Advancing sustainable 3D printing using low-carbon concrete by facilitating machine learning
Fast facts
Funding source and project type:
Hamburg University of Technology: I3 Program – Junior Project

Principal investigators:
Jasper Vollmert, Roya Zeidler

Project duration:
2026 - 2027

Project budget:
€ 10.000,00
Motivation and research problem

The cement industry is one of the largest contributors to global CO₂ emissions, creating an urgent demand for alternative binders with significantly lower clinker content and improved environmental performance. Activated clay-based materials offer strong potential because of wide availability, local sourcing potential, and dual functionality as supplementary cementitious materials and reactive constituents in novel binder systems. Extrusion-based 3D concrete printing also presents major opportunities for material-efficient, safer, and digitally controlled construction. Yet both fields remain insufficiently connected. The applicability of low-carbon binders, including LC³- and geopolymer-based systems, to extrusion-based 3D concrete printing remains largely unresolved. Key challenges include rheological control, extrusion performance, buildability, interaction with printing hardware, fresh- and hardened-state mechanical properties, and long-term durability. Current knowledge gaps restrict practical implementation of low-carbon concrete in additive manufacturing.

Research objectives and expected results

The project aims to develop and validate a low-carbon, activated clay-based material system for extrusion-based 3D printing through an integrated approach combining materials science, digital fabrication, and data-driven modeling. Suitable activated clays will first be selected and comprehensively characterized. On that basis, printable mortar formulations will be designed, and extrusion equipment will be adapted to abrasive clay-based mixtures. Material composition and process parameters will then be iteratively optimized to achieve reliable printability, dimensional stability, and adequate mechanical performance. In parallel, experimental data will be generated to establish and compare predictive machine-learning models for fresh- and hardened-state material behavior, enabling more rapid adaptation to different extrusion systems. Expected project outcomes include a printable activated clay-based material, a modified extrusion setup, an initial predictive modeling framework for 3D-printing applications, and a full-scale demonstration structure accompanied by long-term monitoring under realistic environmental conditions (Figure 1). Collectively, the project outcomes are intended to support industrial adoption and to reduce the environmental impact of concrete-based construction.

Figure 1: Projects and interactions within DFG Research Unit 5672.
Figure 1: AI-generated representation of a potential full-scale demonstration structure made of low-carbon 3D-printed concrete, equipped with integrated monitoring systems for long-term performance assessment under real environmental conditions.

Contact

Jasper Vollmert, M.Sc.
Hamburg University of Technology
Institute of Digital and Autonomous Construction
Blohmstraße 15
21079 Hamburg
Germany
Email: jasper.vollmert(at)tuhh(dot)de