BiographyPier Luigi Gentili received his Ph.D. in Chemistry from the University of Perugia in 2004. His research and teaching activities are focused on Complex Systems. He is author of the book titled “Untangling Complex Systems: A Grand Challenge for Science” published by CRC Press in 2018. Being aware that inanimate matter is driven by force-fields, whereas the interactions between biological systems are also information-based, Gentili is lead by some questions like the following ones. “When does a chemical system become intelligent?” Is it possible to develop a “Chemical Artificial Intelligence?” For the development of the Chemical Artificial Intelligence, Pier Luigi Gentili relies upon the theory and tools of Natural Computing. In particular, he is tracing a new path in the field of Neuromorphic Engineering by using non-linear chemical systems and by encoding information mainly through UV-visible signals. He is proposing methods to process Fuzzy logic by molecular, supramolecular, and systems chemistry. He is editor of the book titled "The Fuzziness in Molecular, Supramolecular, and Systems Chemistry" published by MDPI in 2020.
He has several collaborations and work experience in many laboratories. For instance, the "Photochemistry and Photophysics Group" of the University of Perugia (Italy); the "Nonlinear Dynamics Group" of the Brandeis University (USA); the "European Laboratory of Nonlinear Spectroscopy" in Florence (Italy); the "Center for Photochemical Sciences" of the Bowling Green State University (USA); the "Laboratory of Computational Chemistry and Photochemistry" of University of Siena (Italy).
Areas of Research / Professional Expertise
UNDERSTANDING COMPLEXITY: NATURAL COMPUTING AND THE DEVELOPMENT OF CHEMICAL ARTIFICIAL INTELLIGENCE
Inanimate matter is driven by force-fields, whereas the interactions between biological systems are information-based. My leading questions are: “How was it possible that from an inanimate world, devoid of agents able to process information, matter self-organized in forms able to make decisions?”
“When does a chemical system become intelligent?”
Is it possible to develop a “Chemical Artificial Intelligence?”
For the development of the Chemical Artificial Intelligent, I rely upon the theory and tools of Natural Computing. In particular, I am proposing methods to process Fuzzy logic by molecules, and I am tracing a new path in the field of Neuromorphic Engineering.
For the comprehension of Complexity, I also investigate which are the questions that Science, Philosophy, and Religion share and which are the answers that each of them offers.
PHOTOPHYSICS, PHOTOCHEMISTRY AND CROMOGENISM IN DIFFERENT MICRO-ENVIRONMENTS
The photophysics and photochemistry of Organic, Inorganic, Organometallic, and Coordination Compounds may be extremely sensitive to the surrounding microenvironment. This statement is particularly true for Chromogenic Compounds, which can exert a feedback action on their microscopic environment. To understand the effect of the micro-environment, I exploit the Maximum Entropy Method. To model the interaction of light with solid samples, I use the Kubelka-Munk theory.
After photo-excitation, a molecule can undertake different relaxation pathways that are in kinetic competition among them. The Ultrafast Absorption and Emission Techniques allow investigating the relaxation dynamics. In particular, I have investigated the dependence of the relaxation dynamics on the excitation wavelength and the Vibronic Effects.
The energy coming from the sun is relevant and fundamental for our planet. I am contributing to the exploitation of solar energy by studying the Photo-induced Water Splitting reaction and the Up-Conversion of incoherent light. The Up-Conversion of light by using both the Triplet-Triplet Annihilation (TTA) process and the Photo-Physics of Rare Earth Ions allows reducing the waste of solar light.
The focus of Gentili's research and teaching is Complexity.
The XXI Century Challenges that humanity is facing can be defined as Complexity Challenges: they regard Natural, Computational, Descriptive, and Bio-ethical Complexity.
Natural Complexity regards the study of Complex Systems. Complex Systems are natural systems that science is unable to describe exhaustively. Examples of Complex Systems are both unicellular and multicellular living beings; human brains and immune systems; ecosystems; human societies; global economy; climate and geology of our planet. Science cannot predict the behavior of such systems, especially in the long term.
Computational Complexity regards those computational problems that can and cannot be solved accurately and in a reasonable lapse of time with current electronic supercomputers and software.
Descriptive Complexity is related to the recognition of variable patterns.
Bio-ethical Complexity regards all those delicate choices that societies have to make as far as the birth, suffering, and death of living beings are concerned.
Published: Jan 27, 2021 by Rendiconti Lincei. Scienze Fisiche e Naturali
Authors: Pier Luigi Gentili
This article demonstrates the relevant role that Complexity Science can play in tackling this century's global challenges.
Designing and Teaching a Novel Interdisciplinary Course on Complex Systems To Prepare New Generations To Address 21st-Century Challenges
Published: Jul 18, 2019 by J. Chem. Educ.
Authors: Pier Luigi Gentili
Subjects: Chemistry, Life Science, Materials Science, Physics
The challenges that humanity is facing spur universities to reorganize chemistry education. A contribution to the project of reimagining chemistry education is a novel interdisciplinary course that presents the properties of complex systems through the theories of out-of-equilibrium thermodynamics, nonlinear dynamics, and natural computing.