skip to content

Winton Programme for the Physics of Sustainability

Department of Physics
 
Lithiation of silicon via lithium Zintl-defect complexes from first principles

Modeling provides insight into stable form of Li defects in Si which may play a significant role in Li-ion batteries

A new type of crystalline impurity called a Zintl defect has been predicted by Dr Andrew Morris, Winton Advanced Research Fellow and co-workers at the University of Cambridge and University College London. One such example, called the {4Li,V} complex in silicon is presented in Physical Review B where they show it is important for understanding how lithium-ion batteries charge and available open-access.

Silicon is the cutting edge anode material for Li-ion rechargeable batteries and insight may be gained into how it is charged by studying the lithium defects that from within it. The {4Li,V} complex is very stable in both crystalline and disordered silicon, indicating that it may aid the amorphisation of crystalline silicon and easily form upon delithiation of the silicon anode.

The {4Li,V} Zintl defect (pictured) consists of four lithium atoms (pink) electrostatically confined within a silicon vacancy (the silicon atoms are in yellow), which is similar to the bonding of metal ions in the so-called Zintl phase compounds. It is unusual since the lithium atoms are neither covalently bonded, not pairwise-ionically bonded to the silicon atoms. They predict that it is also stable in germanium.

Modeling battery materials at the atomic level is important since only when we understand their properties at the nanoscale can their full potential be unleashed. An extensive search for low-energy lithium defects in crystalline silicon using density-functional-theory methods and the ab initio random structure searching (AIRSS) method found that the four-lithium-atom substitutional point defect is exceptionally stable compared to other lithium atom impurities in silicon.

Latest news

Manipulation of Quantum Entangled Triplet Pairs

7 January 2021

Researchers have uncovered a new technique to create and manipulate pairs of particle-like excitations in organic semiconductors that carry non-classical spin information across space, much like the entangled photon pairs in the famous Einstein-Podolsky-Roden “paradox”.

Machine learning algorithm helps in the search for new drugs

20 March 2019

Researchers have designed a machine learning algorithm for drug discovery which has been shown to be twice as efficient as the industry standard.