A Modular Programmable Inorganic Cluster Discovery Robot for the Discovery and Synthesis of Polyoxometalates

The exploration of complex multi-component chemical reactions leading to new clusters, where discovery requires both molecular self-assembly and crystallization, is a major challenge. This is because the systematic approach required for an experimental search is limited when the number of parameters in a chemical space becomes too large, restricting both exploration, and reproducibility. Herein, we present a synthetic strategy to systematically search a very large set of potential reactions, using an inexpensive, high-throughput platform; modular in terms of both hardware and software, and capable of running multiple reactions with in-line analysis; for the automation of inorganic and materials chemistry. The platform has been used to explore several inorganic chemical spaces to discover new, and reproduce known, tungsten-based, mixed transition-metal polyoxometalate clusters, giving a digital code allowing the easy repeat synthesis of the clusters. Among the many species identified in this work, most significantly is the discovery of a novel, purely inorganic W24FeIII-superoxide cluster formed under ambient conditions. The Modular Wheel Platform (MWP) was then employed to undertake two chemical space explorations producing compounds [1-4]: (C2H8N)10Na2[H6Fe(O2)W24O82(H2O)25] (1, {W24Fe}), (C2H8N)72Na16[H16Co8W200O660(H2O)40] (2, {W200Co8}), (C2H8N)72Na16[H16Ni8W200 O660-(H2O)40] (3, {W200Ni8}) and (C2H8N)14[H26W34V4O130] (4, {W34V4}), along with many other known species, for example simple Keggin clusters and 1D {W11M2+} chains.

Download Full-text

Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments

10.26434/chemrxiv.7712453.v1 ◽

2019 ◽

Author(s):

Leroy Cronin ◽

Vasilios Duros ◽

Jonathan Grizou ◽

Abhishek Sharma ◽

Hessam Mehr ◽

...

Keyword(s):

Self Assembly ◽

State Of The Art ◽

Chemical Space ◽

Autonomous Systems ◽

Quality Data ◽

High Quality Data ◽

Current State ◽

Robot Teams ◽

Substantial Progress ◽

Inorganic Chemical

<div> Traditionally, chemists have relied on years of training and accumulated experience in order to discover new molecules. But the space of possible molecules so vast, only a limited exploration with the traditional methods can be ever possible. This means that many opportunities for the discovery of interesting phenomena have been missed, and in addition, the inherent variability of these phenomena can make them difficult to control and understand. The current state-of-the-art is moving towards the development of automated and eventually fully autonomous systems coupled with in-line analytics and decision-making algorithms. Yet even these, despite the substantial progress achieved recently, still cannot easily tackle large combinatorial spaces as they are limited by the lack of high-quality data. Herein, we explore the utility of active learning methods for exploring the chemical space by comparing collaboration between human experimenters with an algorithm-based search, against their performance individually to probe the self-assembly and crystallization of the polyoxometalate cluster Na6[Mo120Ce6O366H12(H2O)78]·200H2O (1). We show that the robot-human teams are able to increase the prediction accuracy to 75.6±1.8%, from 71.8±0.3% with the algorithm alone and 66.3±1.8% from only the human experimenters demonstrating that human-robot teams beat robots or humans working alone. </div>

Download Full-text

Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments

10.26434/chemrxiv.7712453 ◽

2019 ◽

Author(s):

Leroy Cronin ◽

Vasilios Duros ◽

Jonathan Grizou ◽

Abhishek Sharma ◽

Hessam Mehr ◽

...

Keyword(s):

Self Assembly ◽

State Of The Art ◽

Chemical Space ◽

Autonomous Systems ◽

Quality Data ◽

High Quality Data ◽

Current State ◽

Robot Teams ◽

Substantial Progress ◽

Inorganic Chemical

<div> Traditionally, chemists have relied on years of training and accumulated experience in order to discover new molecules. But the space of possible molecules so vast, only a limited exploration with the traditional methods can be ever possible. This means that many opportunities for the discovery of interesting phenomena have been missed, and in addition, the inherent variability of these phenomena can make them difficult to control and understand. The current state-of-the-art is moving towards the development of automated and eventually fully autonomous systems coupled with in-line analytics and decision-making algorithms. Yet even these, despite the substantial progress achieved recently, still cannot easily tackle large combinatorial spaces as they are limited by the lack of high-quality data. Herein, we explore the utility of active learning methods for exploring the chemical space by comparing collaboration between human experimenters with an algorithm-based search, against their performance individually to probe the self-assembly and crystallization of the polyoxometalate cluster Na6[Mo120Ce6O366H12(H2O)78]·200H2O (1). We show that the robot-human teams are able to increase the prediction accuracy to 75.6±1.8%, from 71.8±0.3% with the algorithm alone and 66.3±1.8% from only the human experimenters demonstrating that human-robot teams beat robots or humans working alone. </div>

Download Full-text

Expanding the Solvent Chemical Space for Self-Assembly of Dipeptide Nanostructures

ACS Nano ◽

10.1021/nn404237f ◽

2014 ◽

Vol 8 (2) ◽

pp. 1243-1253 ◽

Cited By ~ 100

Author(s):

Thomas O. Mason ◽

Dimitri Y. Chirgadze ◽

Aviad Levin ◽

Lihi Adler-Abramovich ◽

Ehud Gazit ◽

...

Keyword(s):

Self Assembly ◽

Chemical Space

Download Full-text

STM study on the self-assembly of oligothiophene-based organic semiconductors

Beilstein Journal of Nanotechnology ◽

10.3762/bjnano.2.88 ◽

2011 ◽

Vol 2 ◽

pp. 802-808 ◽

Cited By ~ 16

Author(s):

Elena Mena-Osteritz ◽

Marta Urdanpilleta ◽

Erwaa El-Hosseiny ◽

Berndt Koslowski ◽

Paul Ziemann ◽

...

Keyword(s):

Organic Semiconductors ◽

Self Assembly ◽

Theoretical Calculations ◽

The Self ◽

Scanning Tunneling ◽

Ambient Conditions ◽

Tunneling Microscopy ◽

Substitution Pattern ◽

Electronic Density ◽

The Individual

The self-assembly properties of a series of functionalized regioregular oligo(3-alkylthiophenes) were investigated by using scanning tunneling microscopy (STM) at the liquid–solid interface under ambient conditions. The characteristics of the 2-D crystals formed on the (0001) plane of highly ordered pyrolitic graphite (HOPG) strongly depend on the length of the π-conjugated oligomer backbone, on the functional groups attached to it, and on the alkyl substitution pattern on the individual thiophene units. Theoretical calculations were performed to analyze the geometry and electronic density of the molecular orbitals as well as to analyze the intermolecular interactions, in order to obtain models of the 2-D molecular ordering on the substrate.

Download Full-text

Programmable Microbial Ink for 3D Printing of Living Materials Produced from Genetically Engineered Protein Nanofibers

10.1101/2021.04.19.440538 ◽

2021 ◽

Author(s):

Anna M Duraj-Thatte ◽

Avinash Manjula Basavanna ◽

Jarod Rutledge ◽

Jing Xia ◽

Shabir Hassan ◽

...

Keyword(s):

3D Printing ◽

Self Assembly ◽

Genetically Engineered ◽

Ambient Conditions ◽

Chemical Induction ◽

Genetic Circuits ◽

3D Print ◽

E Coli ◽

Molecular Components ◽

Living Materials

Living cells have the capability to synthesize molecular components and precisely assemble them from the nanoscale to build macroscopic living functional architectures under ambient conditions. The emerging field of living materials has leveraged microbial engineering to produce materials for various applications, but building 3D structures in arbitrary patterns and shapes has been a major challenge. We set out to develop a new bioink, termed as "microbial ink" that is produced entirely from genetically engineered microbial cells, programmed to perform a bottom-up, hierarchical self-assembly of protein monomers into nanofibers, and further into nanofiber networks that comprise extrudable hydrogels. We further demonstrate the 3D printing of functional living materials by embedding programmed Escherichia coli (E. coli) cells and nanofibers into microbial ink, which can sequester toxic moieties, release biologics and regulate its own cell growth through the chemical induction of rationally designed genetic circuits. This report showcases the advanced capabilities of nanobiotechnology and living materials technology to 3D-print functional living architectures.

Download Full-text

Construction of solvent-dependent self-assembled porous Ni(ii)-coordinated frameworks as effective catalysts for chemical transformation of CO2

RSC Advances ◽

10.1039/c6ra22971a ◽

2016 ◽

Vol 6 (109) ◽

pp. 108010-108016 ◽

Cited By ~ 3

Author(s):

Zhen Zhou ◽

Lu Yang ◽

Yefei Wang ◽

Cheng He ◽

Tao Liu ◽

...

Keyword(s):

Catalytic Activity ◽

Chemical Transformation ◽

Self Assembly ◽

Ambient Conditions ◽

Heterogeneous Catalytic ◽

Self Assembled

Two types of Ni(ii)-based coordinated frameworks have been solvothermally synthesized via solvent driven self-assembly, showing efficient heterogeneous catalytic activity toward cycloaddition of CO2 with epoxides under ambient conditions.

Download Full-text

An azido-bridged [FeII4] grid-like molecule showing spin crossover behaviour

Dalton Transactions ◽

10.1039/d1dt01908b ◽

2021 ◽

Author(s):

Zhilin Guo ◽

Maolin You ◽

Yi-Fei Deng ◽

Qiang Liu ◽

Yin-Shan Meng ◽

...

Keyword(s):

Self Assembly ◽

Spin Crossover ◽

Great Success ◽

Metal Centers ◽

Synthetic Strategy

Supramolecular self-assembly synthetic strategy provides a valid tool to obtain polynuclear Fe(II) complexes containing effective communications between the metal centers and achieve distinct spin crossover behaviour. Despite great success in...

Download Full-text

Bioinspired synthesis of silica nanocups - Polymer-mediated self-assembly of inorganic nanoparticles

Impact ◽

10.21820/23987073.2020.1.38 ◽

2020 ◽

Vol 2020 (1) ◽

pp. 38-40

Author(s):

Ayae Sugawara-Narutaki

Keyword(s):

Liquid Phase ◽

Self Assembly ◽

Associate Professor ◽

Inorganic Nanoparticles ◽

Materials Chemistry ◽

Vast Array ◽

Bioinspired Synthesis ◽

The World ◽

Health Related

Nature oversees a vast array of amazing shapes formed by organisms such as plants, fungi and animals. Some of these manifest as intricate patterns in structures like coral and the nests of insects and birds. Associate Professor Ayae Sugawara-Narutaki, from the Department of Materials Chemistry at Nagoya University, Japan has a particular interest in these patterns. Sugawara-Narutaki's team focuses on research inspired by these self-organised nanostructures to develop nanomaterials for a variety of health-related applications. The ability of these nanomaterials to self-assemble and self-organise in a liquid phase has attracted a great deal of interest from materials scientists the world over.

Download Full-text

Developing a Nanowriter System: Simulation and Experimental Set-Up of a Plasmonic-Based Lens Design

Materials Science Forum ◽

10.4028/www.scientific.net/msf.505-507.1 ◽

2006 ◽

Vol 505-507 ◽

pp. 1-6 ◽

Cited By ~ 4

Author(s):

Chih Kung Lee ◽

C.L. Lin ◽

D.Z. Lin ◽

T.D. Cheng ◽

Ching Kao Chang ◽

...

Keyword(s):

Surface Plasmon ◽

Theoretical Data ◽

Spot Size ◽

Lens Design ◽

Ambient Conditions ◽

Optomechanical System ◽

Dispersion Relationship ◽

Rigorous Coupled Wave ◽

Set Up ◽

The Many

The aim of this article is to introduce a nanowriter system that could lead to a sub-micrometer spot size using a visible light source under ambient conditions. The key component of the system is a focusing optical head, which incorporates a plasmonic-based lens instead of a conventional lens. Based on knowledge of the physical origin of extraordinary transmission and directional beaming, we theorize that the directional beaming phenomenon can be explained simply as a surface plasmon (SP) diffraction along the corrugations as long as the multiple scattering effects are taken into account to modify the dispersion relationship of the surface plasmon. We introduce a Rigorous Coupled Wave Analysis (RCWA) formulation to pursue a precise dispersion relationship needed for the lens design. Comparing the resultant theoretical data between Finite Difference Time Domain (FDTD) simulations and RCWA results, we found good agreement and the many important characteristic parameters needed for an innovative lens design. We also set up a writing-test optomechanical system to examine the photoresist exposure ability of the plasmonic-based lens.

Download Full-text