Project Grant 2450862
- This $275,008 Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to create an AI-powered framework that helps designers automatically evaluate the environmental impact of their designs and optimize them for sustainability. The key innovations include: Developing novel graph attention network (GAT) algorithms to extract lifecycle inventory (LCI) data by analyzing similarities with existing designs, addressing the issue of LCI data scarcity....
- This National Science Foundation (NSF) Project Grant, awarded under the Engineering (CFDA 47.041) program, aims to create an AI-powered framework to help designers evaluate and optimize the environmental impact of their product designs. The $274,959 award to Florida International University will implement several key innovations: (1) Develop novel graph attention network algorithms to extract lifecycle inventory data for sustainability analysis by leveraging similarities with existing product...
- This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $450,000 to the University of Notre Dame to develop a machine learning-enabled screening tool for estimating the environmental impacts of building materials. The research aims to create a low-cost, user-friendly method that enables small and medium-sized manufacturers to evaluate and improve their production practices without relying on expensive consultants or specialized software. The...
- This National Science Foundation (NSF) Engineering program (CFDA 47.041) award of $587,250 to The Pennsylvania State University, doing business as Penn State, will support research to create and evaluate new methods for incorporating decision support through artificial intelligence during early building design. The project aims to develop flexible machine learning models that can predict key building performance metrics, enable interactive human-computer collaboration on design exploration,...
- This Project Grant award of $422,153 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) is funding a collaborative research project to use artificial intelligence (AI) to design new sustainable polymeric materials that can be easily recycled. The researchers at the University of California, Berkeley will create depolymerizable plastics from simple feedstocks and develop physics-informed AI models to guide the design of these plastics to meet a...
- This Project Grant award from the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) will support collaborative research at Drexel University to evaluate and predict the relationship between sustainable urban design initiatives and gentrification processes in the city of Philadelphia. The $225,000 award, effective from July 15, 2023 to June 30, 2026, will fund the development of artificial intelligence computer vision methods and machine learning models to identify...
- This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award of $294,457 to The Leland Stanford Junior University (Stanford University) explores the feasibility of using generative artificial intelligence (AI) language models to automate the creation of building energy models. The key objectives are to: 1) test the feasibility of applying generative AI to various steps of the building energy modeling process, and 2) quantify the performance and time trade-offs...
- This $274,192 Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports the development of an advanced generative AI toolbox for interactive Life Cycle Assessments (LCA). The primary aim is to create a domain-specific large language model that can process complex, multi-modal data to provide real-time insights into Scope 3 emissions, which are often the most significant part of a company's carbon...
- This $500,000 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to advance national prosperity and workforce development through research that enables more efficient and cost-effective design of mechanical systems. Specifically, the research seeks to develop a theoretical foundation called "mechanics informatics" that can learn material properties from a single optimized test, instead of many, using advanced information...
- This $299,999 project grant from the National Science Foundation's Office of International Science and Engineering, under the International Research and Education program (CFDA 47.079), will fund the development of novel synthetic living materials to improve the construction, performance, and maintenance of buildings. Specifically, the International Partnership for Responsive Infrastructure Using Sustainable Multifunctional Materials project will leverage advances in bioinspired materials...
This $449,984 Project Grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) will fund research at Drexel University to develop a data-driven framework that integrates generative AI, life cycle assessment, and circular economy principles. The goal is to optimize material selection and waste reduction in the built environment. Key innovations include an AI-driven system that generates technical specifications for materials and assemblies based on early-stage design parameters, and the creation of a circular building solutions database as an open-access resource for sustainable building practices. The research aims to help mitigate unnecessary waste, resource depletion, and environmental impacts in the construction industry by providing practical, science-based tools to guide early design decisions. The project will run from October 1, 2025 to September 30, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $450.0k | 7/24/25 |