SLU Highlights Biochar Geopolymer Hollow Block Research At Concrete Engineering Conference In Kuala Lumpur

Concrete hollow blocks stay at the center of masonry construction across Southeast Asia, and new research presented in Kuala Lumpur points to where the material conversation is heading next, lower carbon mixes, performance testing, and smarter design tools.

Saint Louis University in Baguio, Philippines through its civil engineering department under the School of Engineering and Architecture, joined the 17th International Conference on Concrete Engineering and Technology, known as CONCET 2026, held Aug. 17-21 at Universiti Malaya in Kuala Lumpur, Malaysia. The event’s theme focused on sustainability, structural integrity, and artificial intelligence for smarter built environments.

One SLU paper drilled straight into a topic that matters to block production and jobsite performance. Engineer Emerson O. Gapuz presented “Mechanical Strength Performance and Carbon Absorption of Biochar Modified Geopolymer Hollow Blocks,” based on undergraduate research. The team studied rice husk biochar used in both conventional concrete hollow blocks and geopolymer concrete hollow blocks, with attention on mechanical strength performance and carbon dioxide absorption.

For mason contractors and masonry crews, the takeaway is practical. When alternative block mixes show up in specs or value engineering discussions, treat them like any other critical unit submittal. Ask for verified strength data, absorption-related information tied to the research focus, and clear documentation on what the unit is, conventional concrete or geopolymer, plus any required project testing. Keep mockups and installation details aligned with the unit’s documented properties, especially when wall performance and durability are on the line.

SLU also contributed to a second paper that earned CONCET 2026’s Best Paper Award under the Structural Analysis, Design and Engineering theme. Coauthored by Gapuz and presented by Jan Nicholas Baldo, the research used surrogate modeling and MATLAB-based artificial neural networks to predict IDA drift ratio in low-rise reinforced concrete structures in La Trinidad, Benguet, Philippines.

Conference outputs are slated for publication in the IOP Conference Series: Earth and Environmental Science, extending the reach of the work beyond the event.

Read the full, original article from slu.edu.ph here.

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