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III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

3. Supramolecular Systems Chemistry

Le, Tu and David Winkler. Discovery and Optimization of Materials Using Evolutionary Approaches. Chemical Reviews. 116, 6107, 2016. Akin to Peter Sadowski herein, Commonwealth Scientific and Industrial Research Organization CSIRO, Australia systems chemists use algorithmic computations to intentionally continue of life’s computational mode of proliferate, explore, test, iterate, select so to optimize onto a parametric spacescape of candidate materials. It is notable that Material Genome and Fitness Function phrases are cited as if chemicals in some way possess an evolving animate formation.

Materials science is undergoing a revolution, generating valuable new materials such as flexible solar panels, biomaterials and printable tissues, new catalysts, polymers, and porous materials with unprecedented properties. However, the number of potentially accessible materials is immense. Artificial evolutionary methods such as genetic algorithms, which explore large, complex search spaces very efficiently, can be applied to the identification and optimization of novel materials more rapidly than by physical experiments alone. This review discusses the problems of large materials spaces, the types of evolutionary algorithms employed to identify or optimize materials, and how materials can be represented mathematically as genomes, describes fitness landscapes and mutation operators commonly employed in materials evolution, and provides a comprehensive summary of published research on the use of evolutionary methods to generate new catalysts, phosphors, and a range of other materials. (Abstract)

Lehn, Jean-Marie. Constitutional Dynamic Chemistry: Bridge from Supramolecular Chemistry to Adaptive Chemistry. Topics in Current Chemistry. Volume 322, 2012. The Institut de Science et d’Ingenierie Supramolecularies, Universite de Strasbourg, Nobel laureate chemist updates and expands on this robust complex systems “science of informed matter,” which he founded some two decades ago. Chemical compounds are thus dynamically active on their own, as they innately proceed to form evolving biological precursors.

Supramolecular chemistry is intrinsically a dynamic chemistry in view of the lability of the interactions connecting the molecular components of a supramolecular entity and the resulting ability of supramolecular species to exchange their constituents. The same holds for molecular chemistry when the molecular entity contains covalent bonds that may form and break reversibility, so as to allow a continuous change in constitution by reorganization and exchange of building blocks. These features define a Constitutional Dynamic Chemistry (CDC) on both the molecular and supramolecular levels.

CDC introduces a paradigm shift with respect to constitutionally static chemistry. The latter relies on design for the generation of a target entity, whereas CDC takes advantage of dynamic diversity to allow variation and selection. Whereas self-organization by design strives to achieve full control over the output molecular or supramolecular entity by explicit programming, self-organization with selection operates on dynamic constitutional diversity in response to either internal or external factors to achieve adaptation. The merging of the features: -information and programmability, -dynamics and reversibility, -constitution and structural diversity, points to the emergence of adaptive and evolutive chemistry, towards a chemistry of complex matter. (Abstract)

Self-organization is the fundamental cosmic process that has led to the generation of complex matter, from particles to the thinking organism, in the course of the evolution of the universe. (4) In the context of the “big” problems challenging science, where physics addresses the origin and laws of the universe, and biology the rules of life, chemistry may claim to provide the means both for unraveling the progressive evolution towards complex matter by uncovering the processes that underlie self-organization. (8-9) It is clear that, before there was Darwinian evolution of living organisms, there must have been a purely chemical evolution that progressively led to the threshold of life. (9-10)

Lehn, Jean-Marie. From Supramolecular Chemistry towards Constitutional Dynamic Chemistry and Adaptive Chemistry. Chemical Society Reviews. 36/2, 2007. The Professor of Chemistry at the Universite Louis Pasteur who shared the 1989 Nobel Prize describes a salient advance of chemical research that he has pioneered. Atomic and molecular chemistry by covalent bonds can be expanded into “supermolecular” interactions between complex species held by non-covalent forces. A further domain may then include self-organization processes, either by intentional design or by allowing a Darwinian selection to take place, which is dubbed constitutional dynamic chemistry. By so doing, a revolutionary understanding of chemistry as a spontaneous generation of the “progressive evolution” of complex, informationally guided matter is achieved to connect physics and biology.

Self-organization is the fundamental process that has led to the generation of complex matter, from particles to the thinking organism, in the course of the evolution of the universe. (152) Consequently, self-organization processes are in principle able to select the correct molecular components for the generation of a given supramolecular entity from a collection of building blocks. Self-organization may thus take place with selection, by virtue of a basic feature inherent in supramolecular chemistry, its dynamic character. (153)

Highly interconnected networks (reactionally, but also constitutionally) relate to a systems chemistry. Further developments also involve sequential, hierarchical self-organization on increasing scale, with emergence of novel features/properties at each level, self-organization in space as well as in time, and passage beyond reversibility, towards self-organization and constitutional dynamics in non-equilibrium systems. (159)

Lehn, Jean-Marie. Perspectives in Chemistry – Steps toward Complex Matter. Angewandte Chemie International Edition. 52/10, 2013. For a 125th Anniversary issue, the French Nobel laureate chemist, now at ISIS Institute de Science de d’Ingenerie Supramoleculaires, presents a most succinct capsule of a cosmic genesis from physics and chemistry to biology and thought. By this vista, a progressive arrangement of matter can be sketched from discrete states to condensations, assemblies, living systems and onto reflective beings. The evolutionary vector is the result of nature’s inherent self-organizing force, which is seen to involve nonlinearity, cooperativity, complex adaptive systems and network phenomena. From this scenario and its principles, the founder from the 1990s of supramolecular and systems chemistry (search) lays out a project as a Adaptive Evolutive Chemistry for their intentional creative continuance. See also the volume Constitutional Dynamic Chemistry Mikail Bardoiu, ed. (Springer, 2012) for another Lehn paper (second quote) and chapters on this implementation.

The driving force behind this evolution towards more and more complex forms of matter is the most basic of all features, the most fundamental concept: self-organization. It all happened by itself and science will allow us to understand how and why. Chemistry has a key role and a major task in achieving this goal. Physics unravels the laws of the universe, and biology scrutinizes the rules of life. It is the mission of chemistry to build the bridge between the general laws and the specific expressions of these laws that are life and thought on our planet, Earth.

Towards Complex Matter—Self-Organization Self-organization drives towards systems of increasing complexity under the pressure of information, towards more and more complex forms of matter, up to the generation of life and thought (as we know it). Self-organization may be: 1) passive, equilibrium self-organization, involving the generation of organized molecular/covalent or supramoleular/noncovalent functional architectures by self-assembly from components under thermal equilibrium conditions; it allows for adaptation in response to external or internal stimuli/effectors under equilibrium conditions; 2) active, out-of-equilibrium self-organization, involving the generation of organized functional architectures driven by time-dependent, non-equilibrium, dissipative physical and chemical processes; it allows for adaptation and evolution under non-equilibrium conditions. Equilibrium self-organization could also be considered as self-assembly, a term which, however, does not express that it is not just the spontaneous generation of an assembly, but of an organized one. (2838)

Supramolecular chemistry has thus emphasized the perception of chemistry as the science of informed matter, with the aim of gaining progressive control over the organization of matter over its spatial (structural) and temporal(dynamic) features. (3) Self-organization is the fundamental cosmic process that has led to the generation of complex matter, from particles to the thinking organism, in the course of the evolution of the universe. (4)

Li, Jianwei, et al. Dynamic Combinatorial Libraries: From Exploring Molecular Recognition to Systems Chemistry. Journal of the American Chemical Society. 135/25, 2013. A University of Groningen group of J. Li, Piotr Nowak and Sijbren Otto contribute to a transition of chemical studies to systems emphasis, which then serves novel understandings of genetic, catalytic, and other phenomena. And we note the avail of a literary metaphor. See also from this Centre for Systems Chemistry a later paper Diversification of Self-Replicating Molecules in Nature Chemistry (8/3, 2016).

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines. (Abstract)

Ludlow, R. Frederick and Sijbren Otto. Systems Chemistry. Chemical Society Reviews. 37/101, 2008. University of Cambridge chemists provide a tutorial for a reconception of their field akin to systems biology and genomics. A new discipline is thus proposed “that looks at complex mixtures of interacting molecules.” By so doing, one might observe, nature’s nested, recapitulated scale is newly extended into this pregnant chemical realm.

Complex systems are all around us. Think of stock markets, distribution networks, the world wide web, metabolic pathways, ecosystems, and even scientific co-authorship networks. Research into complex networks is well established in most major scientific disciplines including engineering, economics, computer science, biology, mathematics and physics, but not in chemistry. (101)

Maselko, Jerzy. Self-Assembly and Self-Construction. Fellermann, Harold, et al, eds.. Artificial Life XII: Proceedings of the Twelfth International Conference. Cambridge: MIT Press, 2010. In the “Chemical Self-Assembly and Complexity” section of this large volume, along with Hiroki Sayama (see below) and others, a University of Alaska chemist blazes pathways to extend a witness of and utility for self-organizing systems theory into these heretofore seemingly inorganic, basic material domains.

The spontaneous increase of complexity in nature from the formation of elements, followed by the formation of compounds, both inorganic and organic, leading to the emergence of life -- from a single cell to multi-cellular organisms -- and the later formation of communities followed by the emergence of new technologies where complex structures are created by a humans is probably the most important property of matter.

Maskara, Nishad, et al. Programmable Simulations of Molecules and Materials with Reconfigurable Quantum Processors. arXiv:2312.02265. We cite this entry by twelve Harvard University, LBNL, UC Berkeley, Rice University and USC chemists including Anna Krylov as a frontier example as this age old endeavor begins to enter a new spiral phase of algorithmic quantum alchemy.

Simulations of quantum chemistry and materials are important applications of information processors, but realizing their practical advantage is challenging. Here, we introduce a method for correlated quantum systems represented by model spin Hamiltonians. Our approach employs qubit architectures to program real-time dynamics and to introduce an algorithm for spectral properties via classical co-processing of quantum measurement results. We develop a digital-analog simulation toolbox for efficient Hamiltonian time evolution utilizing digital Floquet engineering and hardware-optimized multi-qubit operations. (Excerpt)

Mattia, Elio and Otto Sijbren. Supramolecular Systems Chemistry. Nature Nanotechnology. 10/2, 2015. For these University of Groningen chemists, the title phrase represents a far-from-equilibrium thermodynamic propensity of living matter to kinetically self-assemble. By such natural insights, human intellects can then begin to take up and respectfully continue a genesis creation.

McArdle, Sam, et al. Quantum Computational Chemistry. Review of Modern Physics. 92/015003, 2020. Oxford University and University of Toronto materials scientists post a 51 page, 2020s tutorial as these three major scientific areas flow together and cross-inform each other. A further integration is also made with “classical” approaches, along with algorithmic methods and other skill sets so to compose a unified substantial synthesis.

A promising application of quantum computing is the solving of classically intractable chemistry problems. This may help explain phenomena such as high temperature superconductivity, solid-state physics, transition metal catalysis, and certain biochemical reactions. However, building a sufficient quantum computer for this purpose will be a scientific challenge. This review provides a comprehensive introduction with key methods to demonstrate how to map chemical problems onto a quantum computer, and to solve them. (Abstract excerpt)

McGregor, Simon, et al. Evolution of Associative Learning in Chemical Networks. PLoS Computational Biology. 8/11, 2012. By sophisticated experiments, McGregor and Phil Husbands, University of Sussex, Vera Vasas, Universitat Autònoma de Barcelona, and Christantha Fernando, University of London, bioinformation specialists find in these interactive chemistries an innate propensity to perform cognitive operations so as to enhance their viability. If this article is seen along with many similar reports across a quickening nature, at what point might we be able to imagine and realize a self-learning and self-discovering cosmic genesis?

Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ‘memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells. (Abstract)

Merindol, Remi and Andreas Walther. Materials Learning from Life: Concepts for Active, Adaptive and Autonomous Molecular Systems. Chemical Society Reviews. 46/5588, 2017. In a Chemical Systems Out of Equilibrium collection, Albert-Ludwigs University chemists well scope out the present state of science and art for condensed harder and softer matter studies into the 2010s. At once, nature’s chemical reactivity is seen to spring from vital thermodynamic complexities as it proceeds to structure and organize itself. As these inherent qualities become better quantified and understood, a radical new phase of intentional synthetic procreation is foreseen on the way to a better world.

Bioinspired out-of-equilibrium systems will set the scene for the next generation of molecular materials with active, adaptive, autonomous, emergent and intelligent behavior. Indeed life provides the best demonstrations of complex and functional out-of-equilibrium systems: cells keep track of time, communicate, move, adapt, evolve and replicate continuously. Stirred by the understanding of biological principles, artificial out-of-equilibrium systems are emerging in many fields of soft matter science. Here we put in perspective the molecular mechanisms driving biological functions with the ones driving synthetic molecular systems. Focusing on principles that enable new levels of functionalities (temporal control, autonomous structures, motion and work generation, information processing) rather than on specific material classes, we outline key cross-disciplinary concepts that emerge in this challenging field. (Abstract)

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