CMU's Latest Energy Startups
Technologies developed at Carnegie Mellon University have the ability to enhance energy generation and the consumption of that energy in our buildings, transportation, industry and homes. Some of these technologies are just emerging from the university while others have already entered, or are on the cusp of entering, the marketplace. These next-generation technologies have been developed by undergraduate and graduate students, researchers, faculty and alumni from all across Carnegie Mellon.
Below is a list of our latest energy startups.
Energy Generation, Conversion, Storage and the Environment
SolePower creates kinetic chargers that capture wasted energy from human motion to power portable devices like phones, wearables, sensors and GPS. The company is partnering with the slip resistant footwear leader, SR Max/Saf-Gard, to develop self-charging smart work boots that increase safety and improve operations.
Key Researchers: CMU alumni Hahna Alexander and Matthew Stanton
Teratonix is a maintenance-free solution that converts ambient radio waves to generate electricity on a spot. The company is working on prototype demonstration, exploring possible applications to build a go-to-market end-to-end ioT solution for Walmart or Shell. They are forming a new C-Corp to continue the energy harvesting business under the new entity.
Key Researcher: Yi Luo
Watt-Learn is creating a profitable grid, one intelligent battery at a time. Watt-Learn is an artificial intelligence company that offers a revolutionary battery control software platform which autonomously optimizes battery operations for user-specified criteria. The company's software platform can maximize energy storage projects’ return on investment by optimizing revenue generation per unit battery degradation.
Key Researcher: Julian Lamy
Industry Device Manufacturing and Energy Efficiency
Anactisis develops methods to economically recover rare earth elements from water. For example, it can recover these elements from water used for hydraulic fracturing, geothermal energy and mine tailings settlement. These rare earth elements are needed for a wide range of electronic technologies, but the supply of materials is limited. Further, since most of the mines that hold these materials are in China, which sometimes has restricted access to these materials, it is important to have alternative ways of gathering them.
Key Researcher: Athanasios Karamalidis
BDC develops tools and methods for evaluating and controlling how mistuning affects the vibratory response of Integrally Bladed Disks (IBDs). BDC technologies identify and predict the effects of mistuning and vibration on these critical and expensive engine blades. BDC helps the U.S. military with this and helps commercial partners monitor the health of energy turbines. A woman-owned and operated business founded by the world’s expert on blade mistuning, Blade Diagnostics is working on completing the transition of its IBD inspection technologies for the U. S. Air Force.
Key Researcher: Jerry Griffin
This upcoming CMU spin-off is developing software that will enable dynamic, distributed, parallel management of load balancing in electric power distribution networks. Potential applications include management of microgrids; integration of intermittent power sources; communication/control for demand response programs at the utility and larger-user levels; and parallelization of computing in centrally-controlled utilities to increase the speed of decision-making, reduce vulnerabilities and reduce reserve capacity requirements.
Key Researchers: Gabriela Hug, Soummya Kar and Javad Mohammadi
Commercial Facility and Residential Energy Management
This upcoming CMU spin-off company is developing systems for data collection, analytics and visualization on energy usage to reveal actionable information for building occupants, managers and owners. Their approach to analyzing energy usage at the individual occupant level led to a 35 percent reduction in energy consumption in a pilot project with PNC Bank. Their system scales to enable a review of the energy savings opportunities over an entire portfolio of buildings, and to target investments toward projects with the best return on investment.
Key Researchers: Azizan Aziz and Bertrand Lasternas
Harnessing the powerful GIT and advanced data mining technology, BuildSimHub is an innovative big data management and cross-functional collaboration platform tailored for building energy modeling. They are creating a data-driven and agile development framework for the architecture industry. BuildSimHub's reporting solutions help those working in this industry make better-informed decisions and the platform automatically fills out any type of report in seconds. The company's 3-level quality assurance and auto-debugging solutions make energy modeling easier than ever.
Key Researcher: Weili Xu
LeanFM is a lifecycle software solution for economic, proactive and intelligent Facilities Management. The efficiency of facilities management (FM) is low due to the complexity of buildings and limited access to information. By leveraging Building Information Modeling (BIM) and cloud computing technology, LeanFM addresses this challenge by integrating the heterogeneous building information that is recorded in design drawings, equipment manuals, building automation systems and computerized maintenance management systems.
Key Researchers: Burcu Akinci and Xuesong Liu
Transit Energy Management
This CMU spin-off company is commercializing multiple applications of polymer-based protein engineering technology, based on the controlled radical polymerization. This technology allows the targeted and predicted modification of proteins with polymers, which results in protein-polymer conjugates that have magnitude higher efficacy, and are stable in environments hostile to unmodified proteins, such as low or high pH, high temperatures and organic solvents. Such technology is aimed to extend protein applications in such areas as pharmaceuticals, biocatalysis and energy.
Key researchers: Alan Russell and Kris Matyjaszewski
This award-winning CMU spin-off is an innovative approach to traffic signal control, combining research from artificial intelligence and traffic theory to optimize the performance of signals for the traffic that is actually on the road. As a result, this technology improves traffic flow for both urban grids and corridors, leading to less waiting, reduced congestion, shorter trips, less pollution and happier drivers. A Pittsburgh demonstration project on nine intersections reduced travel time by 26 percent. The demonstration project is now being expanded to 31 intersections.
Key Researchers: Stephen Smith and Greg Barlow