Automation

Accelerated discovery, high throughput experimentation, and fully autonomous laboratories are central to the future of materials engineering. However, dedicated systems are often just that, purpose built for specific applications and difficult to modify for new projects or niche applications. Our group pursues hybrid automation systems which allow us to accelerate our core research, improve reproducibility, and  enable new research avenues. We explore and encourage our team to leverage the incredible expertise and resources at uOttawa which helps us design our instrumentation and data management resources from the ground up. Our team is committed to applying FAIR principles to our data and to designing research experiments that leverage open software and hardware platforms wherever possible.

The Automation Assembly

  • Sophia McKillop

    Automated testing of MIM capacitors for high throughput characterization

  • Nicholas Dallaire

    Data processing and Bayesian optimization for accelerating OTFT research

  • Dr. Joseph Manion

    Design and implementation of data management strategies for research

Highlights

  • Automation in Action

    In Adv. Mater. Nic² et al discuss how over the last eight years the LRG has implemented hybrid automation to accelerate our research through the development of autotesters

  • Fastidious and Precise

    In ACS Appl. Nano. Mater. May and co show off the difference a steady hand can make. Our automated drop-dispensing system yields better and more consistent OTFTs

  • Photo credit: Nicholas Dallaire

    In the Field

    Our autotester setups are designed to go (almost) anywhere. Nic took the idea of field work pretty literally and ended up showing our OTFTs to an unconventional audience

  • Searching the Stacks

    It’s been 10 years since the LRG kicked off. That’s a lot of data! We’re looking back at the highlights and looking forward to the future of data and data management in the LRG