The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Electro-chemo-mechanics of the interfaces in 2d-3d heterostructure electrodes
Author:	Sharma, Vidushi
View Online:	njit-etd2021-074 (xxiii, 166 pages ~ 23.5 MB pdf)
Department:	Department of Mechanical and Industrial Engineering
Degree:	Doctor of Philosophy
Program:	Mechanical Engineering
Document Type:	Dissertation
Advisory Committee:	Datta, Dibakar (Committee chair) Chester, Shawn Alexander (Committee member) Lee, Eon Soo (Committee member) Dong, Lin (Committee member) Ahmadpoor, Fatemeh (Committee member) Dias, Cristiano L. (Committee member) Young, Joshua (Committee member)
Date:	2021-12
Keywords:	Deep learning Density functional theory Electrodes Graphene Interface Selenium
Availability:	Unrestricted
Abstract:	Unique heterostructure electrodes comprising two-dimensional (2D) materials and bulk three dimensional (3D) high-performance active electrodes are recently synthesized and experimentally tested for their electrochemical performance in metal-ion batteries. Such electrodes exhibit long cycle life while they also retain high-capacity inherent to the active electrode. The role of 2D material is to provide a supportive mesh that allows buffer space for volume expansions upon ion intercalation in the active material and establishes a continuous electronic contact. Therefore, the binding strength between both materials is crucial for the success of such electrodes. Furthermore, battery cycles may bring about phase transformations in the active electrodes. Thus, altering the characteristics of its existing interface with the 2D material. Conversely, surface characteristics of 2D material can also initiate new microstructural orders in the bulk electrodes. The resultant structural variations impact the overall functionality of the electrode. Obtaining an insight into the nature of these interfaces has become a necessity to design heterostructure electrodes for commercial applications. However, it is not practiced to date due to limitations imposed by experimental techniques. The purpose of this research is to computationally investigate the interface between 2D materials with 3D bulk systems and highlight the implications of these interfacial attributes on electrode performance. The precise aims are: (i) determine interface strength between 2D materials and 3D active electrode in the light of phase transitions and surface modifications; (ii) differentiate the electrochemical performance of heterostructure electrodes from their free counterparts; and (iii) develop new deep learning-based algorithm to model multiphasic interface systems. Key results of this research are quantitative interface strength values of selenium(Se) and silicon(Si) with 2D materials such as Graphene and MXene. First principle calculations show that bulk materials Se and Si bind with 2D materials with low interface strength, mostly below 0.6 J/m2. The presence of out-of-plane surface functional groups on MXenes can further create stearic effects and low interface stability, resulting in curtailed interface strength. The vdW forces are the primary mode of binding at the interface of 2D materials. Next, a relation between the state of charge and interface structure of the Se-Graphene heterostructure electrode is presented for the potassium ion batteries. More atomic investigations into the 2D-3D interfaces reveal that the interface alone is a cause of crystalline distortions and new phase transitions in the bulk materials. These interfacial disorders cannot be accurately traced by empirical potentials. To overcome this gap, deep learning-based potential energy surfaces (PES) are developed from density functional theory(DFT) data of multiphasic tin(Sn)-Graphene interfaces. Developed PES predict the energies of new interfaces with close to first principles accuracy.