Living cells and biological mechanisms as prototypes for developing chemical artificial intelligence.

Artificial Intelligence (AI) is having a revolutionary impact on our societies. It is helping humans in facing the global challenges of this century. Traditionally, AI is developed in software or through neuromorphic engineering in hardware. More recently, a brand-new strategy has been proposed. It is the so-called Chemical AI (CAI), which exploits molecular, supramolecular, and systems chemistry in wetware to mimic human intelligence. In this work, two promising approaches for boosting CAI are described. One regards designing and implementing neural surrogates that can communicate through optical or chemical signals and give rise to networks for computational purposes and to develop micro/nanorobotics. The other approach concerns "bottom-up synthetic cells" that can be exploited for applications in various scenarios, including future nano-medicine. Both topics are presented at a basic level, mainly to inform the broader audience of non-specialists, and so favour the rise of interest in these frontier subjects.

The Versatile Photo-Thermal Behaviour of a 2-Hydroxyazobenzene.

Photochromic compounds are employed in implementing neuron surrogates. They will boost the development of neuromorphic engineering in wetware. In this work, the photochromic behaviours of (E)-3,4,6-trichloro-2-(p-diazenil)-phenol (t-DZH) and its conjugated phenoxide base (t-DZ) have been investigated experimentally in three different media: (1) pure acetonitrile, (2) in water and acetonitrile mixed in a 1/1 volume ratio, and (3) in an aqueous micellar solution of 3-(N,N-Dimethylmyristylammonio)propanesulfonate (SB3-14). The analysis of the spectral and kinetic features of t-DZH and t-DZ has been supported by quantum-mechanical DFT calculations, the maximum entropy method, and the determination of their colourability (C). The versatility of t-DZH and t-DZ makes them promising molecular probes of micro-environments and potential ingredients of photochemical oscillators required for implementing pacemaker neurons capable of communicating through optical signals in wetware.

A Role for Bottom-Up Synthetic Cells in the Internet of Bio-Nano Things?

The potential role of bottom-up Synthetic Cells (SCs) in the Internet of Bio-Nano Things (IoBNT) is discussed. In particular, this perspective paper focuses on the growing interest in networks of biological and/or artificial objects at the micro- and nanoscale (cells and subcellular parts, microelectrodes, microvessels, etc.), whereby communication takes place in an unconventional manner, i.e., via chemical signaling. The resulting "molecular communication" (MC) scenario paves the way to the development of innovative technologies that have the potential to impact biotechnology, nanomedicine, and related fields. The scenario that relies on the interconnection of natural and artificial entities is briefly introduced, highlighting how Synthetic Biology (SB) plays a central role. SB allows the construction of various types of SCs that can be designed, tailored, and programmed according to specific predefined requirements. In particular, "bottom-up" SCs are briefly described by commenting on the principles of their design and fabrication and their features (in particular, the capacity to exchange chemicals with other SCs or with natural biological cells). Although bottom-up SCs still have low complexity and thus basic functionalities, here, we introduce their potential role in the IoBNT. This perspective paper aims to stimulate interest in and discussion on the presented topics. The article also includes commentaries on MC, semantic information, minimal cognition, wetware neuromorphic engineering, and chemical social robotics, with the specific potential they can bring to the IoBNT.

Thin-Plate Superstructures of the Immunogenic 33-mer Gliadin Peptide.

Gluten related-disorders have a prevalence of 1-5 % worldwide triggered by the ingestion of gluten proteins in wheat, rye, barley, and some oats. In wheat gluten, the most studied protein is gliadin, whose immunodominant 33-mer amino acid fragment remains after digestive proteolysis and accumulates in the gut mucosa. Here, we report the formation of 33-mer thin-plate superstructures using intrinsic tyrosine (Tyr) steady-state fluorescence anisotropy and cryo-TEM in combination with water tension measurements. Furthermore, we showed that fluorescence decay measurements of 33-mer intrinsic fluorophore Tyr provided information on the early stages of the formation of the thin-plate structures. Finally, conformational analysis of Tyr residues using minimalist models by molecular dynamic simulations (MD) demonstrated that changes in Tyr rotamer states depend on the oligomerization stage. Our findings further advance the understanding of the formation of the 33-mer gliadin peptide superstructures and their relation to health and disease.

Establishing a New Link between Fuzzy Logic, Neuroscience, and Quantum Mechanics through Bayesian Probability: Perspectives in Artificial Intelligence and Unconventional Computing.

Human interaction with the world is dominated by uncertainty. Probability theory is a valuable tool to face such uncertainty. According to the Bayesian definition, probabilities are personal beliefs. Experimental evidence supports the notion that human behavior is highly consistent with Bayesian probabilistic inference in both the sensory and motor and cognitive domain. All the higher-level psychophysical functions of our brain are believed to take the activities of interconnected and distributed networks of neurons in the neocortex as their physiological substrate. Neurons in the neocortex are organized in cortical columns that behave as fuzzy sets. Fuzzy sets theory has embraced uncertainty modeling when membership functions have been reinterpreted as possibility distributions. The terms of Bayes' formula are conceivable as fuzzy sets and Bayes' inference becomes a fuzzy inference. According to the QBism, quantum probabilities are also Bayesian. They are logical constructs rather than physical realities. It derives that the Born rule is nothing but a kind of Quantum Law of Total Probability. Wavefunctions and measurement operators are viewed epistemically. Both of them are similar to fuzzy sets. The new link that is established between fuzzy logic, neuroscience, and quantum mechanics through Bayesian probability could spark new ideas for the development of artificial intelligence and unconventional computing.

The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.

The global challenges of the XXI century require a more in-depth analysis and investigation of complex systems [...].

A multi-spectroscopic approach to investigate the interactions between Gramicidin A and silver nanoparticles.

The comprehension and control of the interactions between nanoparticles and proteins at a molecular level are crucial to improve biomedical applications of nanomaterials and to develop nanosystems able to influence and regulate the conformational changes in proteins. In this work, we explore the interactions between Gramicidin A peptide (GramA) and dodecanethiol-stabilized small silver nanoparticles (D-AgNPs), paying particular attention to the effect on GramA conformation in POPC bilayers. D-AgNPs have been prepared to have dimensions (5 nm) and a hydrophobic nature compatible with the POPC lipid bilayer. Fluorescence, Raman and IR spectroscopies have been used to investigate both peptide conformation and its position inside the phospholipid bilayer. Results are discussed in terms of solvent exposure and conformation of GramA peptide.

Chiral separation of helical chromenes with chloromethyl phenylcarbamate polysaccharide-based stationary phases.

Two chloromethyl phenylcarbamate-based chiral stationary phases, one containing an amylose-type chiral selector (Lux Amylose 2, from Phenomenex) and the other a cellulose-type one (Lux Cellulose-4, from Phenomenex), were successfully used for the chiral resolution of three helical chromenes featuring a helicene-like structure. The compound bearing a phenyl substituent on the helicene-like structure was enantioresolved at 25°C with Lux Cellulose-4 and a n-hexane/1-propanol 99:1 v/v eluent. With a n-hexane/2-propanol 99.8:0.2 v/v mobile phase, the same column (operated at 35°C) provided the separation of the four isomers of the compound having a hexyl residue on the helicene-like motif and an additional asymmetric carbon. Lux Amylose-2 was necessary for the enantioseparation of the compound having the sole hexyl residue on the helical scaffold. For the last compound a n-hexane/2-propanol 99.8:0.2 v/v eluent was used, and the column temperature was fixed at 5°C. The enantiomer elution order was appraised by using electronic circular dichroism and theoretical calculations. Notably, different thermodynamics of retention and enantioseparation were observed for molecules with pronounced structural similarity, that is, the enantiomer pairs of the compound containing the additional asymmetric carbon atom. Indeed, both entropically and enthalpically controlled adsorption and separation processes were observed.

The Fuzziness of the Molecular World and Its Perspectives.

Scientists want to comprehend and control complex systems. Their success depends on the ability to face also the challenges of the corresponding computational complexity. A promising research line is artificial intelligence (AI). In AI, fuzzy logic plays a significant role because it is a suitable model of the human capability to compute with words, which is relevant when we make decisions in complex situations. The concept of fuzzy set pervades the natural information systems (NISs), such as living cells, the immune and the nervous systems. This paper describes the fuzziness of the NISs, in particular of the human nervous system. Moreover, it traces three pathways to process fuzzy logic by molecules and their assemblies. The fuzziness of the molecular world is useful for the development of the chemical artificial intelligence (CAI). CAI will help to face the challenges that regard both the natural and the computational complexity.

Processing Binary and Fuzzy Logic by Chaotic Time Series Generated by a Hydrodynamic Photochemical Oscillator.

This work demonstrates the computational power of a hydrodynamic photochemical oscillator based on a photochromic naphthopyran generating aperiodic time series. The chaotic character of the time series is tested by calculating its largest Lyapunov exponent and the correlation dimension of its attractor after building its phase space through the Takens' theorem. Then, the chaotic dynamic is shown to be suitable to implement all the fundamental Boolean two-inputs-one-output logic gates. Finally, the strategy to implement fuzzy logic systems (FLSs) based on the time series is described. Such FLSs promise to be useful in the field of computational linguistics, which is concerned with the development of artificial intelligent systems able to transform collections of numerical data into natural language texts.

Optical Communication among Oscillatory Reactions and Photo-Excitable Systems: UV and Visible Radiation Can Synchronize Artificial Neuron Models.

Neuromorphic engineering promises to have a revolutionary impact in our societies. A strategy to develop artificial neurons (ANs) is to use oscillatory and excitable chemical systems. Herein, we use UV and visible radiation as both excitatory and inhibitory signals for the communication among oscillatory reactions, such as the Belousov-Zhabotinsky and the chemiluminescent Orban transformations, and photo-excitable photochromic and fluorescent species. We present the experimental results and the simulations regarding pairs of ANs communicating by either one or two optical signals, and triads of ANs arranged in both feed-forward and recurrent networks. We find that the ANs, powered chemically and/or by the energy of electromagnetic radiation, can give rise to the emergent properties of in-phase, out-of-phase, anti-phase synchronizations and phase-locking, dynamically mimicking the communication among real neurons.

Probing and exploiting the chaotic dynamics of a hydrodynamic photochemical oscillator to implement all the basic binary logic functions.

The convective motions within a solution of a photochromic spiro-oxazine being irradiated by UV only on the bottom part of its volume, give rise to aperiodic spectrophotometric dynamics. In this paper, we study three nonlinear properties of the aperiodic time series: permutation entropy, short-term predictability and long-term unpredictability, and degree distribution of the visibility graph networks. After ascertaining the extracted chaotic features, we show how the aperiodic time series can be exploited to implement all the fundamental two-inputs binary logic functions (AND, OR, NAND, NOR, XOR, and XNOR) and some basic arithmetic operations (half-adder, full-adder, half-subtractor). This is possible due to the wide range of states a nonlinear system accesses in the course of its evolution. Therefore, the solution of the convective photochemical oscillator results in hardware for chaos-computing alternative to conventional complementary metal-oxide semiconductor-based integrated circuits.

P-Type Photochromism of New Helical Naphthopyrans: Synthesis and Photochemical, Photophysical and Theoretical Study.

Two novel helical naphthopyrans have been synthesised. The helical scaffold has the interesting effect of increasing the thermal stability of the transoid-trans (TT) open isomer formed upon UV irradiation of the closed form (CF), which transforms these naphthopyrans from thermal to photochemical photochromes. The photochromic performance is excellent in both polar and apolar solvents and the conversion percentage from the CF to the TT form can be as high as 92.8 %. We propose a new method to determine the quantum yields of the photochemical processes that lead to transoid-cis (TC) and TT isomers, and their molar absorption coefficients. The thermal stability of the TT and TC isomers has been studied in different solvents. The quantum yields of fluorescence before and after irradiation, along with the decay lifetimes, have also been measured. TD-DFT calculations have been performed to determine the relative thermodynamic stability of the species involved in the photochromic mechanism and to rationalise their spectral properties.

Analysis and prediction of aperiodic hydrodynamic oscillatory time series by feed-forward neural networks, fuzzy logic, and a local nonlinear predictor.

Forecasting of aperiodic time series is a compelling challenge for science. In this work, we analyze aperiodic spectrophotometric data, proportional to the concentrations of two forms of a thermoreversible photochromic spiro-oxazine, that are generated when a cuvette containing a solution of the spiro-oxazine undergoes photoreaction and convection due to localized ultraviolet illumination. We construct the phase space for the system using Takens' theorem and we calculate the Lyapunov exponents and the correlation dimensions to ascertain the chaotic character of the time series. Finally, we predict the time series using three distinct methods: a feed-forward neural network, fuzzy logic, and a local nonlinear predictor. We compare the performances of these three methods.

A triplet-triplet annihilation based up-conversion process investigated in homogeneous solutions and oil-in-water microemulsions of a surfactant.

The triplet-triplet annihilation based up-conversion process, involving a platinum octaethyl-porphyrin (PtOEP) as a sensitizer and tetraphenyl-pyrene (TPPy) as an emitter, has been investigated in homogeneous solutions of toluene, bromobenzene and anisole, and oil-in-water microemulsions of the TX-100 surfactant, where toluene constitutes the non-polar phase. In homogeneous solutions, the highest up-conversion quantum yield (of the order of 20%) has been achieved in toluene, being the solvent that has the lowest viscosity among those explored. The up-conversion emission from the PtOEP-TPPy pair has been then investigated in a toluene based oil-in-water microemulsion at three different concentrations of the solutes, showing quantum yields up to the order of 1%, under the same irradiation conditions, but different deoxygenating procedures. The results herein reported might represent a good starting point for a future investigation in microheterogeneous systems. An optimization of the microemulsion composition, in terms of surfactant, co-surfactant and toluene concentrations, could allow us to increase the sensitizer and emitter concentrations and set up the best operative conditions to obtain even higher up-conversion efficiencies.

The Conformational Contribution to Molecular Complexity and Its Implications for Information Processing in Living Beings and Chemical Artificial Intelligence.

This work highlights the relevant contribution of conformational stereoisomers to the complexity and functions of any molecular compound. Conformers have the same molecular and structural formulas but different orientations of the atoms in the three-dimensional space. Moving from one conformer to another is possible without breaking covalent bonds. The interconversion is usually feasible through the thermal energy available in ordinary conditions. The behavior of most biopolymers, such as enzymes, antibodies, RNA, and DNA, is understandable if we consider that each exists as an ensemble of conformers. Each conformational collection confers multi-functionality and adaptability to the single biopolymers. The conformational distribution of any biopolymer has the features of a fuzzy set. Hence, every compound that exists as an ensemble of conformers allows the molecular implementation of a fuzzy set. Since proteins, DNA, and RNA work as fuzzy sets, it is fair to say that life's logic is fuzzy. The power of processing fuzzy logic makes living beings capable of swift decisions in environments dominated by uncertainty and vagueness. These performances can be implemented in chemical robots, which are confined molecular assemblies mimicking unicellular organisms: they are supposed to help humans "colonise" the molecular world to defeat diseases in living beings and fight pollution in the environment.

Neuromorphic Engineering in Wetware: Discriminating Acoustic Frequencies through Their Effects on Chemical Waves.

Some features of the human nervous system can be mimicked not only through software or hardware but also through liquid solutions of chemical systems maintained under out-of-equilibrium conditions. We describe the possibility of exploiting a thin layer of the Belousov-Zhabotinsky (BZ) reaction as a surrogate for the cochlea for sensing acoustic frequencies. Experiments and simulations demonstrate that, as in the human ear where the cochlea transduces the mechanical energy of the acoustic frequencies into the electrochemical energy of neural action potentials and the basilar membrane originates topographic representations of sounds, our bioinspired chemoacoustic system, based on the BZ reaction, gives rise to spatiotemporal patterns as the representation of distinct acoustic bands through transduction of mechanical energy into chemical energy. Acoustic frequencies in the range 10-2000 Hz are partitioned into seven distinct bands based on three attributes of the emerging spatiotemporal patterns: (1) the types and frequencies of the chemical waves, (2) their velocities, and (3) the Faraday waves' wavelengths.

Tracing a new path in the field of AI and robotics: mimicking human intelligence through chemistry. Part II: systems chemistry.

Inspired by some traits of human intelligence, it is proposed that wetware approaches based on molecular, supramolecular, and systems chemistry can provide valuable models and tools for novel forms of robotics and AI, being constituted by soft matter and fluid states as the human nervous system and, more generally, life, is. Bottom-up mimicries of intelligence range from the molecular world to the multicellular level, i.e., from the Ångström (10-10 meters) to the micrometer scales (10-6 meters), and allows the development of unconventional chemical robotics. Whereas conventional robotics lets humans explore and colonise otherwise inaccessible environments, such as the deep oceanic abysses and other solar system planets, chemical robots will permit us to inspect and control the microscopic molecular and cellular worlds. This article suggests that systems made of properly chosen molecular compounds can implement all those modules that are the fundamental ingredients of every living being: sensory, processing, actuating, and metabolic networks. Autonomous chemical robotics will be within reach when such modules are compartmentalised and assembled. The design of a strongly intertwined web of chemical robots, with or without the involvement of living matter, will give rise to collective forms of intelligence that will probably reproduce, on a minimal scale, some sophisticated performances of the human intellect and will implement forms of "general AI." These remarkable achievements will require a productive interdisciplinary collaboration among chemists, biotechnologists, computer scientists, engineers, physicists, neuroscientists, cognitive scientists, and philosophers to be achieved. The principal purpose of this paper is to spark this revolutionary collaborative scientific endeavour.

Tracing a new path in the field of AI and robotics: mimicking human intelligence through chemistry. Part I: molecular and supramolecular chemistry.

Chemical Artificial Intelligence (CAI) is a brand-new research line that exploits molecular, supramolecular, and systems chemistry in wetware (i.e., in fluid solutions) to imitate some performances of human intelligence and promote unconventional robotics based on molecular assemblies, which act in the microscopic world, otherwise tough to be accessed by humans. It is undoubtedly worth spreading the news that AI researchers can rely on the help of chemists and biotechnologists to reach the ambitious goals of building intelligent systems from scratch. This article reports the first attempt at building a Chemical Artificial Intelligence knowledge map and describes the basic intelligent functions that can be implemented through molecular and supramolecular chemistry. Chemical Artificial Intelligence provides new tools and concepts to mimic human intelligence because it shares, with biological intelligence, the same principles and materials. It enables peculiar dynamics, possibly not accessible in software and hardware domains. Moreover, the development of Chemical Artificial Intelligence will contribute to a deeper understanding of the strict link between intelligence and life, which are two of the most remarkable emergent properties shown by the Complex Systems we call biological organisms.

The structures, morphologies, and photophysical properties of multiluminescent layered lanthanide-phosphono-carboxylate nanoparticles.

A new family of layered metal(III)-phosphono-carboxylate nanostructures (M=Y, Eu, Tb, Er, and Yb) was hydrothermally synthesized and their structures and morphologies were characterized by X-ray powder diffraction and TEM. 4-[Bis(phosphonomethyl)amino]caproic acid and 4- [bis(phosphonomethyl)amino]undecanoic acid, with general formula (H(2)O(3)PCH(2))(2)NR (R=C(5)H(10)COOH(P2CAPR) and C(10)H(22)COOH(P2UND), respectively) were used as building blocks for the preparation of novel layered hybrid materials in which the inorganic layers were composed of MO(7) or MO(8) polyhedra and PO(3)C tetrahedra. The interlayer region was occupied by carboxyalkyl chains. These layered compounds were easily dispersed as stable solutions in alkylamine/water upon ultrasonication. These dispersions were constituted of rectangular elongated nanoparticles (NPs), which showed a distribution of sizes ranging from 20-500 nm. These new materials had interesting photophysical properties because they were multiluminescent compounds. These properties gave rise to several emission bands, which were spread over the broad spectroscopic region, from the near-UV up to the near-IR regions. Each emission band had a specific lifetime, which ranged from the sub-ps to the ms scale.