Research & Projects
My research addresses the decarbonisation of construction materials across the full innovation pathway: from material synthesis and experimental characterisation to data-driven design and technology scale-up.
Over the past decade, I have investigated how industrial wastes, alternative binders and carbon-utilisation processes can enable lower-carbon construction. This experimental foundation now informs my work in materials intelligence, where artificial intelligence and domain-informed digital tools are used to accelerate materials discovery, optimisation and translation.
A Multiscale Research Framework
Low-Carbon Cements and Process Technologies
Engineering reactivity from raw material to industrial processes
“I investigate how mineral resources, industrial by-products and waste streams can be transformed into high-value, low-carbon construction materials. Rather than treating these resources as simple cement replacements, my research examines their intrinsic chemistry, mineralogy, surface properties and reactivity, and then engineers these characteristics through chemical, mechanochemical, and thermal processing.”
Linked projects: TFI N+ Project · IDRIC WAVE2 MIP8.7 · HRI ICP R4 (with Heidelberg Materials)
Functional Cementitious Materials
Designing cementitious materials to do more than carry load
“I investigate how cementitious materials can be engineered to deliver energy storage, electrical conductivity and other functions alongside structural performance. Rather than relying on the simple addition of functional ingredients, my research establishes how chemistry, phase assemblage and multiscale structure govern thermochemical and charge-transport behaviour, providing a scientific basis for designing reliable multifunctional materials for next-generation infrastructure.”
Linked projects: GeoBattery· Read the research
Intelligent Design of Sustainable Materials
From empirical formulation to domain-informed materials intelligence
“I develop data-driven frameworks that move sustainable materials research beyond trial-and-error formulation. By integrating materials data, physicochemical knowledge and machine learning, my work identifies composition–process–structure–performance relationships and enables inverse design: beginning with required performance and working backwards towards promising materials and processing conditions.”
Linked projects: Digital AAM v0.1
Research Collaborates
I welcome collaborations with researchers and industry partners working across materials intelligence, low-carbon construction and industrial decarbonisation. To explore opportunities to work together, please get in touch.
Xinyuan Ke 