TY - JOUR
T1 - Imperfections are not 0 K
T2 - free energy of point defects in crystals
AU - Mosquera-Lois, Irea
AU - Kavanagh, Seán R.
AU - Klarbring, Johan
AU - Tolborg, Kasper
AU - Walsh, Aron
N1 - Publisher Copyright:
© 2023 The Royal Society of Chemistry.
PY - 2023/8/11
Y1 - 2023/8/11
N2 - Defects determine many important properties and applications of materials, ranging from doping in semiconductors, to conductivity in mixed ionic-electronic conductors used in batteries, to active sites in catalysts. The theoretical description of defect formation in crystals has evolved substantially over the past century. Advances in supercomputing hardware, and the integration of new computational techniques such as machine learning, provide an opportunity to model longer length and time-scales than previously possible. In this Tutorial Review, we cover the description of free energies for defect formation at finite temperatures, including configurational (structural, electronic, spin) and vibrational terms. We discuss challenges in accounting for metastable defect configurations, progress such as machine learning force fields and thermodynamic integration to directly access entropic contributions, and bottlenecks in going beyond the dilute limit of defect formation. Such developments are necessary to support a new era of accurate defect predictions in computational materials chemistry.
AB - Defects determine many important properties and applications of materials, ranging from doping in semiconductors, to conductivity in mixed ionic-electronic conductors used in batteries, to active sites in catalysts. The theoretical description of defect formation in crystals has evolved substantially over the past century. Advances in supercomputing hardware, and the integration of new computational techniques such as machine learning, provide an opportunity to model longer length and time-scales than previously possible. In this Tutorial Review, we cover the description of free energies for defect formation at finite temperatures, including configurational (structural, electronic, spin) and vibrational terms. We discuss challenges in accounting for metastable defect configurations, progress such as machine learning force fields and thermodynamic integration to directly access entropic contributions, and bottlenecks in going beyond the dilute limit of defect formation. Such developments are necessary to support a new era of accurate defect predictions in computational materials chemistry.
UR - http://www.scopus.com/inward/record.url?scp=85168817664&partnerID=8YFLogxK
U2 - 10.1039/d3cs00432e
DO - 10.1039/d3cs00432e
M3 - Review article
C2 - 37565783
AN - SCOPUS:85168817664
SN - 0306-0012
VL - 52
SP - 5812
EP - 5826
JO - Chemical Society Reviews
JF - Chemical Society Reviews
IS - 17
ER -