July/August_AMP_Digital

A D V A N C E D M A T E R I A L S & P R O C E S S E S | J U L Y / A U G U S T 2 0 1 8 1 5 ICME is another exciting area. In- tegration of modeling with materials manufacturing—covering all aspects from materials processing to micro- structure evolution to predicting ma- terials properties to then linking these properties to design and performance— will continue to increase in importance. John Ågren: Machine learning, CALPHAD (including DFT), and process modeling will be combined to make precise predictions to be used in ma- terials and component design. In addi- tion, materials and component design (topology optimization) will be com- bined to use additive manufacturing to achieve superior performance of engi- neering components. Jennie Hwang: One of the most intriguing advances is in 2D materials. These single-layer materials are ex- pected to offer breakthrough perfor- mance in numerous applications, such as a new generation of electronic devic- es. Another area involves advancing the basic understanding of quantum entan- glement to develop leading materials technologies. What opportunities do you see in the materials science arena related to new technology areas such as big data, artificial intelligence (AI), additive manufacturing, the Internet of Things (IoT), and autonomous vehicles? Hwang: In electric vehicles, I see opportunities for materials technolo- gies to make higher performance and/ or more economical batteries; in ad- ditive manufacturing, to make metal processes more reproducible to deliv- er consistent mechanical properties; and in IoT and AI, to align hardware de- sign and manufacturing with market demands. Gray: In addition to additive man- ufacturing, multifunctional materials that meet several requirements simul- taneously are another promising area. One illustration is structural elements within a larger device or platform that also serve as energy components such as batteries or solar collectors. Appli- cations abound within the land/water transportation, aerospace, and build- ing industries. Matlock: Obviously, multiple op- portunities exist and will evolve with each of the new technologies men- tioned. As reliance on big data and ar- tificial intelligence continues to grow, it will also be necessary for the engineers of the future not to ignore developing their “common sense” so that they will be in a position to realistically assess outcomes of computer-based analyses. In the materials field, develop- ments in sensor technology and ad- vanced analytical tools will provide new and greatly expanded data sets that will need to be managed. For ex- ample, traditional tensile testing in- volving data obtained from load cells and extensometers typically resulted in three primary data sets including load, displacement, and time. With the development of digital image correla- tion (DIC) techniques, data files map strains in two dimensions, as opposed to the uniaxial data obtained with an extensometer. As a result, data files are significantly larger and comput- er programs will be required to extract meaningful data from the tests without What major technology advancements in materials do you anticipate over the next decade? David Matlock: Integrated com- putational materials engineering (ICME) is now rapidly developing. I anticipate that over the next decade, we will see results where first-principle ICME tools actually lead to the identification and commercialization of new materials with unique properties, or significantly improved and more efficient process- ing routes for existing materials. Addi- tivemanufacturing will alsomature and be incorporated, where appropriate, in multiple industries. Due to the expanding global population and growth in consumer economies in multiple countries, de- velopment of global strategies to man- age critical material resources to ensure sustainable sources for future applica- tions will be an important goal for all. Rusty Gray: While the hype has been extensive over the past several years, additive manufacturing remains an exciting technology capable of re- ducing the time to optimization and material/component insertion through accelerated prototyping and experi- mentation. Nevertheless, careful con- sideration is needed regarding the cost of pedigreed feed materials (powder or wire), cost of AM machines, cost of op- eration of AM production, and the cur- rently modest rate of build production. These challenges place AM in the re- gime of being most beneficial to proto- typing and thereafter focused on high value/low volume production. Additive manufacturing is making steady progress for printing everything fromplas- tics to metals to human tissue. Courtesy of NYU. Intel’s field programmable gate arrays are accelerating artificial intelligence for deep learning in Bing, Microsoft’s intelligent search engine. Washable, ultra-thin organic solar cells fromRiken in Japan.