Purdue University, along with IBM Research and international partners from the Commonwealth Scientific and Industrial Research Organisation (CSIRO, Australia) will utilize remote sensing platforms to collect data and develop models for automated phenotyping and predictive plant growth. The team will create a system that combines data streams from ground and airborne mobile platforms for high-throughput automated field phenotyping. The team's custom "phenomobile" will be a mobile, ground-based platform that will carry a sensor package capable of measuring numerous plant traits in a large number of research plots in a single day. In addition, the team will use unmanned aerial vehicles (UAVs) equipped with advanced sensors configured to optimize the collection of diverse phenotypic data and complement the data collected from the phenomobile. Advanced image and signal processing methods will be utilized to extract phenotypic information and develop predictive models for plant growth and development. IBM Research will contribute high-performance computing platforms and advanced machine learning approaches to associate these measurements with genomic information to identify genes controlling sorghum performance. International partners from CSIRO will lend their expertise in crop modelling and phenotyping to the effort.

Purdue University will develop an integrated, connected vehicle control system for diesel-powered Class 8 trucks. Improvements from this system are expected to achieve 20% fuel consumption reduction relative to a 2016 baseline Peterbilt Class 8 truck. Class 8 trucks are large (over 33,000 lbs) vehicles such as trucks and tractor-trailer combinations like 18-wheelers. While these large trucks represent only 4% of all on-road vehicles in the U.S., they are responsible for almost 22% of global on-road fuel consumption. The Purdue team's work is based on a system-of-systems approach that integrates hardware and software components of the powertrain, vehicle dynamic control systems, and vehicle-to-everything (V2X) communication, supported by cloud computing. Communication between vehicles relies on short range radio, while cloud communications will operate over the LTE cellular network. This approach will provide the data needed to optimize single vehicle or two vehicles closely following each other in a platooning formation - reducing the platoon's overall energy consumption using technologies such as predictive cruise control and coordinated gear shifting. The proposed technology can also be applied to lighter class of trucks as the same performance shortcomings for Class 8 truck engines and transmissions also exist in lighter vehicle classes.

Purdue University will develop a new class of small-scale sensing systems that use mass and electrochemical sensors to detect the presence of CO₂. CO₂ concentration is a data point that can help enable the use of variable speed ventilation fans in commercial buildings, thus saving a significant amount of energy. There is also a pressing need for enhanced CO₂ sensing to improve the comfort and productivity of people in commercial buildings, including academic spaces. The research team will develop a sensing system that leverages on-chip integrated organic field effect transistors (FET) and resonant mass sensors. Field effect transistors are chemical sensors that can transform chemical energy into electrical energy. The unique design allows the system to measure two distinct quantities as it absorbs CO₂ from the environment - electrical impedance using the FET and added mass using the resonant mass sensors. The design will use low-cost circuit boards and off-the-shelf devices like commercial solar panels and batteries to reduce the cost of the system and enable easy deployment. By combining two unique sensing technologies into a single package, the team hopes to implement a solution for monitoring CO₂ levels that could yield a nearly 30% reduction in building energy use.

The University of Notre Dame is developing a new CO₂ capture process that uses special ionic liquids (ILs) to remove CO₂ from the gas exhaust of coal-fired power plants. ILs are salts that are normally liquid at room temperature, but Notre Dame has discovered a new class of ILs that are solid at room temperature and change to liquid when they bind to CO₂. Upon heating, the CO₂ is released for storage, and the ILs re-solidify and donate some of the heat generated in the process to facilitate further CO₂ release. These new ILs can reduce the energy required to capture CO₂ from the exhaust stream of a coal-fired power plant when compared to state-of-the-art technology.