AI for Sustainable Material Selection
AI for selecting sustainable and low-carbon building materials.
Definition
AI for material selection helps choose sustainable building materials. AI can compare material environmental impacts, identify sustainable alternatives, and ensure specification compliance. This improves sustainable material decisions.
In Depth
Sustainable material selection evaluates products against environmental criteria — embodied carbon, recycled content, regional sourcing, VOC emissions, and Red List chemical avoidance — alongside the performance requirements. AI filters available products against all of these criteria simultaneously, identifying products that meet both the sustainability and performance requirements.
The multi-criteria evaluation is what makes AI valuable for material selection. A specifier looking for a low-carbon concrete alternative needs a product that meets the structural specification (strength, durability, air content), the sustainability requirement (reduced embodied carbon), and the constructability requirement (workability, set time, availability). AI evaluates available products against all requirements and presents compliant options.
Examples
Comparing material impacts
Finding sustainable alternatives
Selecting low-carbon options
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Frequently Asked Questions
AI for material selection helps choose sustainable building materials. AI can compare material environmental impacts, identify sustainable alternatives, and ensure specification compliance. This improves sustainable material decisions.
Comparing material impacts. Finding sustainable alternatives. Selecting low-carbon options.
Project Research: Instantly access all project-critical information from a single search interface.