Topic Editors

Department of Chemistry, Biology, and Biotechnology, University of Perugia, 06123 Perugia, Italy
Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland
Department of Chemistry, Faculty of Science, University of Malta, MSD 2080 Msida, Malta
Department of Biological and Environmental Sciences and Technologies (DiSTeBA), Università del Salento, I-73100 Lecce, Italy

Recent Advances in Chemical Artificial Intelligence

Abstract submission deadline
closed (1 March 2025)
Manuscript submission deadline
1 October 2025
Viewed by
3178

Topic Information

Dear Colleagues,

Artificial Intelligence (AI) and robotics are becoming more prevalent in our societies. They assist, and sometimes even replace, humans in accomplishing specific tasks and dealing with complex systems. Traditionally, AI and robotics are developed in software and hardware, the latter being either rigid or soft. In the early 2010s, a new promising strategy was put forward as follows: to use molecular, supramolecular, and systems chemistry in wetware (i.e., in fluid solutions) to mimic some performances of human (and, more generally, biological) intelligence and develop the so-called Chemical Artificial Intelligence (CAI) and Chemical Robotics. In CAI, information is encoded, collected, stored, processed, and sent primarily through molecules and chemical reactions. CAI and Chemical Robots will allow humans to colonize the microscopic world. Microscopic artificial intelligent chemical systems will help in diagnosing and curing diseases, safeguarding the environment, and contributing to increased energy and food supplies. Finally, designing and implementing various forms of autonomous chemical intelligence will allow for a deeper comprehension of two remarkable emergent properties: intelligence and life.

This topic accepts research articles, reviews, and perspectives presenting the burgeoning field of CAI and Chemical Robotics, with the ambition of gathering brilliant ideas of the principal investigators in this new and forward-thinking research field and promoting the generation of a research network for further scientific collaborations.

Prof. Dr. Pier Luigi Gentili
Prof. Dr. Jerzy Górecki
Prof. Dr. David C Magri
Dr. Pasquale Stano
Topic Editors

Keywords

  • molecular chemistry
  • biomolecules
  • supramolecular chemistry
  • systems chemistry
  • smart colloids
  • synthetic cells
  • molecular logic gates
  • chemical communication
  • fuzziness of chemistry
  • oscillatory chemical reactions
  • origin of life

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Molecules
molecules
4.2 7.4 1996 15.1 Days CHF 2700 Submit
Biomimetics
biomimetics
3.4 3.5 2016 19.5 Days CHF 2200 Submit
Chemosensors
chemosensors
3.7 5.0 2013 20.1 Days CHF 2700 Submit
Life
life
3.2 4.3 2011 17.8 Days CHF 2600 Submit
AI
ai
3.1 7.2 2020 18.9 Days CHF 1600 Submit
Sci
sci
- 4.5 2019 37.1 Days CHF 1200 Submit

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Published Papers (1 paper)

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24 pages, 1503 KiB  
Article
The Effects of Omeprazole on the Neuron-like Spiking of the Electrical Potential of Proteinoid Microspheres
by Panagiotis Mougkogiannis and Andrew Adamatzky
Molecules 2024, 29(19), 4700; https://doi.org/10.3390/molecules29194700 - 4 Oct 2024
Cited by 1 | Viewed by 1279
Abstract
This study examines a new approach to hybrid neuromorphic devices by studying the impact of omeprazole–proteinoid complexes on Izhikevich neuron models. We investigate the influence of these metabolic structures on five specific patterns of neuronal firing: accommodation, chattering, triggered spiking, phasic spiking, and [...] Read more.
This study examines a new approach to hybrid neuromorphic devices by studying the impact of omeprazole–proteinoid complexes on Izhikevich neuron models. We investigate the influence of these metabolic structures on five specific patterns of neuronal firing: accommodation, chattering, triggered spiking, phasic spiking, and tonic spiking. By combining omeprazole, a proton pump inhibitor, with proteinoids, we create a unique substrate that interfaces with neuromorphic models. The Izhikevich neuron model is used because it is computationally efficient and can accurately simulate the various behaviours of cortical neurons. The results of our simulations show that omeprazole–proteinoid complexes have the ability to affect neuronal dynamics in different ways. This suggests that they could be used as adjustable components in bio-inspired computer systems. We noticed a notable alteration in the frequency of spikes, patterns of bursts, and rates of adaptation, especially in chattering and triggered spiking behaviours. The findings indicate that omeprazole–proteinoid complexes have the potential to serve as adaptable elements in neuromorphic systems, presenting novel opportunities for information processing and computation that have origins in neurobiological principles. This study makes a valuable contribution to the expanding field of biochemical neuromorphic devices and establishes a basis for the development of hybrid bio-synthetic computational systems. Full article
(This article belongs to the Topic Recent Advances in Chemical Artificial Intelligence)
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