VIII. Earth Earns: An Open CoCreative Earthropocene to Astropocene PediaVerse

1. Mind Over Matter and Energy: Quantum, Atomic, Chemical, Astronomic Realms

Lookman, Turab, et al, eds. Information Science for Materials Discovery and Design. Berlin: Springer, 2015. A volume that gathers several 2010s endeavors such as the Material Genome Initiative, Integrated Computational Materials Engineering, (Google each) and others, under this algorithmic theme. An opening chapter is A Perspective on Materials Informatics, with other entries on Bayesian Optimization, Data Visualization, Hidden Structures in Complex Physical Systems (search Nussinov), Combinatorial Materials Science and so on. In a phenomenal Natural Genesis, these robust, sophisticated efforts can attest to a potential passage of cosmic self-creation to a our human radically intentional, evolitionary phase.

This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop for materials design) to involve iteratively learning from experiments and calculations to develop materials with optimum properties. Such a loop requires the elements of incorporating domain materials knowledge, a database of descriptors (the genes), a surrogate or statistical model developed to predict a given property with uncertainties, performing adaptive experimental design to guide the next experiment or calculation and aspects of high throughput calculations as well as experiments. (Blurb excerpt)

Louie, Steven, et al. Discovering and Understanding Materials through Computation. Nature Materials. June, 2021. UC Berkeley, Stanford and Yale researchers introduce and embellish this leading edge approach by which to mathematically conjure substantial creations. Two titles are Electronic Structure Methods for Materials Design and Mesoscopic and Multiscale Modelling. See also The Rise of Intelligent Matter by Steven Louie, et al in Nature (594/345, 2021). So herewith is another manifest instance of our Earthuman acumen beginning to initiate a new natural cocreativity.

Materials modelling and design using computational quantum and classical approaches has become well established as an essential pillar in condensed matter physics, chemistry and materials science research. The 21st century has witnessed steady advances by which to understand and predict the ground-state, excited-state and dynamical properties of materials from molecules to nanoscopic/mesoscopic scale to larger dimensional systems. The four entries in this Perspective give a brief overview, as well as some future challenges and opportunities. (Abstract excerpt)

Lu, Ziaobo, et al. Superconductors, Orbital Magnets, and Correlated States in Magic Angle Bilayer Graphene. arXiv:1903.06513. Barcelona Institute of Science and Technology, UT Austin, National Institute for Material Science, Japan, and Chinese Academy of Sciences, Beijing condensed matter physicists tap into nature’s seemingly endless array of material properties for human benefit and creative avail. Companion entries are With a Simple Twist, “Magic” Material is Now the Big Thing in Physics by David Freedman in Quanta Magazine, (April 30, 2019), and Unconventional Supercondictivity in Magic-Angle Graphene Superlattices in Nature (556/43, 2018).

Superconductivity often occurs close to broken-symmetry parent states and is especially common in doped magnetic insulators. When twisted close to a magic relative orientation angle near 1 degree, bilayer graphene has flat moire superlattice minibands that have emerged as a rich and highly tunable source of strong correlation physics, notably the appearance of superconductivity close to interaction-induced insulating states. Here we report on the fabrication of bilayer graphene devices with exceptionally uniform twist angles. Our study shows that symmetry-broken states, interaction driven insulators, and superconducting domes are common across the entire moire flat bands, including near charge neutrality. (Abstract excerpt)

Luisi, Pier Luigi and Cristiano Chiarabelli, eds. Chemical Synthetic Biology. New York: Wiley, 2011. A table of contents and sample first chapter are available on the publisher’s book webpage. Four parts cover Nucleic Acids, Peptides and Proteins, Complex Systems, and General Problems. Dr. Luisi introduces, and a typical chapter is “Synthetic Genetic Codes as the Basis of Synthetic Life” by J. Tze-Fei Wong and Hong Xue

Chemistry plays a very important role in the emerging field of synthetic biology. In particular, chemical synthetic biology is concerned with the synthesis of chemical structures, such as proteins, that do not exist in nature. With contributions from leading international experts, Chemical Synthetic Biology shows how chemistry underpins synthetic biology. The book is an essential guide to this fascinating new field, and will find a place on the bookshelves of researchers and students working in synthetic chemistry, synthetic and molecular biology, bioengineering, systems biology, computational genomics, and bioinformatics. (Publisher)

Makey, Ghaith, et al. Universality of Dissipative Self-Assembly from Quantum Dots to Human Cells. Nature Physics. 16/7, 2020. A 15 member project at the National Nanotechnology Research Center and Institute of Materials Science, Bilkent University, Ankara, Turkey well quantifies nature’s deep autocatalytic, self-organizing propensities from quantum to organic cellularity. These constant processes across a wide domain is then seen to express a universal repetition in kind. The work merited a review Dissipate Your Way to Self-Assembly by Gili Bisker (Tel Aviv University) in the same issue. So at the same while that the Hagia Sophia (holy wisdom) is reverting back to a mosque, Turkish scientists, whose achievement is praised by a Jewish woman, contribute and look forward to a new common creation.

An important goal of self-assembly research is to develop a general methodology applicable to almost any material, from the smallest to the largest scales, whereby qualitatively identical results are obtained independently of initial conditions, size, shape and function of the constituents. Here, we introduce a dissipative self-assembly methodology demonstrated on a diverse spectrum of materials, from simple, passive, identical quantum dots (a few hundred atoms) that experience extreme Brownian motion, to complex, active, non-identical human cells (~1017 atoms) with sophisticated internal dynamics. Autocatalytic growth curves of the self-assembled aggregates are shown to scale identically, and interface fluctuations of growing aggregates obey the universal Tracy–Widom law. (Abstract)

Marcovich, Anne and Terry Shinn. Toward a New Dimension: Exploring the Nanoscale. Oxford: Oxford University Press, 2014. An update introduction to these microscape frontiers of physical and biological co-creation. In a section entitled Life as a Dynamic Lego Game, in accord with a nature that “tinkers” by trying out many candidates, a program is proposed to include and balance both selective effects along with an intentional engineering design.

Marelli, Benedetto, et al. Programming Function into Mechanical Forms by Directed Assembly of Silk Bulk Materials. Proceedings of the National Academy of Sciences. 114/451, 2017. An eight member team of Tufts University biomedical, chemical, and electrical engineers quantify how these exemplary fabrics have been formed by nature, and then go on to discuss their novel, intentional advance and use. The work merited a report in the same issue as When Bottom-Up Meets Top Down by the Israeli chemists Zvi Shtein and Oded Shoseyov where this evolutionary passage of natural materiality onto humanly creative intention is given notice.

We report simple, water-based fabrication methods based on protein self-assembly to generate 3D silk fibroin bulk materials that can be easily hybridized with water-soluble molecules to obtain multiple solid formats with predesigned functions. Controlling self-assembly leads to robust, machinable formats that exhibit thermoplastic behavior consenting material reshaping at the nanoscale, microscale, and macroscale. We illustrate the versatility of the approach by realizing demonstrator devices where large silk monoliths can be generated, polished, and reshaped into functional mechanical components that can be nanopatterned, embed optical function, heated on demand in response to infrared light, or can visualize mechanical failure through colorimetric chemistries embedded in the assembled (bulk) protein matrix. Finally, we show an enzyme-loaded solid mechanical part, illustrating the ability to incorporate biological function within the bulk material with possible utility for sustained release in robust, programmably shapeable mechanical formats. (Abstract)

Markovic, Danijela and Julie Grolier. Quantum Neuromorphic Computing. arXiv:2006.15111. We note this entry by CNRS, University of Paris-Saclay physicists as an instance of a 2020s hyper-synthesis by an effective integration of deep physical and active cerebral qualities. See also Physics for Neuromorphic Computing by the authors and colleagues in Nature Reviews Physics (2/499, 2020).

Quantum neuromorphic computing physically implements neural networks in brain-inspired quantum hardware so to speed up their computation. In this perspective article, we show that this emerging paradigm could make best use of existing and near future intermediate size quantum computers. Some approaches are based on parametrized quantum circuits, and use neural network-inspired algorithms to train them. Other approaches, closer to classical neuromorphic computing, take advantage of the physical properties of quantum oscillator assemblies to mimic neurons and compute. (Abstract)

Over the past years, quantum and neuromorphic computing have emerged as two leading visions for the future of computation. Quantum computing makes use of intrinsic properties such as entanglement and superposition to design algorithms that are faster than classical ones. Neuromorphic computing gets inspiration from the brain and uses complex ensembles of artificial neurons and synapses to mimic animal intelligence and calculate faster with low energy consumption. In this article we review convergences between these two fields, and on the experimental implementations of neuromorphic computing on quantum hardware. (1)

McCarthy, Wil. Hacking Matter. New York: Basic Books, 2003. A technology writer extols the seemingly unlimited potentials to redesign, create and “program” the subatomic basis of nature, by which endeavor humankind might take over the material creation of the universe.

Mehr, Hessam, et al. A Universal System for Digitization and Automatic Execution of the Chemical Synthesis Literature. Science. 370/101, 2020. As our collective human acumen begins to take up and over a new material creation, aka synthetic chemistry, University of Glasgow chemists including Leroy Cronin describe how language-based computational methods can enhance and speed up the process. The project involves both the detection of current natural forms, along with finding and making novel compositions for a better life and planet.

Robotic systems for chemical synthesis are growing in popularity but can be difficult to run and maintain because of the lack of a standard operating system or capacity for access to the literature through natural language processing. Here we describe an extendable chemical execution architecture that can be informed by automatically reading the literature so to achieve a universal autonomous workflow. We showcase automated syntheses of 12 compounds from the literature, including the analgesic lidocaine, the Dess-Martin periodinane oxidation reagent, and the fluorinating agent AlkylFluor. (Abstract)

Mitra, Anupam, et al.. Macrostates vs. Microstates in the Classical Simulation of Critical Phenomena in Quench Dynamics of 1D Ising Models. arXiv:2310.08567.. This entry by Center for Quantum Information and Control, University of New Mexico physicists including Ivan Deutsch is posted as an example among many to show how readily human intellects can delve into these fundamental depths and then to take over and commence anew a second intentional, informed material cocreation. See also Ultracold field-linked tetratomic molecules by Chen, Xing-Yan Chen, et al in Nature (January 31, 2024) for a similar instance.

We study the tractability of classically simulating critical phenomena in the quench dynamics of one-dimensional transverse field Ising models (TFIMs) using highly truncated matrix product states (MPS). We focus on two paradigmatic examples: a dynamical quantum phase transition (DQPT) that occurs in nonintegrable long-range TFIMs, and the infinite-time correlation length of the integrable nearest-neighbor TFIM when quenched to the critical point. For the DQPT, we show that the order parameters can be efficiently simulated with surprisingly heavy truncation of the MPS bond dimension. This can be used to reliably extract critical properties of the phase transition, including critical exponents, even when the full many-body state is not simulated with high fidelity.

Moeini, Samaneh and Tie Jun Cui. Reflective Metasurfaces: Fractal Coding Metamaterials. Annalen der Physik. 531/2, 2019. University of Aveiro, Portugal and Southeast University, Nanking, China informatic engineers (a global team posts in a German periodical) discern and deftly apply nature’s self-similar mathematics to create a novel realm of visionary surfaces.

Editor’s Note In article number 1800134, Samaneh Moeini and Tie Jun Cui propose a concept of fractal coding metamaterials, which can be used to design reflective metasurfaces with self‐similar pseudo‐random phase responses. The introduced coding strategy utilizes fractal interpolation functions. An analytical relation between the reflection phase distribution and the far‐field radiation pattern is derived.

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