e-ASIA Joint Research Programme 2024

Together with our international partners from Thailand and Japan, we will develop a biomass electrolyser to simultaneously produce hydrogen gas and valuable chemicals from biologic materials that would otherwise end up in a landfill. This biomass electrolyser will be powered by renewable energy, thereby generating environmentally friendly hydrogen and green chemicals.

To achieve this, New Zealand investigators Holger Fiedler (GNS Science), John Kennedy (GNS Science) and Suren Wijeyekoon (SCION) will develop an abundant, cheap, effective hydrogen evolution reaction catalyst using New Zealand forestry biomass, such as lignin and cellulose. The strong international coupling with biomass electro-oxidation catalysts that will be investigated and optimised by our e-Asia partners enables the creation of a scalable, selective electrocatalytic process.

This project lays the foundation for replacing New Zealand imports of fossil-fuel-based, carbon emitting chemicals with zero-carbon substitutes that are electrocatalytic oxidised from New Zealand biomass waste by 2040. Furthermore, the simultaneous production of hydrogen gas will enhance our energy resilience in the future.

Our interdisciplinary team from Kyoto University, the MacDiarmid Institute, and Vidyasirimedhi Institute of Science and Technology proposes to build a platform to accelerate the development of organic solar cells by optimizing interface compositions.

The future of solar cell technology will be driven by discovering new materials and device structures that are suitable for printed solar cells. Their light weight and flexibility will enable widespread adoption and entirely new uses and benefits.

The multi-scale mechanism for sunlight-to-electricity conversion in Organic Solar Cells (OSCs) has been an obstacle to rationally designing improved materials and devices, and this problem is compounded by the vast number of relevant materials to experimentally screen. We know from drug design that using computational methods to screen vast numbers of materials in simulated devices, without actually synthesising them or fabricating prototypes, would expedite the discovery of effective OSC materials.

In this project, we aim to create the Interface Materials Informatics platform – the first computational platform to accelerate OSC development by optimizing interface compositions. We will harness the respective strengths of each team spanning interface structure simulation, machine learning, experimental and computational approaches to organic semiconductor physics, charge extracting interfaces, and OSC device optimisation. The platform will compute device properties from first principles and will identify optimal interface compositions using machine learning and evolutionary algorithms. Its reliability will be ensured by extensive benchmarking to experimental data. The ability to screen interface compositions will be a significant step towards a new materials informatics paradigm: virtual screening of entire solar cell devices.

The primary users of this first-of-a-kind computational platform will be researchers – both academic and industrial – who will be able to save the significant time and cost of experimentally searching for new materials and device structures within a vast parameter space. By generating large datasets describing OSC performance, this platform will also position us to meaningfully apply machine learning approaches for accelerated material design. More generally, this work aligns with efforts in Asia’s chemical industry to assimilate data science and computation as part of the Industry 4.0 revolution. Through our partnerships with prominent global materials databases, we aim to facilitate broad access to the computational platform and integrate it with other experimental and computational datasets.