitors (Polθi) exhibited limited pharmacological activity and metabolic stability, warranting the development of a Polθi with improved drug-like properties. Here, we developed RTx-303, a selective allosteric small-molecule Polθ-pol inhibitor that exhibits 5.1 nM IC50, 88% oral bioavailability, and a prolonged half-life along with its equipotent metabolite. X-ray crystallography highlights the development of a solvent-exposed side-chain that is essential for the optimal drug-like properties of RTx-303. Notably, RTx-303 exhibits significantly higher cellular potency than previously developed Polθ-pol inhibitors and strongly potentiates PARPi in BRCA1/2 mutant cells and patient-derived xenograft models. The superior potency, robust pharmacological activity, and high tolerability of RTx-303 warrant further development as a Polθ-pol inhibitor drug candidate.

Chandramouly, Gurushankar [Thomas Jefferson Univer↗

DOE OSTI2014

Near-surface depletion of antimony during the growth of GaAsSb and GaAs/GaAsSb nanowires

The near-surface reduction of the Sb mole fraction during the growth of GaAsSb nanowires (NWs) and GaAs NWs with GaAsSb inserts has been studied using quantitative high-angle annular dark field scanning transmission electron microscopy (STEM). A model for diffusion of Sb in the hexagonal NWs was developed and employed in combination with the quantitative STEM analysis. GaAsSb NWs grown by Ga-assisted molecular beam epitaxy (MBE) and GaAs/GaAsSb NWs grown by Ga- and Au-assisted MBE were investigated. At the high temperatures employed in the NW growth, As-Sb exchange at and outward diffusion of Sb towards the surface take place, resulting in reduction of the Sb concentration at and near the surface in the GaAsSb NWs and the GaAsSb inserts. In GaAsSb NWs, an increasing near-surface depletion of Sb was observed towards the bottom of the NW due to longer exposure to the As beam flux. In GaAsSb inserts, an increasing change in the Sb concentration profile was observed with increasing post-insert axial GaAs growth time, resulting from a combined effect of radial GaAs overgrowth and diffusion of Sb. The effect of growth temperature on the diffusion of Sb in the GaAsSb inserts was identified. The consequences of these findings for growth optimization and the optoelectronic properties of GaAsSb are discussed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2018

Development and Optimization of Voltammetric Methods for Real Time Analysis of Electrorefiner Salt with High Concentrations of Actinides and Fission Products

This project addresses the problem of achieving accurate material control and accountability (MC&A) around pyroprocessing electrorefiner systems. Spent nuclear fuel pyroprocessing poses a unique challenge with respect to reprocessing technology in that the fuel is never fully dissolved in the process fluid. In this case, the process fluid is molten, anhydrous LiCl-KCl salt. Therefore, there is no traditional input accountability tank. However, electrorefiners (ER) accumulate very large quantities of fissile nuclear material (including plutonium) and should be well safeguarded in a commercial facility. Idaho National Laboratory (INL) currently operates a pyroprocessing facility for treatment of spent fuel from Experimental Breeder Reactor-II with two such ER systems. INL implements MC&A via a mass tracking model in combination with periodic sampling of the salt and other materials followed by destructive analysis. This approach is projected to be insufficient to meet international safeguards timeliness requirements. A real time or near real time monitoring method is, thus, direly needed to support commercialization of pyroprocessing. A variety of approaches to achieving real time monitoring for ER salt have been proposed and studied to date—including a potentiometric actinide sensor for concentration measurements, a double bubbler for salt depth and density measurements, and laser induced breakdown spectroscopy (LIBS) for concentration measurements. While each of these methods shows some promise, each also involves substantial technical complexity that may ultimately limit their implementation. Yet another alternative is voltammetry —a very simple method in theory that has previously been tested for this application to a limited extent. The equipment for a voltammetry system consists of off-the-shelf components (three electrodes and a potentiostat), which results in substantial benefits relative to cost and robustness. Based on prior knowledge of electrochemical reduction potentials for each of the species of interest, voltammetry can be used to quantify concentrations of a variety of elemental species—including uranium, plutonium, minor actinides, and rare earths. Various methods have been tested by other researchers to date—including cyclic voltammetry, square wave voltammetry, normal pulse voltammetry, etc. In most cases, it has been observed that there is a very limited concentration range for which the output can be readily correlated with concentration in the salt. Furthermore, testing to date has been limited to simple ternary salts with only a single element being quantified. While incomplete for application to MC&A for pyroprocessing, these results lead us to believe that voltammetry can be optimized based on salt properties and fundamental electrochemical rate processes to yield a highly accurate and robust method. This project is divided into four tasks jointly executed by three university research groups. This includes experimental measurement of key physical data on the systems of interest, development of a predictive voltammetry model, experimental validation of the voltammetry model, and design/verification of an optimized measurement method. This project supports the goals of the US-ROK Joint Fuel Cycle Study in addition to the NA-24 Office of the National Nuclear Security Agency and the International Atomic Energy Agency (IAEA).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Generative AI for design of nanoporous materials: review and future prospects

Generative artificial intelligence (AI) is emerging as a powerful tool for advancing the design of nanoporous materials such as metal–organic frameworks, covalent–organic frameworks, and zeolites. These materials have potential application in important areas such as carbon capture, catalysis, gas storage, chemical separation, and drug delivery due to their modular, tunable structures, and their performance in these areas depends on precise control over their structure, chemical functionalities, and properties. Herein, we provide a review of generative AI algorithms that are emerging as powerful tools for the design of nanoporous materials, namely generative adversarial networks, variational autoencoders, diffusion models, genetic algorithms, reinforcement learning, and large language models. Some models are particularly good at generating diverse and high-quality designs, while others excel at exploring large design spaces or optimizing materials with desired properties. Certain algorithms also allow for efficient transitions between different designs, and some offer versatility in generating materials based on textual input. We discuss the advantages, limitations, and applications of these algorithms in porous material design and emphasize the future potential of integrating AI with experimental workflows to accelerate the development and validation of AI-generated materials.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Computational Tools and Algorithms for Designing Customized Synthetic Genes

Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Low-field magnetoresistance up to 400 K in double perovskite Sr{sub 2}FeMoO{sub 6} synthesized by a citrate route

A wet-chemistry technique, namely the citrate route, has been used to prepare high-quality polycrystalline samples of double perovskite Sr{sub 2}FeMoO{sub 6}. We report on the evolution of magnetic and magnetoresistive properties of the synthesized samples as a function of three parameters (i) the pH of the starting solution, (ii) the decomposition temperature of the citrate precursors and (iii) the sintering conditions. The low-field magnetoresistance (LFMR) value of our best samples is as high as 5% at room temperature for an applied magnetic field of 1 kOe. Additionally, the distinguishing feature of these samples is the persistence of LFMR, with a reasonably large value, up to 400 K which is a crucial parameter for any practical application. Our study indicates that the enhancement of LFMR observed is due to a good compromise between the grain size distribution and their magnetic polarization. -- Graphical abstract: The microstructure (left panel) and corresponding low-field magnetoresistance of one of the Sr{sub 2}FeMoO{sub 6} samples synthesized in the course of this work. Highlights: • Samples of Sr{sub 2}FeMoO{sub 6} are prepared using a citrate route under varying conditions. • Magnetoresistive properties are improved and optimized. • Low-field magnetoresitence values as large as 5% at 300 K/1 kOe are reported. • Persistence of low-field magnetoresistance up to 400 K.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Effect of Properties/Injection Schedule on Fuel Spray Mixing

The DOE project for Co-Optimization of Fuels and Engines seeks to define both fuel properties and engine hardware to create cleaner and more fuel-efficient engines. Fuel spray technologies are central to this goal as the spray injection determines the combustible mixtures formed within the engine. Sprays are known to affect bum rate and efficiency, particulate formation and emissions, as well as temperature and engine knock sites. Computational fluid dynamic models must predict complicated interaction between plumes and vaporization to be useful as a design tool for industry. Changes in fuel properties are expected to affect fuel delivery. While Co-Optima fuels may be selected for chemical criteria, such as high octane number rating, an understanding of how the physical properties affect spray performance is necessary to optimize fuel delivery. Many of the selected Co-Optima fuels have properties that are different than standard gasoline, requiring investigations for their performance. A new continuous-flow spray chamber facility has been completed, offering capability to control the pressure and temperature of the gases at engine-relevant conditions at the time of injection as well as a massive increase in data throughput. Direct-injection multi-hole gasoline sprays for different Co-Optima fuels are investigated in this chamber.

02 PETROLEUM↗

DOE OSTI2021

Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications

Deep neural networks have been successfully employed in an extensive variety of research areas, including solving partial differential equations. Despite its significant success, there are some challenges in effectively training DNN, such as avoiding overfitting in over-parameterized DNNs and accelerating the optimization in DNNs with pathological curvature. Here, we propose a Bayesian type sparse deep learning algorithm. The algorithm utilizes a set of spike-and-slab priors for the parameters in the deep neural network. The hierarchical Bayesian mixture will be trained using an adaptive empirical method. That is, one will alternatively sample from the posterior using preconditioned stochastic gradient Langevin Dynamics (PSGLD), and optimize the latent variables via stochastic approximation. The sparsity of the network is achieved while optimizing the hyperparameters with adaptive searching and penalizing. A popular SG-MCMC approach is Stochastic gradient Langevin dynamics (SGLD). However, considering the complex geometry in the model parameter space in nonconvex learning, updating parameters using a universal step size in each component as in SGLD may cause slow mixing. To address this issue, we apply a computationally manageable preconditioner in the updating rule, which provides a step-size parameter to adapt to local geometric properties. Moreover, by smoothly optimizing the hyperparameter in the preconditioning matrix, our proposed algorithm ensures a decreasing bias, which is introduced by ignoring the correction term in the preconditioned SGLD. According to the existing theoretical framework, we show that the proposed algorithm can asymptotically converge to the correct distribution with a controllable bias under mild conditions. Numerical tests are performed on both synthetic regression problems and learning solutions of elliptic PDE, which demonstrate the accuracy and efficiency of the present work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Experimental Assessment of Elastic Modulus vs. Relative Density for Stretch- and Bend-Dominated Lattices

This project was designed to study the possibility of using structural properties of lattices to replicate the material properties of certain hard to manufacture designs and use topology optimization to determine the lattice type and density required to mimic these properties. The integration of additively manufactured lattice structures with topology optimization highlights the need for well characterized mechanical properties and uncertainty analyses to insure these optimized structures respond as predicted. Stereolithographically printed octet and rhombic dodecahedron lattices were manufactured at 10%, 25% and 65% density by volume. As a separate task, yet integrated into this work, finite element analysis (FEA) was used to predict the printed lattice’s mechanical properties, which were then compared to our experimental results. After comparing FEA and experimentallymeasured elastic moduli, it was determined that the FEA provides highly reliable predictions for the modulus of these printed lattice structures. These lattices also exhibited greater tensile stiffness than that of the solid material demonstrating the flexibility that lattices provide to designing parts with designer structural properties. The accurate printing and reliable modeling of these lattices will enable topology optimization of complex parts from well-characterized rhombic dodecahedron and octet lattice structures of varying densities.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Advancements in the modification of TiFe alloys for enhanced hydrogen Storage: Strategies and future Directions

Hydrogen is considered a promising clean energy source, and a potential alternative to conventional fossil fuels. TiFe alloy has been particularly interesting due to its ability to reversibly absorb and desorb hydrogen at room temperature and low pressure. The initial hydrogen absorption stage of TiFe alloy requires activation under high-temperature and high-pressure conditions, which hinders its practical application. Here, this paper primarily examines the impact of elemental substitution methods on the hydrogen storage capabilities of TiFe alloys, with a particular emphasis on elucidating the mechanisms associated with various substituent elements. Commonly utilized elements, such as Mn, V, and Zr, significantly improve the activation performance of TiFe alloys. Additionally, the incorporation of elements such as Ni, Cr, Ce, and Y contributes to the modulation of phase composition, as well as the enhancement of activation and kinetic properties. However, there exists a notable deficiency in systematic investigations concerning alternative elements, coupled with a frequent oversight of the preparation process's influence on the hydrogen storage characteristics of these alloys. Consequently, the mechanisms by which different elements affect the hydrogen storage process in TiFe alloys remain inadequately understood among current research, thereby complicating the establishment of experiment-based design guidelines for TiFe alloys. Furthermore, the plasma treatment and high-entropy alloying present new approaches for optimizing the hydrogen storage properties of TiFe alloys. This paper aims to present novel research perspectives and insights to scholars in the field by introducing methods for the modification of TiFe alloys.

Hydrogen storage↗

DOE OSTI2025

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs

Applications of deep learning (DL) to design nanomaterials are hampered by a lack of suitable data representations and training data. Here, in this study, we report efforts to overcome these limitations and leverage DL to optimize the nonlinear optical properties of core–shell upconverting nanoparticles (UCNPs). UCNPs, which have applications in fields such as biosensing, super-resolution microscopy and three-dimensional printing, can emit visible and ultraviolet light from near-infrared excitations. We report a large-scale dataset of UCNP emission spectra based on accurate but expensive kinetic Monte Carlo simulations (N > 6,000) and use these data to train a heterogeneous graph neural network using a physically motivated representation of UCNP nanostructure. Applying gradient-based optimization on the trained graph neural network, we identify structures with 6.5× higher predicted emission under 800-nm illumination than any UCNP in our training set. Our work reveals design principles for UCNP heterostructures and presents a roadmap for DL-based inverse design of nanomaterials.

Sivonxay, Eric [Lawrence Berkeley National Laborat↗

DOE OSTI2025

Influence of counterion substitution on the properties of imidazolium-based ionic liquid clusters

Due to their unique physiochemical properties that may be tailored for specific purposes, ionic liquids (ILs) have been investigated for various applications, including chemical separations, catalysis, energy storage, and space propulsion. The different cations and anions comprising ILs may be selected to optimize a range of desired properties, such as thermal stability, ionic conductivity, and volatility, leading to the designation of certain ILs as designer “green” solvents. The effect of counterions on the properties of ILs is of both fundamental scientific interest and technological importance. Herein, we report a systematic experimental and theoretical investigation of the size, charge, stability toward dissociation, and geometric/electronic structure of 1-ethyl-3-methyl imidazolium (EMIM)-based IL clusters containing two different atomic counterions (i.e., bromide [Br − ] and iodide [I − ]). This work extends our studies of EMIM + cations with atomic chloride (Cl − ) and molecular tetrafluoroborate (BF 4 − ) anions reported previously by Baxter et al. [Chem. Mater. 34, 2612 (2022)] and Zhang et al . [J. Phys. Chem. Lett. 11, 6844 (2020)], respectively. Distributions of anionic IL clusters were generated in the gas phase using electrospray ionization and characterized by high mass resolution mass spectrometry, energy-resolved collision-induced dissociation, and negative ion photoelectron spectroscopy experiments. The experimental results reveal anion-dependent trends in the size distribution, relative abundance, ionic charge state, stability toward dissociation, and electron binding energies of the IL clusters. Complementary global optimization theory provides molecular-level insights into the bonding and electronic structure of a selected subset of clusters, including their low energy structures and electrostatic potential maps, and how these fundamental characteristics are influenced by anion substitution. Collectively, our findings demonstrate how the fundamental properties of ILs, which determine their suitability for many applications, may be tuned by substituting counterions. These observations are critical in the sub-nanometer cluster size regime where phenomena do not scale predictably to the bulk phase, and each atom counts toward determining behavior.

cluster↗

DOE OSTI2012

Energy Saving Melting and Revert Reduction (E-SMARRT): Optimization of Heat Treatments on Stainless Steel Castings for Improved Corrosion Resistance and Mechanical Properties

It is commonly believed that high alloy steel castings have inferior corrosion resistance to their wrought counterparts as a result of the increased amount of microsegregation remaining in the as-cast structure. Homogenization and dissolution heat treatments are often utilized to reduce or eliminate the residual microsegregation and dissolve the secondary phases. Detailed electron probe microanalysis (EPMA) and light optical microscopy (LOM) were utilized to correlate the amount of homogenization and dissolution present after various thermal treatments with calculated values and with the resultant corrosion resistance of the alloys.The influence of heat treatment time and temperature on the homogenization and dissolution kinetics were investigated using stainless steel alloys CN3MN and CK3MCuN. The influence of heat treatment time and temperature on the impact toughness and corrosion reistance of cast stainless steel alloys CF-3, CF-3M, CF-8, and CF-8M was also investigated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Ultra low density biodegradable shape memory polymer foams with tunable physical properties

Compositions and/or structures of degradable shape memory polymers (SMPs) ranging in form from neat/unfoamed to ultra low density materials of down to 0.005 g/cc density. These materials show controllable degradation rate, actuation temperature and breadth of transitions along with high modulus and excellent shape memory behavior. A method of m ly low density foams (up to 0.005 g/cc) via use of combined chemical and physical aking extreme blowing agents, where the physical blowing agents may be a single compound or mixtures of two or more compounds, and other related methods, including of using multiple co-blowing agents of successively higher boiling points in order to achieve a large range of densities for a fixed net chemical composition. Methods of optimization of the physical properties of the foams such as porosity, cell size and distribution, cell openness etc. of these materials, to further expand their uses and improve their performance.

36 MATERIALS SCIENCE↗