Skip to main content
SpringerLink
Log in
Book cover

Handbook of Materials Modeling pp 37–48Cite as

The Long and Winding Road: Predicting Materials Properties Through Theory and Computation

  • Reference work entry
  • First Online:

Abstract

First-principles simulations of materials provide both computational microscopes and predictive tools, which we aspire to turn into design strategies for materials with target properties. One requisite to meet this goal is the enablement of predictions of material properties on a large scale, so as to generate a vast amount of validated computational data that may eventually be used to solve inverse problems. However it is challenging to use big data to address the “why question.” First-principles calculations of specific materials and properties can instead be extremely effective at answering the “why question,” namely, at unraveling mechanisms and providing fundamental, physical insights, thus paving the way to innovative design strategies. In this chapter, we present first-principles predictions of material properties relevant to energy conversion processes. We also discuss some open challenges related to automated integration of theory and computation with experiments and with validated, interpreted data.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   799.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   999.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Adorf CS, Dodd PM, Ramasubrami V, Glotzer SC (2018) Simple data and workflow management with the signac framework. Comput Mater Sci 146:220

    Article  Google Scholar 

  • Bennett CH, DiVincenzo DP (2000) Quantum information and computation. Nature 404:247–255

    Article  ADS  MATH  Google Scholar 

  • Bhat TN, Bartolo LM, Kattner UR, Campbell CE, Elliot JT (2015) Strategy for extensible, evolving terminology for the materials genome initiative efforts. JOM 67:1866

    Article  Google Scholar 

  • Blaiszik B, Chard K, Pruyne J, Ananthakrishnan R, Tuecke S, Foster I (2016) The materials data facility: data services to advance materials science research. JOM 68:8

    Article  Google Scholar 

  • Blum V, Gehrke R, Hanke F, Havu P, Havu V, Ren X, Reuter K, Scheffler M (2009) Ab initio molecular simulations with numeric atom-centered orbitals. Comput Phys Commun 180:2175–2196

    Article  ADS  MATH  Google Scholar 

  • Castelli IE, Hüser F, Pandey M, Li H, Thygesen KS, Seger B, Jain A, Persson KA, Ceder G, Jacobsen KW (2015) New light-harvesting materials using accurate and efficient bandgap calculations. Adv Energy Mater 5:1400915

    Article  Google Scholar 

  • Chard K, Dart E, Foster I, Shifflett D, Tuecke S, Williams J (2018) The Modern Research Data Portal: a design pattern for networked, data-intensive science. PeerJ Comput Sci 4:e144

    Article  Google Scholar 

  • Curtarolo S, Setyawan W, Wang S, Xue J, Yang K, Taylor RH, Nelson LJ, Hart GLW, Sanvito S, Buongiorno-Nardelli M, Mingo N, Levy O (2012) AFLOWLIB.ORG: a distributed materials properties repository from high-throughput ab initio calculations. Comput Mater Sci 58:227

    Article  Google Scholar 

  • De Mauro A, Greco M, Grimaldi M (2015) What is big data? A consensual definition and a review of key research topics. AIP Conf Proc 1644:97–104

    Article  ADS  Google Scholar 

  • De Yoreo J, Mandrus D, Soderholm L (2016) Basic research needs for synthesis science: report of the basic energy sciences workshop on synthesis science for energy relevant technology. https://science.energy.gov/~/media/bes/pdf/reports/2017/BRN_SS_Rpt_web.pdf

  • Freire J, Chirigati F (2018) Provenance and the different flavors of computational reproducibility. IEEE Data Eng Bull 41(1):15–26. http://sites.computer.org/debull/A18mar/p15.pdf

  • Gerosa M, Gygi F, Govoni M, Galli G (2018) The role of defects and excess surface charges at finite temperature for optimizing oxide photoabsorbers. Nat Mater 17:1122–1127

    Article  ADS  Google Scholar 

  • Giannozzi P, Baroni S, Bonini N, Calandra M, Car R, Cavazzoni C, Ceresoli D, Chiarotti GL, Cococcioni M, Dabo I, Dal Corso A, de Gironcoli S, Fabris S, Fratesi G, Gebauer R, Gerstmann U, Gougoussis C, Kokalj A, Lazzeri M, Martin-Samos L, Marzari N, Mauri F, Mazzarello R, Paolini S, Pasquarello A, Paulatto L, Sbraccia C, Scandolo S, Sclauzero G, Seitsonen AP, Smogunov A, Umari P, Wentzcovitch RM (2009) QUANTUM ESPRESSO: a modular and open- source software project for quantum simulations of materials. J Phys Condens Matter 21:395502

    Article  Google Scholar 

  • Govoni M, Munakami M, Tanikanti A, Skone JH, Runesha HB, Giberti F, de Pablo J, Galli G (2019) Qresp, a tool for curating, discovering, and exploring reproducible scientific papers. Sci Data 6:190002. https://www.nature.com/articles/sdata20192

  • Greeley J, Jaramillo TF, Bonde J, Chorkendorff IB, Nørskov JK (2006) Computational high-throughput screening of electrocatalytic materials for hydrogen evolution. Nat Mater 5:909–913

    Article  ADS  Google Scholar 

  • Greenwood AR, Vörös M, Giberti F, Galli G (2018) Emergent electronic and dielectric properties of interacting nanoparticles at finite temperature. Nano Lett 18:255–261

    Article  ADS  Google Scholar 

  • Gygi F (2008) Architecture of Qbox: a scalable first-principles molecular dynamics code. IBM J Res Dev 52:137–144

    Article  Google Scholar 

  • Heyd J, Scuseria GE, Ernzerhof M (2003) Hybrid functionals based on a screened Coulomb potential. J Chem Phys 118:8207

    Article  ADS  Google Scholar 

  • Heyd J, Scuseria GE, Ernzerhof M (2006) Erratum: hybrid functionals based on a screened Coulomb potential. J Chem Phys 124:219906

    Article  ADS  Google Scholar 

  • Hohenberg P, Kohn W (1964) Inhomogeneous electron gas. Phys Rev 136:B864

    Article  ADS  MathSciNet  Google Scholar 

  • Hutter J, Iannuzzi M, Schiffmann F, VandeVondele J (2014) CP2K: atomistic simulations of condensed matter systems. Wiley Interdiscip Rev Comput Mol Sci 4:15–25

    Article  Google Scholar 

  • Jain A, Ong SP, Hautier G, Chen W, Richards WD, Dacek S, Cholia S, Gunter D, Skinner D, Ceder G, Persson KA (2013a) Commentary: the materials project: a materials genome approach to accelerating materials innovation. Appl Mater 1:011002

    Article  ADS  Google Scholar 

  • Jain A, Castelli IE, Hautier G, Bailey DH, Jacobsen KW (2013b) Performance of genetic algorithms in search for water splitting perovskites. J Mater Sci 48:6519–6534

    Article  ADS  Google Scholar 

  • Jain A, Ong SP, Chen W, Medasani B, Qu X, Kocher M, Brafman M, Petretto G, Rignanese G-M, Hautier G, Gunter D, Persson KA (2015) FireWorks: a dynamic workflow system designed for high-throughput applications. Concurr Comput Pract Exp 27:5037

    Article  Google Scholar 

  • Jain A, Persson KA, Ceder G (2016) Research update: the materials genome initiative: data sharing and the impact of collaborative ab initio databases. APL Mater 4:053102

    Article  ADS  Google Scholar 

  • Kaipio J, Somersalo E (2005) Statistical and computational inverse problems. Springer, New York

    MATH  Google Scholar 

  • Kalidindi SR, De Graef M (2015) Materials data science: current status and future outlook. Annu Rev Mater Res 45:171. https://www.annualreviews.org/doi/full/10.1146/annurev-matsci-070214-020844

    Article  ADS  Google Scholar 

  • Kohn W, Sham LJ (1965) Self-consistent equations including exchange and correlation effects. Phys Rev 140:A1133

    Article  ADS  MathSciNet  Google Scholar 

  • Kovalenko MV (2013) Chemical design of nanocrystal solids. Chimia 67:316–321

    Article  Google Scholar 

  • Kresse G, Furthmüller J (1996a) Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput Mater Sci 6:15. https://www.sciencedirect.com/science/article/pii/0927025696000080?via%3Dihub

    Article  Google Scholar 

  • Kresse G, Furthmüller J (1996b) Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys Rev B 54:11169. https://www.sciencedirect.com/science/article/pii/0927025696000080?via%3Dihub

    Article  ADS  Google Scholar 

  • Kresse G, Hafner J (1993) Ab initio molecular dynamics for liquid metals. Phys Rev B 47:558. https://journals.aps.org/prb/abstract/10.1103/PhysRevB.47.558

    Article  ADS  Google Scholar 

  • Kresse G, Hafner J (1994) Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium. Phys Rev B 49:14251. https://journals.aps.org/prb/abstract/10.1103/PhysRevB.49.14251

    Article  ADS  Google Scholar 

  • Kroemer H (2000) Quasi-electric fields and band offsets: teaching electrons new tricks. Nobel Prize Lecture, Stockholm. https://www.nobelprize.org/prizes/physics/2000/kroemer/lecture/

    Google Scholar 

  • Lee J-S, Kovalenko MV, Huang J, Chung DS, Talapin DV (2011) Band-like transport, high electron mobility and high photoconductivity in all-inorganic nanocrystal arrays. Nat Nanotechnol 6:348–352

    Article  ADS  Google Scholar 

  • Liu W, Lee J-S, Talapin DV (2013) III–V Nanocrystals capped with molecular metal chalcogenide ligands: high electron mobility and ambipolar photoresponse. J Am Chem Soc 135:1349–1357

    Article  Google Scholar 

  • Martin RM (2004) Electronic structure: basic theory and practical methods. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  • Martin RM, Reining L, Ceperley DM (2016) Interacting electrons: theory and computational approaches. Cambridge University Press, Cambridge

    Google Scholar 

  • McKone JR, Lewis NS, Gray HB (2013) Will solar-driven water-splitting devices see the light of day? Chem Mater 26:407–414

    Article  Google Scholar 

  • Meng H, Thain D (2017) Facilitating the reproducibility of scientific workflows with execution environment specifications. Proc Comput Sci 108:705. https://www.sciencedirect.com/science/article/pii/S1877050917306816

    Article  Google Scholar 

  • Obama B (2011) Remarks by the President at Carnegie Mellon University’s National Robotics Engineering Center. The Obama White House Archives. https://obamawhitehouse.archives.gov/the-press-office/2011/06/24/remarks-president-carnegie-mellon-universitys-national-robotics-engineer

  • Perdew JP, Ernzerhof M, Burke K (1996) Rationale for mixing exact exchange with density functional approximations. J Chem Phys 105:9982

    Article  ADS  Google Scholar 

  • Pham TA, Ping Y, Galli G (2017) Modelling heterogeneous interfaces for solar water splitting. Nat Mater 16:401–408

    Article  ADS  Google Scholar 

  • Pizzi G, Cepellotti A, Sabatini R, Marzari N, Kozinsky B (2016) AiiDA: automated interactive infrastructure and database for computational science. Comput Mater Sci 111:218

    Article  Google Scholar 

  • Rajan K (2015) Materials informatics: the materials “gene” and big data. Annu Rev Mater Res 45:153. https://www.annualreviews.org/doi/full/10.1146/annurev-matsci-070214-021132

    Article  ADS  Google Scholar 

  • Saal JE, Kirklin S, Aykol M, Meredig B, Wolverton C (2013) Materials design and discovery with high-throughput density functional theory: the open quantum materials database (OQMD). JOM 65:1501

    Article  Google Scholar 

  • Scalise E, Srivastava V, Janke E, Talapin DV, Galli G, Wippermann S (2018) Surface chemistry and buried interfaces in all-inorganic nanocrystalline solids. Nat Nanotechnol 13:841–848

    Article  ADS  Google Scholar 

  • Soler JM, Artacho E, Gale JD, García A, Junquera J, Ordejón P, Sánchez-Portal D (2002) The SIESTA method for ab initio order-N materials simulation. J Phys Condens Matter 14:2745

    Article  ADS  Google Scholar 

  • Talapin DV (2012) Nanocrystal solids: a modular approach to materials design. MRS Bull 37:63–71

    Article  Google Scholar 

  • Talapin DV, Lee J-S, Kovalenko MV, Shevchenko EV (2010) Prospects of colloidal nanocrystals for electronic and optoelectronic applications. Chem Rev 110:389–458

    Article  Google Scholar 

  • Thygesen KS, Jacobsen KW (2016) Making the most of materials computations. Science 354:180. http://science.sciencemag.org/content/354/6309/180

    Article  ADS  Google Scholar 

  • Walter MG, Warren EL, McKone JR, Boettcher SW, Mi Q, Santori EA, Lewis NS (2010) Solar water splitting cells. Chem Rev 110:6446–6473

    Article  Google Scholar 

  • Wippermann S, Vörös M, Rocca D, Gali A, Zimanyi G, Galli G (2013) High-pressure core structures of Si nanoparticles for solar energy conversion. Phys Rev Lett 110:046804

    Article  ADS  Google Scholar 

  • Wippermann S, Vörös M, Gali A, Gygi F, Zimanyi G, Galli G (2014) Solar nanocomposites with complementary charge extraction pathways for electrons and holes: Si embedded in ZnS. Phys Rev Lett 112:106801

    Article  ADS  Google Scholar 

  • Wippermann S, He Y, Vörös M, Galli G (2016) Novel silicon phases and nanostructures for solar energy conversion. Appl Phys Rev 3:040807

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by DOE-BES under the MICCoM grant.

Author information

Authors and Affiliations

  1. Department of Chemistry, Institute for Molecular Engineering, The University of Chicago, Chicago, IL, USA

    Giulia Galli

Authors
  1. Giulia Galli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Giulia Galli .

Editor information

Editors and Affiliations

  1. Institute of Physics, Swiss Federal Institute of Technology – Lausanne, Lausanne, Switzerland

    Wanda Andreoni

  2. Department of Nuclear Science and Engineering, Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Sidney Yip

Section Editor information

  1. Institute of Physics, Swiss Federal Institute of Technology - Lausanne, Lausanne, Switzerland

    Wanda Andreoni

  2. Department of Nuclear Science & Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Sidney Yip

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Galli, G. (2020). The Long and Winding Road: Predicting Materials Properties Through Theory and Computation. In: Andreoni, W., Yip, S. (eds) Handbook of Materials Modeling. Springer, Cham. https://doi.org/10.1007/978-3-319-44677-6_42

Download citation

Publish with us

Policies and ethics

Search

Navigation