The idea of neuromorphic engineering, i.e. to transfer learning and memory processes from biology to electronic circuits, is now more than 30 years old. However, this area is currently attracting unprecedented attention. The reason for this is a continuing change in almost all areas of life towards a digital society. Following the industrial revolution for about 200 years, this change is often called the digital revolution. The digital revolution increasingly relies on the use of machine learning algorithms which are realized on silicon technologies. However, the silicon technology is more and more restrictive for the digital revolution due to their high energy consumption. A solution to this problem requires extremely performance-efficient hardware that is tailored to the new requirements, i.e. suitable for unconventional computing strategies. This particularly requires a cooperation of scientists from various disciplines ranging from biology, physics, and material science to informatics and electronics.

In recent years, more and more scientists from a wide range of those disciplines have come together to form todays neuromorphic engineering knowledge base. However, the extreme thematic breadth of that field requires platforms that allow scientists to exchange ideas beyond the boundaries of their own communities. This was the idea at the beginning of this Guest Edited Collection. We wanted to build a platform to bring together the research work of different areas in the field of unconventional computing. Therefore, the Collection provides a platform for interdisciplinary research along three main lines: memristive materials and devices, emulation of cellular learning (neurons and synapses), and unconventional computing and network schemes.

 You can access the Collection here.

 I am happy to see the result and would like to thank all my colleagues who have contributed to this Guest Edited Collection. Big thanks goes to Robbie Roe and Bastien Conan (Projects Coordinator and Manager at Scientific Reports) who supported the project. The Collection is still open for submissions, so if you are interested in submitting a paper for consideration then please see the Call for Papers page for more details. It was and is a great collaboration and I am very happy that we can keep this platform open for further submissions. I hope all readers enjoy the Collection and look forward to more exciting articles on this platform.

Further to the post above, the interested reader is encouraged to read the other "Behind the Paper" posts from authors of the ‘Novel hardware and concepts for unconventional computing’ Collection:

• SLIM: Simultaneous Logic in Memory using Emerging Non-Volatile Memory Devices
• Analog Memristive Generative Adversarial Networks for Edge AI Computing
• An out-of-the-shelf ultra-compact leaky-integrate-and-fire artificial neuron
• Neuromorphic CMOS-MoS2 based hybrid system for low power edge-computing
• A 'no-brainer' paradigm of intelligence, or how to think without a brain