Networking chemical robots for reaction multitasking

The development of the internet of things has led to an explosion in the number of networked devices capable of control and computing. However, whilst common place in remote sensing, these approaches have not impacted chemistry due to difficulty in developing systems flexible enough for experimental data collection. Herein we present a simple and affordable (<$500) chemistry capable robot built with a standard set of hardware and software protocols that can be networked to coordinate many chemical experiments in real time. We demonstrate how multiple processes can be done with two internet connected robots collaboratively, exploring a set of azo-coupling reactions in a fraction of time needed for a single robot, as well as encoding and decoding information into a network of oscillating reactions. The system can also be used to assess the reproducibility of chemical reactions and discover new reaction outcomes using game playing to explore a chemical space

A nanomaterials discovery robot for the Darwinian evolution of shape programmable gold nanoparticles

The fabrication of nanomaterials from the top-down gives precise structures but it is costly, whereas bottom-up assembly methods are found by trial and error. Nature evolves materials discovery by refining and transmitting the blueprints using DNA mutations autonomously. Genetically inspired optimisation has been used in a range of applications, from catalysis to light emitting materials, but these are not autonomous, and do not use physical mutations. Here we present an autonomously driven materials-evolution robotic platform that can reliably optimise the conditions to produce gold-nanoparticles over many cycles, discovering new synthetic conditions for known nanoparticle shapes using the opto-electronic properties as a driver. Not only can we reliably discover a method, encoded digitally to synthesise these materials, we can seed in materials from preceding generations to engineer more sophisticated architectures. Over three independent cycles of evolution we show our autonomous system can produce spherical nanoparticles, rods, and finally octahedral nanoparticles by using our optimized rods as seeds

A universal system for digitization and automatic execution of the chemical synthesis literature

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 direct access to the literature through natural language processing. Here we show an extendable chemical execution architecture that can be populated by automatically reading the literature, leading to a universal autonomous workflow. The robotic synthesis code can be corrected in natural language without any programming knowledge and, because of the standard, is hardware independent. This chemical code can then be combined with a graph describing the hardware modules and compiled into platform-specific, low-level robotic instructions for execution. 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

The Radiated Energy Budget of Chromospheric Plasma in a Major Solar Flare Deduced From Multi-Wavelength Observations

This paper presents measurements of the energy radiated by the lower solar atmosphere, at optical, UV, and EUV wavelengths, during an X-class solar flare (SOL2011-02-15T01:56) in response to an injection of energy assumed to be in the form of nonthermal electrons. Hard X-ray observations from RHESSI were used to track the evolution of the parameters of the nonthermal electron distribution to reveal the total power contained in flare accelerated electrons. By integrating over the duration of the impulsive phase, the total energy contained in the nonthermal electrons was found to be $>2\times10^{31}$ erg. The response of the lower solar atmosphere was measured in the free-bound EUV continua of H I (Lyman), He I, and He II, plus the emission lines of He II at 304\AA\ and H I (Ly$\alpha$) at 1216\AA\ by SDO/EVE, the UV continua at 1600\AA\ and 1700\AA\ by SDO/AIA, and the WL continuum at 4504\AA, 5550\AA, and 6684\AA, along with the Ca II H line at 3968\AA\ using Hinode/SOT. The summed energy detected by these instruments amounted to $\sim3\times10^{30}$ erg; about 15% of the total nonthermal energy. The Ly$\alpha$ line was found to dominate the measured radiative losses. Parameters of both the driving electron distribution and the resulting chromospheric response are presented in detail to encourage the numerical modelling of flare heating for this event, to determine the depth of the solar atmosphere at which these line and continuum processes originate, and the mechanism(s) responsible for their generation.Comment: 14 pages, 18 figures. Accepted for publication in Astrophysics Journa

A modular programmable inorganic cluster discovery robot for the discovery and synthesis of polyoxometalates

The exploration of complex multicomponent 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 that is modular in terms of both hardware and software and is 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 that allows the easy repeat synthesis of the clusters. Among the many species identified in this work, the most significant is the discovery of a novel, purely inorganic W24FeIII–superoxide cluster formed under ambient conditions. The modular wheel platform was employed to undertake two chemical space explorations, producing compounds 1–4: (C2H8N)10Na2[H6Fe(O2)W24O82] (1, {W24Fe}), (C2H8N)72Na16[H16Co8W200O660(H2O)40] (2, {W200Co8}), (C2H8N)72Na16[H16Ni8W200O660(H2O)40] (3, {W200Ni8}), and (C2H8N)14[H26W34V4O130] (4, {W34V4}), along with many other known species, such as simple Keggin clusters and 1D {W11M2+} chains

The AU Microscopii Debris Disk: Multiwavelength Imaging and Modeling

(abridged) Debris disks around main sequence stars are produced by the erosion and evaporation of unseen parent bodies. AU Microscopii (GJ 803) is a compelling object to study in the context of disk evolution across different spectral types, as it is an M dwarf whose near edge-on disk may be directly compared to that of its A5V sibling beta Pic. We resolve the disk from 8-60 AU in the near-IR JHK' bands at high resolution with the Keck II telescope and adaptive optics, and develop a novel data reduction technique for the removal of the stellar point spread function. The point source detection sensitivity in the disk midplane is more than a magnitude less sensitive than regions away from the disk for some radii. We measure a blue color across the near-IR bands, and confirm the presence of substructure in the inner disk. Some of the structural features exhibit wavelength-dependent positions. The disk architecture and characteristics of grain composition are inferred through modeling. We approach the modeling of the dust distribution in a manner that complements previous work. Using a Monte Carlo radiative transfer code, we compare a relatively simple model of the distribution of porous grains to a broad data set, simultaneously fitting to midplane surface brightness profiles and the spectral energy distribution. Our model confirms that the large-scale architecture of the disk is consistent with detailed models of steady-state grain dynamics. Here, a belt of parent bodies from 35-40 AU is responsible for producing dust that is then swept outward by the stellar wind and radiation pressures. We infer the presence of very small grains in the outer region, down to sizes of ~0.05 micron. These sizes are consistent with stellar mass-loss rates Mdot_* << 10^2 Mdot_sun.Comment: ApJ accepted, 56 pages, preprint style. Version in emulateapj with high-resolution figures available at http://tinyurl.com/y6ent

Evaporation and condensation of spherical interstellar clouds. Self-consistent models with saturated heat conduction and cooling

Shortened version: The fate of IS clouds embedded in a hot tenuous medium depends on whether the clouds suffer from evaporation or whether material condensates onto them. Analytical solutions for the rate of evaporative mass loss from an isolated spherical cloud embedded in a hot tenuous gas are deduced by Cowie & McKee (1977). In order to test the validity of the analytical results for more realistic IS conditions the full hydrodynamical equations must be treated. Therefore, 2D numerical simulations of the evolution of IS clouds %are performed with different internal density structures and surrounded by a hot plasma reservoir. Self-gravity, interstellar heating and cooling effects and heat conduction by electrons are added. Classical thermal conductivity of a fully ionized hydrogen plasma and saturated heat flux are considered. Using pure hydrodynamics and classical heat flux we can reproduce the analytical results. Heat flux saturation reduces the evaporation rate by one order of magnitude below the analytical value. The evolution changes totally for more realistic conditions when interstellar heating and cooling effects stabilize the self-gravity. Evaporation then turns into condensation, because the additional energy by heat conduction can be transported away from the interface and radiated off efficiently from the cloud's inner parts. I.e. that the saturated heat flux consideration is inevitable for IS clouds embedded in hot tenuous gas. Various consequences are discussed in the paper.Comment: 16 pages, 24 figures, accepted in Astronomy and Astrophysic

An artificial intelligence enabled chemical synthesis robot for exploration and optimization of nanomaterials

We present an autonomous chemical synthesis robot for the exploration, discovery, and optimization of nanostructures driven by real-time spectroscopic feedback, theory, and machine learning algorithms that control the reaction conditions and allow the selective templating of reactions. This approach allows the transfer of materials as seeds between cycles of exploration, opening the search space like gene transfer in biology. The open-ended exploration of the seed-mediated multistep synthesis of gold nanoparticles (AuNPs) via in-line ultraviolet-visible characterization led to the discovery of five categories of nanoparticles by only performing ca. 1000 experiments in three hierarchically linked chemical spaces. The platform optimized nanostructures with desired optical properties by combining experiments and extinction spectrum simulations to achieve a yield of up to 95%. The synthetic procedure is outputted in a universal format using the chemical description language (χDL) with analytical data to produce a unique digital signature to enable the reproducibility of the synthesis

Organic synthesis in a modular robotic system driven by a chemical programming language

The synthesis of complex organic compounds is largely a manual process that is often incompletely documented. To address these shortcomings, we developed an abstraction that maps commonly reported methodological instructions into discrete steps amenable to automation. These unit operations were implemented in a modular robotic platform using a chemical programming language which formalizes and controls the assembly of the molecules. We validated the concept by directing the automated system to synthesize three pharmaceutical compounds, Nytol, rufinamide, and sildenafil, without any human intervention. Yields and purities of products and intermediates were comparable to or better than those achieved manually. The syntheses are captured as digital code that can be published, versioned, and transferred flexibly between platforms with no modification, thereby greatly enhancing reproducibility and reliable access to complex molecules

Arterial spin labelling reveals an abnormal cerebral perfusion pattern in Parkinson's disease

There is a need for objective imaging markers of Parkinson's disease status and progression. Positron emission tomography and single photon emission computed tomography studies have suggested patterns of abnormal cerebral perfusion in Parkinson's disease as potential functional biomarkers. This study aimed to identify an arterial spin labelling magnetic resonance-derived perfusion network as an accessible, non-invasive alternative. We used pseudo-continuous arterial spin labelling to measure cerebral grey matter perfusion in 61 subjects with Parkinson's disease with a range of motor and cognitive impairment, including patients with dementia and 29 age- and sex-matched controls. Principal component analysis was used to derive a Parkinson's disease-related perfusion network via logistic regression. Region of interest analysis of absolute perfusion values revealed that the Parkinson's disease pattern was characterized by decreased perfusion in posterior parieto-occipital cortex, precuneus and cuneus, and middle frontal gyri compared with healthy controls. Perfusion was preserved in globus pallidus, putamen, anterior cingulate and post- and pre-central gyri. Both motor and cognitive statuses were significant factors related to network score. A network approach, supported by arterial spin labelling-derived absolute perfusion values may provide a readily accessible neuroimaging method to characterize and track progression of both motor and cognitive status in Parkinson's diseas