III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet Incubator Lifescape
3. Supramolecular Systems Chemistry
Nicolaou, Zachery, et al.. Prevalence of Multistability and Nonstationarity in Driven Chemical Networks. Journal of Chemical Physics. June, 2023. ZN, University of Washington, Adilson Motter, Northwestern University and Jason Green, UMass Boston survey a spontaneous prebiotic liveliness which seems to presage animate varieties. Once again, an array of phenomenal propensities are seen altogether to lay down a path to evolution and maybe our curious Earthkinder.
External flows of energy, entropy, and matter can cause sudden transitions in the stability of biological and industrial systems, and alter their dynamical function. Here, we analyze changes giving rise to complex behavior in relatively random networks under external driving forces. When subject to an influx and outflux of chemical species, the steady state can undergo bifurcations and multistable oscillations. We then show that catalysis plays an important role in the emergence of animate complexity. Our results suggest that these innate conditions can be seen to engender biochemical processes and abiogenesis. (Abstract excerpt)
Nitschke, Jonathan. Molecular Networks Come of Age. Nature. 462/736, 2009. A Cambridge University chemist cites the work of Ludlow and Otto above, and a growing corpus to laud the novel thermodynamic and kinetic approaches being applied to material systems.
What is systems chemistry? It’s the study of complex systems, or networks, of molecules. Tools for analyzing complex networks are being developed and employed in fields as diverse as computer science and sociology. By applying these tools to systems of interacting molecules – molecules that might link together into larger superstructures, or catalyse one another’s formation – chemists can investigate how interactions between members propagate through networks, allowing complex behaviour to emerge. (736)
Pandoli, Omar and Gian Piero Spada. The Supramolecular Chemistry between Eastern Philosophy and the Complexity Theory. Journal of Inclusion Phenomena and Macrocyclic Chemistry. 65/1-2, 2009. A unique contribution in this important periodical that needs to be read in its entirety. Pandoli, University of Ferrera, presently Shanghai Jiao Tong University, and Spada, University of Bologna, achieve an extraordinary synthesis across the ages between an innately creative natural systems substance and the essences of holistic perennial wisdom, as especially its Taoist dynamics of Yin and Yang. Both of these disparate encounters report and reflect an informed matter that repeatedly organizes itself as it arises, grows, quickens, and personifies.
Pross, Addy. Toward a General Theory of Evolution: Extending Darwinian Theory to Inanimate Matter. Journal of Systems Chemistry. 2/1, 2011. In this new online resource, the Ben Gurion University of the Negev chemist embellishes his deeper rootings of life through fertile chemical soils into its “physical” substrate. Six qualities of living systems in such regard are far-from-equilibrium, complexities, homochirality, teleonomic character, dynamic autocatalysis, and diverse adaptation. Although not ready to admit an implied organic cosmos, or genetic guise for these dynamics, (see Hillier) this epic morphing from old machine to phenomenal genesis grows in veracity.
Though Darwinian theory dramatically revolutionized biological understanding, its strictly biological focus has resulted in a widening conceptual gulf between the biological and physical sciences. In this paper we strive to extend and reformulate Darwinian theory in physicochemical terms so it can accommodate both animate and inanimate systems, thereby helping to bridge this scientific divide. The extended formulation is based on the recently proposed concept of dynamic kinetic stability and data from the newly emerging area of systems chemistry. The analysis leads us to conclude that abiogenesis and evolution, rather than manifesting two discrete stages in the emergence of complex life, actually constitute one single physicochemical process. (Abstract, 1)
Raucci, Umberto, et al. Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing, and Cloud Computing. Annual Review of Physical Chemistry. 74/313, 2023. National Accelerator Lab, Menlo Park, CA, and Stanford University scientists lay out tutorial research pathways with the aim of advancing beneficial chemical innovations by means of these novel title abilities. As a result, a new frontier opens as a new (second) substantial (re)creation.
Modern quantum chemistry algorithms are now able to quite enhance the prediction of nove molecular formulations and properties. Despite this progress, performing such calculations is not readily accessible since a domain expertise, programming skills, and powerful hardware is required. In this review, we discuss how to create practical platforms that can compute quantum chemistry properties such as artificial intelligence–driven input methods, and extended reality visualization. (Excerpt)
Reiher, Markus. Special Issue on Quantum Information in Chemistry. International Journal of Quantum Chemistry. 115/19, 2015. An ETH Zurich physical chemist and group leader introduces a cross-fertilization of quantum information processing methods with chemical research which is increasingly adopting a systems, network, and computational character. Some entries are Geometric Phases in Quantum Information, Orbital Entanglement in Quantum Chemistry, and The Radical Pair Mechanism and the Avian Chemical Compass.
Ruben, Mario, et al. Hierarchical Self-Assembly of Supramolecular Spintronic Modules into 1D- and 2D- Architectures with Emergence of Magnetic Properties. Chemistry: A European Journal. 11/1, 2005. Deep in the primary scientific literature a new universe is being uncovered whose matter is not a lumpen dross but which organizes itself in a progressive scale of complex, animate systems.
Ruiz-Mirazo, Kepa, et al.
Prebiotic Systems Chemistry: New Perspectives for the Origins of Life.
Ruiz-Mirazo, University of the Basque Country systems biophysicist and philosopher, Carlos Briones, Spanish National Research Council astrobiologist, and Andreas de la Escosura, Autonomous University of Madrid biochemist survey this historic project to reconstruct how living, evolving systems came to be. With 85 pages, 1,000 references, and a reach beyond biomolecules to chemical, thermodynamic and physical substrates and energies involved, it is a most comprehensive review to date. For starters, as now common, “life” is said to be represented by three main features – replication, metabolism, and compartments. In addition, conducive “prebiotic” conditions of complex biochemicals, autocatalysis, far-from-equilibrium states, morphogenesis, along with self-organizing and assembling dynamics from which life arose need to be included. Such emergent systems composed of “a great diversity of components with multiple interactions between them,” give rise to “global properties and dynamic behaviors.”
Although finding consensus about the nature and definition of life is a very difficult issue, and will remain as a subject of debate probably for a long time, there is nowadays relatively widespread agreement on which features should be shared by the simplest living systems. They must possess a genetic apparatus able to store and transmit information to their progeny, some sort of metabolism for gathering nutrients and energy from the environment, and a selectively permeable boundary that separates and distinguishes them from that environment. Hence, in order to explain how the first organisms might have appeared on Earth, or elsewhere, it is necessary to develop chemistries that enable the synthesis of information-bearing polymers, protometabolic networks, and protocellular compartments under compatible prebiotic conditions. Moreover, there is the need for finding thermodynamically and kinetically plausible pathways to integrate the three kinds of subsystems into far-from-equilibrium, autonomous agents with open-ended evolution capacities. (349)
Sadowski, Peter, et al. Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction. Journal of Chemical Information and Modeling. 56/2135, 2016. UC Irvine and ExxonMobil Research computational chemists including Pierre Baldi achieve a novel synthesis of these physical and neural methods, which are reported herein, and in Mind Over Matter. As a result, an efficient, quantum learning approach serves to parse the “grammar” of chemical reactions by these natural language processes. See also in this journal Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships by Junshui Ma, et al (55/263, 2015).
Machine learning (ML) and quantum mechanical (QM) methods can be used in two-way synergy to build chemical reaction expert systems. The proposed ML approach identifies electron sources and sinks among reactants and then ranks all source–sink pairs. This addresses a bottleneck of QM calculations by providing a prioritized list of mechanistic reaction steps. QM modeling can then be used to compute the transition states and activation energies of the top-ranked reactions, providing additional or improved examples of ranked source–sink pairs. Retraining the ML model closes the loop, producing more accurate predictions from a larger training set. The approach is demonstrated in detail using a small set of organic radical reactions. (Abstract)
Saitou, Naruya, Naruya. Introduction to Evolutionary Genomics. International: Springer, 2018. A National Institute of Genetics, Mishima, Japan population geneticist provides after 2013 a second edition which further joins our homo sapiens genetic endowment with a deep ancestry in life’s emergent development. Three main sections are Basic Processes of Genome Evolution, Evolving Genomes, and Methods for Evolutionary Genomics.
Topics and Features: Introduces the basics of molecular biology, covering protein structure and diversity, as well as DNA replication, transcription, and translation; Examines the phylogenetic relationships of DNA sequences, and the processes of mutation, neutral evolution, and natural selection; Presents a brief evolutionary history of life, surveying the key features of the genomes of prokaryotes, eukaryotes, viruses and phages, vertebrates, and humans; Reviews the various biological “omic” databases, and discusses the analysis of homologous nucleotide and amino acid sequences; Provides an overview of the experimental sequencing of genomes and transcriptomes, and the construction of phylogenetic trees.
Salles, Airton, et al. A Self-Organizing Chemical Assembly Line. Journal of the American Chemical Society. 135/51, 2013. University of Cambridge complexity chemists in coauthor Jonathan Nitschke’s group describe how principles of biological self-organization can similarly be applied to “inorganic” material dynamic reactivities. View Nitschke’s website to learn about members, projects such as Complex Topologies, and more publications.
Chemical syntheses generally involve a series of discrete transformations whereby a simple set of starting materials are progressively rendered more complex. In contrast, living systems accomplish their syntheses within complex chemical mixtures, wherein the self-organization of biomolecules allows them to form “assembly lines” that transform simple starting materials into more complex products. Here we demonstrate the functioning of an abiological chemical system whose simple parts self-organize into a complex system capable of directing the multistep transformation of the small molecules furan, dioxygen, and nitromethane into a more complex and information-rich product. The novel use of a self-assembling container molecule to catalytically transform a high-energy intermediate is central to the system’s functioning. (Abstract)
Sayama, Hiroki. Swarm Chemistry. Artificial Life. 15/1, 2009. In a special issue on Artificial Chemistry, a SUNY Binghamton bioengineer finds these generic complex systems principles to be similarly suitable across chemical domains.
We propose swarm chemistry, a new artificial chemistry framework that uses artificial swarm populations as chemical reactants. Reaction in swarm chemistry is not determined by predefined reaction rules as commonly assumed in typical artificial chemistry studies, but is spontaneously achieved by the emergence of a new spatiotemporal pattern of collective behavior through the kinetic interaction between multiple chemical species.