All Outputs (2)

Machine Learning for Ultra High Throughput Screening of Organic Solar Cells: Solving the Needle in the Haystack Problem (2023)
Journal Article
Hußner, M., Pacalaj, R. A., Olaf Müller‐Dieckert, G., Liu, C., Zhou, Z., Majeed, N., …MacKenzie, R. C. I. (2024). Machine Learning for Ultra High Throughput Screening of Organic Solar Cells: Solving the Needle in the Haystack Problem. Advanced Energy Materials, 14(3), Article 2303000. https://doi.org/10.1002/aenm.202303000

Over the last two decades the organic solar cell community has synthesized tens of thousands of novel polymers and small molecules in the search for an optimum light harvesting material. These materials are often crudely evaluated simply by measuring... Read More about Machine Learning for Ultra High Throughput Screening of Organic Solar Cells: Solving the Needle in the Haystack Problem.

On Spread Spectrum for DC Grids: Low-Frequency Conducted EMI Mitigation and Signal Integrity Disruption in Serial Communication Links (2023)
Journal Article
Pena-Quintal, A., Sayed, W. E., Sumner, M., Ercan, S. U., Greedy, S., Thomas, D., & Smolenski, R. (2023). On Spread Spectrum for DC Grids: Low-Frequency Conducted EMI Mitigation and Signal Integrity Disruption in Serial Communication Links. IEEE Transactions on Electromagnetic Compatibility, 65(4), 1027-1036. https://doi.org/10.1109/TEMC.2023.3273111

This article addresses the effects on nearby communication systems when spread spectrum modulation techniques are used for a dc-dc power converter. These interactions can be found in modern smart grids and automotive power networks in which the combi... Read More about On Spread Spectrum for DC Grids: Low-Frequency Conducted EMI Mitigation and Signal Integrity Disruption in Serial Communication Links.