000263498 001__ 263498
000263498 005__ 20190619220157.0
000263498 022__ $$a0022-3727
000263498 022__ $$a1361-6463
000263498 02470 $$a000448410100001$$2isi
000263498 0247_ $$a10.1088/1361-6463/aad926$$2doi
000263498 037__ $$aARTICLE
000263498 245__ $$aThe 2019 materials by design roadmap
000263498 260__ $$c2019$$aBristol$$bIOP PUBLISHING LTD
000263498 269__ $$a2019-01-02
000263498 336__ $$aReviews
000263498 520__ $$aAdvances in renewable and sustainable energy technologies critically depend on our ability to design and realize materials with optimal properties. Materials discovery and design efforts ideally involve close coupling between materials prediction, synthesis and characterization. The increased use of computational tools, the generation of materials databases, and advances in experimental methods have substantially accelerated these activities. It is therefore an opportune time to consider future prospects for materials by design approaches. The purpose of this Roadmap is to present an overview of the current state of computational materials prediction, synthesis and characterization approaches, materials design needs for various technologies, and future challenges and opportunities that must be addressed. The various perspectives cover topics on computational techniques, validation, materials databases, materials informatics, high-throughput combinatorial methods, advanced characterization approaches, and materials design issues in thermoelectrics, photovoltaics, solid state lighting, catalysts, batteries, metal alloys, complex oxides and transparent conducting materials. It is our hope that this Roadmap will guide researchers and funding agencies in identifying new prospects for materials design.
000263498 650__ $$aPhysics, Applied
000263498 650__ $$aPhysics
000263498 6531_ $$adensity functional theory
000263498 6531_ $$amaterials genome initative
000263498 6531_ $$amaterials design
000263498 6531_ $$ahigh-throughput methods
000263498 6531_ $$aenergy applications
000263498 6531_ $$alight-emitting-diodes
000263498 6531_ $$adensity-functional theory
000263498 6531_ $$aperovskite solar-cells
000263498 6531_ $$ahigh-throughput characterization
000263498 6531_ $$aorganometal halide perovskites
000263498 6531_ $$amonte-carlo simulations
000263498 6531_ $$alead iodide perovskite
000263498 6531_ $$alithium-ion batteries
000263498 6531_ $$amaterials discovery
000263498 6531_ $$amaterials science
000263498 700__ $$aAlberi, Kirstin
000263498 700__ $$aNardelli, Marco Buongiorno
000263498 700__ $$aZakutayev, Andriy
000263498 700__ $$aMitas, Lubos
000263498 700__ $$aCurtarolo, Stefano
000263498 700__ $$aJain, Anubhav
000263498 700__ $$aFornari, Marco
000263498 700__ $$g210230$$0246415$$aMarzari, Nicola
000263498 700__ $$aTakeuchi, Ichiro
000263498 700__ $$aGreen, Martin L.
000263498 700__ $$aKanatzidis, Mercouri
000263498 700__ $$aToney, Mike F.
000263498 700__ $$aButenko, Sergiy
000263498 700__ $$aMeredig, Bryce
000263498 700__ $$aLany, Stephan
000263498 700__ $$aKattner, Ursula
000263498 700__ $$aDavydov, Albert
000263498 700__ $$aToberer, Eric S.
000263498 700__ $$aStevanovic, Vladan
000263498 700__ $$aWalsh, Aron
000263498 700__ $$aPark, Nam-Gyu
000263498 700__ $$aAspuru-Guzik, Alan
000263498 700__ $$aTabor, Daniel P.
000263498 700__ $$aNelson, Jenny
000263498 700__ $$aMurphy, James
000263498 700__ $$aSetlur, Anant
000263498 700__ $$aGregoire, John
000263498 700__ $$aLi, Hong
000263498 700__ $$aXiao, Ruijuan
000263498 700__ $$aLudwig, Alfred
000263498 700__ $$aMartin, Lane W.
000263498 700__ $$aRappe, Andrew M.
000263498 700__ $$aWei, Su-Huai
000263498 700__ $$aPerkins, John
000263498 773__ $$q013001$$k1$$j52$$tJournal Of Physics D-Applied Physics
000263498 909CO $$ooai:infoscience.epfl.ch:263498$$preview
000263498 961__ $$afantin.reichler@epfl.ch
000263498 973__ $$aEPFL$$sPUBLISHED$$rREVIEWED
000263498 980__ $$aREVIEW
000263498 980__ $$aWoS
000263498 981__ $$aoverwrite
000263498 999C0 $$0252461$$mnicola.marzari@epfl.ch$$zMarselli, Béatrice$$pTHEOS$$xU12411