Dye adsorption on metal-oxide films often results in small to substantial absorption shifts relative to the solution phase, with undesirable consequences for the performance of dye-sensitized solar cells and optical sensors. While density functional theory is frequently used to model such behaviour, it is too time-consuming for rapid assessment. In this paper, we explore the use of supervised machine learning to predict whether dye adsorption on titania is likely to induce a change in its absorption characteristics. The physicochemical features of each dye were encoded as a numeric vector whose elements are the counts of molecular fragments and topological indices. Various classification models were subsequently trained to predict the type of absorption shift i.e. blue, red or unchanged (|Δλ| ≤ 10 nm). The models were able to predict the nature of the shift with a good likelihood (~80%) of success when applied to unseen data.

Direct C-H arylation coupling is potentially a more economical and sustainable process than conventional cross-coupling. However, this method has found limited application in the synthesis of organic dyes for dye-sensitized solar cells. Although direct C-H arylation is not an universal solution to any cross-coupling reactions, it efficiently complements conventional sp2−sp2 bond formation and can provide shorter and more efficient routes to diketopyrrolopyrrole dyes. Here, we have applied palladium catalyzed direct C-H arylation in the synthesis of five new 3,6-dithienyl diketopyrrolopyrrole dyes. All prepared sensitizers display broad absorption from 350 nm up to 800 nm with high molar extinction coefficients. The dye-sensitized solar cells based on these dyes exhibit a power conversion efficiency in the range of 2.9 to 3.4%.

First and foremost I praise God for the strength upon all who assisted me. I praise Him for giving me life, health, and courage to press on challenges and shortcomings I experienced along the journey of my Ph.D. research.I would like to express my heartfelt sincere gratitude to my supervisors, Prof.Wang Mingfeng and Prof. NG Siu Choon (for the first part of my Ph.D. projects), for their invaluable and enthusiastic guidance, inspirational insights and helpful thoughts throughout all my Ph.D. research projects. They have encouraged and motivated me during my four years research work and I have learned a great deal of scientific knowledge from them all. I would like to acknowledge all my lab mates both past and present especially