NGSE8 is coming!
NGSE is a global conference on solar energy organized by FAU and HI ERN, held annually in December, and a bi-monthly PhD-Postdoc series. NGSE 8, in collaboration with LBNL, takes place on December 12-14, 2023, in Erlangen, featuring a hybrid format. The focus is on “High-throughput Synthesis and AI for Energy Materials,” with a workshop on the Emerging PV database project on the final day. The conference will be freely accessible via Zoom Webinar for registered online participants! You can register here
Tuesday, December 12th
| Time Berkeley | Time Erlangen | Speaker |
| 7:00 – 7:30 | 16:00 – 16:30 | Marcus Noack (LBNL): Mathematical Nuances of Gaussian-Process-Driven Autonomous Experimentation |
| 7:30 – 8:00 | 16:30 – 17:00 | Sergei Kalinin (University of Tennessee): Autonomous probe microscopy of combinatorial libraries: physics discovery and materials optimization |
| 8:00 – 8:30 | 17:00 – 17:30 | Pascal Friederich (KIT): Machine learning to simulate, understand, and design molecules and materials |
| 8:30 – 9:00 | 17:30 – 18:00 | Jianchang Wu (HI ERN): Predicting hole transport materials for perovskite solar cells assisted by machine learning. |
| 9:00 – 9:30 | 18:00 – 18:30 | break |
| 9:30 – 10:00 | 18:30 – 19:00 | Alessandro Troisi (University of Liverpool): Digital Materials Discovery in Organic Electronics |
| 10:00 – 10:30 | 19:00 – 19:30 | Felipe Oviedo (Microsoft): DeepDeg: Forecasting and explaining degradation in novel photovoltaics |
| 10:30 – 11:00 | 19:30 – 20:00 | Mariano Campoy Quiles (ICMAB): Using high throughput screening to match materials and photovoltaic applications |
| 11:00 – 11:30 | 20:00 – 20:30 | Benjamin Sanchez Lengeling (Google): Learning Representations of Data: An introduction to the Deep Learning Toolkit for Sciences and Engineering |
Wednesday, December 13th
| Time Berkeley | Time Erlangen | Speaker |
| 7:00 – 7:30 | 16:00 – 16:30 | Thomas Kirchartz (FZ Jülich): Transforming characterization data into information in emerging solar cells |
| 7:30 – 8:00 | 16:30 – 17:00 | Marina Leite (UC Davis): A Machine Learning Framework to Predict Halide Perovskite’s Dynamic Behavior |
| 8:00 – 8:30 | 17:00 – 17:30 | Aron Walsh (Imperial College): Hunt for the next halide perovskite |
| 8:30 – 9:00 | 17:30 – 18:00 | Larry Lüer (FAU): Towards a digital twin for PV materials |
| 9:00 – 9:30 | 18:00 – 18:30 | break |
| 9:30 – 10:00 | 18:30 – 19:00 | Mashid Ahmadi (University of Tennessee): Automated High Throughput Synthesis and Characterization of Metal Halide Perovskites: Exploration and Exploitation |
| 10:00 – 10:30 | 19:00 – 19:30 | David Fenning (UC San Diego): Perovskites with Precision: the Perovskite Automated Solar Cell Assembly Line (PASCAL) |
| 10:30 – 11:00 | 19:30 – 20:00 | Helge Stein (KIT): Catalyzing research acceleration through the engineering of science |
| 11:00 – 11:30 | 20:00 – 20:30 | Ivano Castelli (DTU): Autonomous workflows for an accelerated discovery of energy materials |
Thursday, December 14th
| Time Erlangen | Speaker |
| 13:45 – 14:00 | Osbel Almora (Universitat Rovira i Virgili): Emerging PV report 2023 |
| 14:00 – 14:30 | René Janssen (TU Eindhoven): Multijunction Perovskite Solar Cells: Materials, Devices, and Characterization |
| 14:30 – 15:00 | Kenjiro Fukuda (RIKEN): Very Thin and Lightweight Flexible Organic Solar Cells: Performance and Potential Applications |
| 15:00 – 15:30 | Vincent M. Le Corre (FAU / HI ERN): Machine learning and device modeling as an automated diagnostic tool for high-throughput research |
| 15:30 – 16:00 | break |
| 16:00 – 16:30 | Maria A. Loi (University of Groningen): SnO2 for High-Performance and Stable Organic Solar Cells |
| 16:30 – 17:00 | Barry P. Rand (Princeton): Unforeseen ink chemistry: Solutions for perovskite solar cells |
| 17:00 – 17:30 | Maria Ronda-Lloret (Wiley): AI Tools in Scientific Writing and Publishing |
| 17:30 – 17:40 | Christoph J. Brabec (HI-ERN / FAU): Concluding remarks |