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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Magnetic field experiment for Voyagers 1 and 2

The magnetic field experiment to be carried on the Voyager 1 and 2 missions consists of dual low field (LFM) and high field magnetometer (HFM) systems. The dual systems provide greater reliability and, in the case of the LFM's, permit the separation of spacecraft magnetic fields from the ambient fields. Additional reliability is achieved through electronics redundancy. The wide dynamic ranges of plus or minus 0.5G for the LFM's and plus or minus 20G for the HFM's, low quantization uncertainty of plus or minus 0.002 gamma in the most sensitive (plus or minus 8 gamma) LFM range, low sensor RMS noise level of 0.006 gamma, and use of data compaction schemes to optimize the experiment information rate all combine to permit the study of a broad spectrum of phenomena during the mission. Planetary fields at Jupiter, Saturn, and possibly Uranus; satellites of these planets; solar wind and satellite interactions with the planetary fields; and the large-scale structure and microscale characteristics of the interplanetary magnetic field are studied. The interstellar field may also be measured.

Behannon, K. W.↗
NASA NTRS1990

Recent experience with multidisciplinary analysis and optimization in advanced aircraft design

The task of modern aircraft design has always been complicated due to the number of intertwined technical factors from the various engineering disciplines. Furthermore, this complexity has been rapidly increasing by the development of such technologies as aeroelasticity tailored materials and structures, active control systems, integrated propulsion/airframe controls, thrust vectoring, and so on. Successful designs that achieve maximum advantage from these new technologies require a thorough understanding of the physical phenomena and the interactions among these phenomena. A study commissioned by the Aeronautical Sciences and Evaluation Board of the National Research Council has gone so far as to identify technology integration as a new discipline from which many future aeronautical advancements will arise. Regardless of whether one considers integration as a new discipline or not, it is clear to all engineers involved in aircraft design and analysis that better methods are required. In the past, designers conducted parametric studies in which a relatively small number of principal characteristics were varied to determine the effect on design requirements which were themselves often diverse and contradictory. Once a design was chosen, it then passed through the various engineers' disciplines whose principal task was to make the chosen design workable. Working in a limited design space, the discipline expert sometimes improved the concept, but more often than not, the result was in the form of a penalty to make the original concept workable. If an insurmountable problem was encountered, the process began over. Most design systems that attempt to account for disciplinary interactions have large empirical elements and reliance on past experience is a poor guide in obtaining maximum utilizations of new technologies. Further compounding the difficulty of design is that as the aeronautical sciences have matured, the discipline specialist's area of research has generally narrowed as more sophisticated methods are developed in the specialist's area of expertise. The results have been a decrease in the awareness of the impact of his decisions on other disciplines. This paper will outline the progress and problems encountered in the analysis, design, optimization sensitivity analysis, mathematical modeling, and configurations control and the means by which they are being solved. The breadth versus depth dilemma in analysis and design and the means for coping with that dilemma will be discussed. Finally, the all-important human aspects and the need for a new 'culture ' for doing business in an integrated, multidisciplinary design environment are discussed.

Dollyhigh, Samuel M.↗
DOE OSTI2024

How Does Escherichia coli Allocate Proteome?

Microorganisms are shown to actively partition their intracellular resources, such as pro- teins, for growth optimization. Recent experiments have begun to reveal molecular com- ponents unpinning the partition; however, it remains unclear quantitatively how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation, and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that cellular ability of resource partition lies in an ultrasensitive, negative feedback control- ling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism which mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations, and is also efficient for biomass production over time. Furthermore, this work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Charged particle LET-spectra measurements aboard LDEF

The linear energy transfer (LET) spectra of charged particles was measured in the 5 to 250 keV/micron (water) interval with CR-39 and in the 500 to 1500 keV/micron (water) interval with polycarbonate plastic nuclear track detectors (PNTDs) under different shielding depths in the P0006 experiment. The optimal processing conditions were determined for both PNTDs in relation to the relatively high track densities due to the long term exposure in space. The total track density was measured over the selected samples, and tracks in coincidence on the facing surfaces of two detector sheets were selected for measuring at the same position on each sheet. The short range (SR) and Galactic Cosmic Ray (GCR) components were measured separately with CR-39 PNTDs and the integral dose and dose rate spectra of charged particles were also determined. The high LET portion of the LET spectra was measured with polycarbonate PNTDs with high statistical accuracy. This is a unique result of this exposure due to the low flux of these types of particles for typical spaceflight durations. The directional dependence of the charged particles at the position of the P0006 experiment was also studied by four small side stacks which surrounded the main stack and by analyzing the dip angle and polar angle distributions of the measured SR and GCR particle tracks in the main stack.

Csige, I.↗
DOE OSTI2020

Coupling High-Throughput Experiments and Regression Algorithms to Optimize PGM-Free ORR Electrocatalyst Synthesis

Over the past decades, significant improvement has been achieved in the performance of platinum group metal-free (PGM-free) materials as an alternative to Pt-based electrocatalysts for oxygen reduction reaction (ORR). However, further progress in ORR activity requires evaluation of precursors and synthesis approaches. In response to this challenge, we generated a first of its kind experimental data set of 36 samples using high-throughput synthesis and activity measurements. Several control parameters (e.g., Fe precursor identity, the precursor content, and pyrolysis temperature) were varied. We then developed several state-of-the-art machine learning (ML) based regression models to predict ORR activity, dependent on selected synthesis variables. Through an iterative algorithm, higher prediction accuracy (smaller root-mean-square error) was achieved. We identified that gradient boosting regression (GBR) and support vector regression (SVR), among several methods, work best for this data set. Aided by our ML-based surrogate models, we decided to alter catalyst synthesis conditions, which resulted in a 36% increase in measured ORR activity in comparison to the maximum ORR mass activity value of 21.9 A/g catalyst in the original data set. Overall, this combined experiment and machine learning approach represents a promising path forward toward developing highly efficient next-generation ORR electrocatalysts and, more generally, functional materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Assessing Customer Experience and Business Models around Price-to-Device Communication and Smart Control Pathways in CalFlexHub

California is facing three major challenges in electrical grid operation: renewable overgeneration, steep evening ramping, and growing peak demand. The state has identified dynamic retail price response as a key strategy evidenced by CPUC’s Dynamic Rates proceeding and CEC’s Load Management Standards. Furthermore, the CEC launched a $16M “California Load Flexibility Research and Deployment Hub (CalFlexHub)” administered by Berkeley Lab to accelerate price-response flexible load technologies in buildings and EV charging. There are more than 16 laboratory and field demonstration projects in CalFlexHub, each demonstrating innovative automated price-response technologies. CalFlexHub tests various pathways through which hourly price signals and triggered control commands are communicated to load-flexible devices such as smart thermostats, heat pumps, water heaters, and EVs. We identified seven unique communication and control pathways, which involve combinations of third-party cloud, device OEM’s cloud, building central gateway, and local controller in between the price server and the load-flexible devices. It is important for utilities and policy makers to understand the long-term implications of each pathway in designing future programs and creating related policies and mandates for market transformation. We propose an evaluation framework including the following aspects: ● Functionality: connectivity and uptime, resilience, and optimization; ● Customer experience: simplicity in setup, troubleshooting support, continuity, customer choice, first cost, and ongoing cost; ● Business model and scalability: advance interoperability, holistic solution, bridge unique gap, customer base, and value streams and pricing structures. In this paper, we identify emerging business models associated with each communication pathway and discuss their positive features and challenges from the above aspects.

Liu, Jingjing↗
DOE OSTI2023

FIRST RESULTS FROM Nb3Sn COATINGS OF 2.6 GHz Nb SRF CAVITIES USING DC CYLINDRICAL MAGNETRON SPUTTERING SYSTEM

A DC cylindrical magnetron sputtering system has been commissioned and operated to deposit Nb3Sn onto 2.6 GHz Nb SRF cavities. After optimizing the deposition conditions in a mock-up cavity, Nb-Sn films are deposited first on flat samples by multilayer sequential sputtering of Nb and Sn, and later annealed at 950 °C for 3 hours. X-ray diffraction of the films showed multiple peaks for the Nb3Sn phase and Nb (substrate). No peaks from any Nb-Sn compound other than Nb3Sn were detected. Later three 2.6 GHz Nb SRF cavities are coated with ~1 µm thick Nb3Sn. The first Nb3Sn coated cavity reached close to Eacc = 8 MV/m, demonstrating a quality factor Q0 of 3.2 × 108 at Tbath = 4.4 K and Eacc = 5 MV/m, about a factor of three higher than that of Nb at this temperature. Q0 was close to 1.1 × 109, dominated by the residual resistance, at 2 K and Eacc = 5 MV/m. The Nb3Sn coated cavities demonstrated Tc in the range of 17.9 ? 18 K. Here, we present the commissioning experience, system optimization, and the first results from the Nb3Sn fabrication on flat samples and SRF cavities.

Shakel, M.S.↗
DOE OSTI2023

FIRST RESULTS FROM Nb3Sn COATINGS OF 2.6 GHz Nb SRF CAVITIES USING DC CYLINDRICAL MAGNETRON SPUTTERING SYSTEM

A DC cylindrical magnetron sputtering system has been commissioned and operated to deposit Nb3Sn onto 2.6 GHz Nb SRF cavities. After optimizing the deposition conditions in a mock-up cavity, Nb-Sn films are deposited first on flat samples by multilayer sequential sputtering of Nb and Sn, and later annealed at 950 °C for 3 hours. X-ray diffraction of the films showed multiple peaks for the Nb3Sn phase and Nb (substrate). No peaks from any Nb-Sn compound other than Nb3Sn were detected. Later three 2.6 GHz Nb SRF cavities are coated with ~1 µm thick Nb3Sn. The first Nb3Sn coated cavity reached close to Eacc = 8 MV/m, demonstrating a quality factor Q0 of 3.2 × 108 at Tbath = 4.4 K and Eacc = 5 MV/m, about a factor of three higher than that of Nb at this temperature. Q0 was close to 1.1 × 109, dominated by the residual resistance, at 2 K and Eacc = 5 MV/m. The Nb3Sn coated cavities demonstrated Tc in the range of 17.9 ? 18 K. Here, we present the commissioning experience, system optimization, and the first results from the Nb3Sn fabrication on flat samples and SRF cavities.

Shakel, M. S.↗
DOE OSTI2023

First Results From Nb3Sn Coatings of 2.6 GHz Nb SRF Cavities Using DC Cylindrical Magnetron Sputtering System

A DC cylindrical magnetron sputtering system has been commissioned and operated to deposit Nb3Sn onto 2.6 GHz Nb SRF cavities. After optimizing the deposition conditions in a mock-up cavity, Nb-Sn films are deposited first on flat samples by multilayer sequential sputtering of Nb and Sn, and later annealed at 950°C for 3 hours. X-ray diffraction of the films showed multiple peaks for the Nb3Sn phase and Nb (substrate). No peaks from any Nb- Sn compound other than Nb3Sn were detected. Later three 2.6 GHz Nb SRF cavities are coated with ~1 μm thick Nb3Sn. The first Nb3Sn coated cavity reached close to Eacc = 8 MV/m, demonstrating a quality factor Q0 of $3.2 \times 108$ at Tbath = 4.4 K and Eacc = 5 MV/m, about a factor of three higher than that of Nb at this temperature. Q0 was close to $1.1 \times 109$, dominated by the residual resistance, at 2 K and Eacc = 5 MV/m. The Nb3Sn coated cavities demonstrated Tc in the range of $17.9 -- 18$ K. Here we present the commissioning experience, system optimization, and the first results from the Nb3Sn fabrication on flat samples and SRF cavities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

First Results from Nb3Sn Coatings of 2.6 GHz Nb SRF Cavities Using DC Cylindrical Magnetron Sputtering System

A DC cylindrical magnetron sputtering system has been commissioned and operated to deposit Nb3Sn onto 2.6 GHz Nb SRF cavities. After optimizing the deposition conditions in a mock-up cavity, Nb-Sn films are deposited first on flat samples by multilayer sequential sputtering of Nb and Sn, and later annealed at 950 {\deg}C for 3 hours. X-ray diffraction of the films showed multiple peaks for the Nb3Sn phase and Nb (substrate). No peaks from any Nb3Sn compound other than Nb3Sn were detected. Later three 2.6 GHz Nb SRF cavities are coated with ~1 $\mu$m thick Nb3Sn. The first Nb3Sn coated cavity reached close to Eacc = 8 MV/m, demonstrating a quality factor Q0 of 3.2 x 108 at Tbath = 4.4 K and Eacc = 5 MV/m, about a factor of three higher than that of Nb at this temperature. Q0 was close to 1.1 x 109, dominated by the residual resistance, at 2 K and Eacc = 5 MV/m. The Nb3Sn coated cavities demonstrated Tc in the range of 17.9 - 18 K. Here we present the commissioning experience, system optimization, and the first results from the Nb3Sn fabrication on flat samples and SRF cavities.

43 PARTICLE ACCELERATORS↗
NASA NTRS2019

NASA GeneLab Platform Utilized for Space Radiation Dosimetry Biological Response Compared to Radiation Ground Studies

Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The NASA GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) includes datasets from both spaceflight and ground-based studies, a majority of which involved exposure to ionizing radiation. Recently GeneLab has also assessed radiation dosimetry data with omics datasets associated with samples flown to the International Space Station (ISS). The combination of the detailed information on radiation exposure for ground-based studies and curated dosimetry information for spaceflight experiments allows GeneLab to be the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. We demonstrate the usefulness of these datasets by analyzing multiple GeneLab datasets associated with both radiation ground-based studies and spaceflight studies. The radiation ground based studies we analyzed includes both in vivo and in vitro work with a range ions from protons to iron particles with doses from 0.1Gy to 2Gy. These datasets were compared to both in vivo and in vitro datasets from samples flown to the ISS and on shorter shuttle missions with total doses of 0.1 mGy to 30 mGys. From this analysis we were able to associate distinct biological signatures associating specific ions to specific biological response to radiation exposure in space. For example, we discovered radiation biological response related to cardiovascular effects from proton ground studies are the dominating response for samples related to cardiovascular effects on the ISS. With this work we will provide a summary of how different ions will impact different biological response in space and how this can be used in future studies to assess optimal ground experiments to simulate space radiation.

Beheshti, Afshin↗
NASA NTRS1998

The development of spaceflight experiments with Arabidopsis as a model system in gravitropism studies

Experiments with Arabidopsis have been developed for spaceflight studies in the European Space Agency's Biorack module. The Biorack is a multiuser facility that is flown on the United States Space Shuttle and serves as a small laboratory for studying cell and developmental biology in unicells, plants, and small invertebrates. The purpose of our spaceflight research was to investigate the starch-statolith model for gravity perception by studying wild-type (WT) and three starch-deficient mutants of Arabidopsis. Since spaceflight opportunities for biological experimentation are scarce, the extensive ground-based testing described in this paper is needed to ensure the success of a flight project. Therefore, the specific aims of our ground-based research were: (1) to modify the internal configuration of the flight hardware, which originally was designed for large lentil seeds, to accommodate small Arabidopsis seeds; (2) to maximize seed germination in the hardware; and (3) to develop favorable conditions in flight hardware for the growth and gravitropism of seedlings. The hardware has been modified, and growth conditions for Arabidopsis have been optimized. These experiments were successfully flown on two Space Shuttle missions in 1997.

STS-84 Shuttle Project↗
DOE OSTI2024

Enhancements and Deployment of the TDAQ System for the Mu2e Experiment

The Real Time Processing Systems Division at Fermilab has deployed new features to the Off-The-Shelf Data Acquisition framework (otsdaq) for the Mu2e experiment. The Mu2e experiment will search for the coherent neutrino-less conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement of 10,000 times over existing limits. Such a charged lepton flavor-violating reaction probes new physics at a scale unavailable at present or planned high-energy colliders. The Mu2e Trigger and Data Acquisition (TDAQ) system uses otsdaq as its online Data Acquisition System (DAQ) framework. otsdaq integrates the artdaq and art frameworks for event transfer, filtering, and processing. otsdaq is a web-based DAQ software suite focusing on flexibility and scalability and provides a multi-user interface accessible through a web browser. artdaq handles the entire data stream, which is read over the peripheral component interconnect express (PCIe) bus to a software filter algorithm that selects events combined with the data flux coming from a cosmic-ray veto (CRV) system. Detector front-ends are configured through the PCIe bus by customized otsdaq plugins. The otsdaq slow controls infrastructure has been further developed using the experimental physics and industrial control system (EPICS) open-source platform for monitoring, controlling, alarming, and archiving. The detector control system (DCS) for Mu2e has been integrated into otsdaq. The production TDAQ and DCS system has been deployed at the experimental hall and is being debugged and optimized for experiment operations. We report on the feature enhancements and deployment of otsdaq for Mu2e.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2002

Structural Optimization of a Force Balance Using a Computational Experiment Design

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Parker, P. A.↗
DOE OSTI2023

Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing

Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these techniques lags behind their development in the lab. This means that material and process development proceeds largely via trial and error. This is sub-optimal since experiments are cost-, time-, and labor-intensive. In this work we propose a machine learning framework, differential property classification (DPC), which enables an experimenter to leverage machine learning's unparalleled pattern matching capability to pursue data-driven experimental design. DPC takes two possible experiment parameter sets and outputs a prediction of which will produce a material with a more desirable property specified by the operator. We demonstrate the success of DPC on AA7075 tube manufacturing process and mechanical property data using shear assisted processing and extrusion (ShAPE), an emerging solid phase processing technology. We show that by focusing on the experimenter's need to choose between multiple candidate experimental parameters, we can reframe the challenging regression task of predicting material properties from processing parameters, into a classification task on which machine learning models can achieve good performance.

advanced manufacturing, machine learning, ShAPE↗
DOE OSTI2023

Bayesian sequential optimal experimental design for nonlinear models using policy gradient reinforcement learning

We present a mathematical framework and computational methods for optimally designing a finite sequence of experiments. This sequential optimal experimental design (sOED) problem is formulated as a finite-horizon partially observable Markov decision process (POMDP) under a Bayesian setting and with information-theoretic utilities. The formulation is general and may accommodate continuous random variables, non-Gaussian posteriors, and nonlinear forward models. The sOED design policy incorporates elements of feedback and lookahead simultaneously, and we show it to generalize the commonly-used batch and greedy design strategies. We solve for the sOED policy using the policy gradient (PG) method from reinforcement learning, and provide a derivation for the PG expression in the sOED context. Adopting an actor-critic approach, the policy and value functions are parameterized using deep neural networks and improved via PG estimates produced from simulated episodes of designs and observations. The new PG-sOED algorithm is first validated on a linear-Gaussian benchmark, and then compared against other design baselines on a sensor movement problem for contaminant source inversion in a convection-diffusion field. As a result, we provide explanation for the policy behaviors using knowledge of the underlying physical process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Fabrication and durability characterization of superhydrophobic and lubricant-infused surfaces

Hypothesis: Practical applications of non-wetting surfaces require good mechanical durability in the wet environments for which they are intended to be used. Durability of non-wetting surfaces is influenced by the surface features, interaction with the functionalization agent, and the lubricant properties that can be tuned independently to identify optimal combination. Experiments: In this study, superhydrophobic and lubricant-infused surfaces are fabricated on copper tubes using chemical etching and electrodeposition texturing techniques, six different functionalizing agents, and five different infused lubricants. Through 180 fabrication combinations and 102 durability tests, each parameter is systematically studied for contributions to initial non-wetting behavior and its durability in heated, wet environment, under high-energy water jet impingement, and under accelerated flow conditions. Findings: Among the adsorbing and curing functionalization agents investigated, n-Hexadecyl mercaptan that belongs to the sulfhydryl group and Sylgard-184, respectively, showed high durability in heated water immersion and under jet impingement tests. For lubricant-infused surfaces, lubricants with high surface tension demonstrated high durability in heated water immersion test, whereas durability in hydrodynamic conditions is closely correlated to lubricant viscosity. Results showed that a lubricant-infused surface will maintain its non-wetting properties in dropwise condensation conditions for approximately 1.5 years.

36 MATERIALS SCIENCE↗