Discovery Space Research Articles

Tunable Chemical Disorder in Concentrated Alloys: Defect Physics and Radiation Performance.

The development of advanced structural alloys with performance meeting the requirements of extreme environments in nuclear reactors has been long pursued. In the long history of alloy development, the search for metallic alloys with improved radiation tolerance or increased structural strength has relied on either incorporating alloying elements at low concentrations to synthesize so-called dilute alloys or incorporating nanoscale features to mitigate defects. In contrast to traditional approaches, recent success in synthesizing multicomponent concentrated solid-solution alloys (CSAs), including medium-entropy and high-entropy alloys, has vastly expanded the compositional space for new alloy discovery. Their wide variety of elemental diversity enables tunable chemical disorder and sets CSAs apart from traditional dilute alloys. The tunable electronic structure critically lowers the effectiveness of energy dissipation via the electronic subsystem. The tunable chemical complexity also modifies the scattering mechanisms in the atomic subsystem that control energy transport through phonons. The level of chemical disorder depends substantively on the specific alloying elements, rather than the number of alloying elements, as the disorder does not monotonically increase with a higher number of alloying elements. To go beyond our knowledge based on conventional alloys and take advantage of property enhancement by tuning chemical disorder, this review highlights synergistic effects involving valence electrons and atomic-level and nanoscale inhomogeneity in CSAs composed of multiple transition metals. Understanding of the energy dissipation pathways, deformation tolerance, and structural stability of CSAs can proceed by exploiting the equilibrium and non-equilibrium defect processes at the electronic and atomic levels, with or without microstructural inhomogeneities at multiple length scales. Knowledge of tunable chemical disorder in CSAs may advance the understanding of the substantial modifications in element-specific alloy properties that effectively mitigate radiation damage and control a material's response in extreme environments, as well as overcome strength-ductility trade-offs and provide overarching design strategies for structural alloys.

The search for living worlds and the connection to our cosmic origins

One of the most exciting scientific challenges is to detect Earth-like planets in the habitable zones of other stars in the galaxy and search for evidence of life. During the past 20 years the detection of exoplanets, orbiting stars beyond our own, has moved from science fiction to science fact. From the first handful of gas giants, found through radial velocity studies, detection techniques have increased in sensitivity, finding smaller planets and diverse multi-planet systems. Through enhanced ground-based spectroscopic observations, transit detection techniques and the enormous productivity of the Kepler space mission, the number of confirmed planets has increased to more than 2000. Several space missions, including TESS (NASA), now operational, and PLATO (ESA), will extend the parameter space for exoplanet discovery towards the regime of rocky Earth-like planets and take the census of such bodies in the neighbourhood of the Solar System. The ability to observe and characterise dozens of potentially rocky Earth-like planets now lies within the realm of possibility due to rapid advances in key space and imaging technologies and active studies of potential missions have been underway for a number of years. The latest of these is the Large UV Optical IR space telescope (LUVOIR), one of four flagship mission studies commissioned by NASA in support of the 2020 US Decadal Survey. LUVOIR, if selected, will be of interest to a wide scientific community and will be the only telescope capable of searching for and characterizing a sufficient number of exo-Earths to provide a meaningful answer to the question “Are we alone?”. This contribution is a White Paper that has been submitted in response to the ESA Voyage 2050 Call.

QoS-Based Pattern Recognition Approach for Web Service Discovery: Ar_WSDS

Web service composition requires high levels of integration and reliability of the services involved in its operation, which must meet specific quality criteria to ensure their proper execution and deployment. The discovery and selection of web services currently face optimization problems. Many services might satisfy a requirement with similar quality criteria. Because of this, software developers have to choose the most appropriate services for a given composition, complicated by the rapid increase in providers and services available in the cloud. Service composition also implies coupling according to a composition flow and non-functional requirement criteria. Such requirements make selection and composition a complex task not previously solved in the literature. This paper presents Ar_WSDS, a computational approach for web services discovery and selection in cloud environments, which bases its implementation on the brain’s pattern recognition systematic functioning. This process allows classifying web services through recognition modules created dynamically based on their quality parameters, resulting in a set of web services suitable for a web service composition. This approach allows a solution to the selection problem using less complex tasks. This paper introduces an architectural and procedural definition that provides the web service description with a pattern to recognize and select services using different recognition levels. We simulated our approach and evaluated it using a dataset from the QWS project that offers a set of quality criteria collected from different providers. The web services are recognized and classified using different quality criteria for the composition and each of their services. The results demonstrate the effectiveness of the discovery and selection process compared to other approaches. Furthermore, Ar_WSDS allows us to recognize and filter out web services with ambiguity and similarity in their provider information, a process that minimizes the discovery space for services.

The emergence of imaging mass spectrometry in drug discovery and development: Making a difference by driving decision making

In this special feature article, Steve Castellino and co-authors highlight why matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technology is an important innovation, which can improve and enhance drug discovery and development. Currently, most IMS studies conducted in drug discovery and development focus on the quantitative distribution of drug candidates and their metabolites in animal model tissues. The need to understand the biodistribution of drugs in tissues is not a new concept, but historically, the analytical tools available to achieve this were limited. The introduction of IMS has addressed this gap by providing the ability to quantitatively characterize the distribution of drugs within tissues providing direct evidence of whether the drug is reaching the intended target. Thus, the aim of this special feature article is to share the authors collective experience in designing, conducting, and delivering impactful results using IMS in the preclinical space of pharmaceutical discovery and development. Dr. Stephen Castellino is currently Chief Analytics Officer at Glycopath (Charleston, South Carolina, USA). Dr Nichole M. Lareau is a Senior investigator and Dr Mark Reid Groseclose a Director in the Bioimaging group of GlaxoSmithKline (Collegeville, Pennsylvania, USA).

Insights into the Variation in Bioactivities of Closely Related Streptomyces Strains from Marine Sediments of the Visayan Sea against ESKAPE and Ovarian Cancer.

Marine sediments host diverse actinomycetes that serve as a source of new natural products to combat infectious diseases and cancer. Here, we report the biodiversity, bioactivities against ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) and ovarian cancer, and metabolites variation among culturable actinomycetes isolated from the marine sediments of Visayan Sea, Philippines. We identified 15 Streptomyces species based on a 16S rRNA gene sequence analysis. The crude extracts of 10 Streptomyces species have inhibited the growth of ESKAPE pathogens with minimum inhibitory concentration (MIC) values ranging from 0.312 mg/mL to 20 mg/mL depending on the strain and pathogens targeted. Additionally, ten crude extracts have antiproliferative activity against A2780 human ovarian carcinoma at 2 mg/mL. To highlight, we observed that four phylogenetically identical Streptomyces albogriseolus strains demonstrated variation in antibiotic and anticancer activities. These strains harbored type I and II polyketide synthase (PKS) and non-ribosomal synthetase (NRPS) genes in their genomes, implying that their bioactivity is independent of the polymerase chain reaction (PCR)-detected bio-synthetic gene clusters (BGCs) in this study. Metabolite profiling revealed that the taxonomically identical strains produced core and strain-specific metabolites. Thus, the chemical diversity among these strains influences the variation observed in their biological activities. This study expanded our knowledge on the potential of marine-derived Streptomyces residing from the unexplored regions of the Visayan Sea as a source of small molecules against ESKAPE pathogens and cancer. It also highlights that Streptomyces species strains produce unique strain-specific secondary metabolites; thus, offering new chemical space for natural product discovery.

Small Molecule Microcrystal Electron Diffraction for the Pharmaceutical Industry-Lessons Learned From Examining Over Fifty Samples.

The emerging field of microcrystal electron diffraction (MicroED) is of great interest to industrial researchers working in the drug discovery and drug development space. The promise of being able to routinely solve high-resolution crystal structures without the need to grow large crystals is very appealing. Despite MicroED’s exciting potential, adoption across the pharmaceutical industry has been slow, primarily owing to a lack of access to specialized equipment and expertise. Here we present our experience building a small molecule MicroED service pipeline for members of the pharmaceutical industry. In the past year, we have examined more than fifty small molecule samples submitted by our clients, the majority of which have yielded data suitable for structure solution. We also detail our experience determining small molecule MicroED structures of pharmaceutical interest and offer some insights into the typical experimental outcomes. This experience has led us to conclude that small molecule MicroED adoption will continue to grow within the pharmaceutical industry where it is able to rapidly provide structures inaccessible by other methods.

Online-2D NanoLC-MS for Crude Serum Proteome Profiling: Assessing Sample Preparation Impact on Proteome Composition.

Although current LC-MS technology permits scientists to efficiently screen clinical samples in translational research, e.g., steroids, biogenic amines, and even plasma or serum proteomes, in a daily routine, maintaining the balance between throughput and analytical depth is still a limiting factor. A typical approach to enhance the proteome depth is employing offline two-dimensional (2D) fractionation techniques before reversed-phase nanoLC-MS/MS analysis (1D-nanoLC-MS). These additional sample preparation steps usually require extensive sample manipulation, which could result in sample alteration and sample loss. Here, we present and compare 1D-nanoLC-MS with an automated online-2D high-pH RP × low pH RP separation method for deep proteome profiling using a nanoLC system coupled to a high-resolution accurate-mass mass spectrometer. The proof-of-principle study permitted the identification of ca. 500 proteins with ∼10,000 peptides in 15 enzymatically digested crude serum samples collected from healthy donors in 3 laboratories across Europe. The developed method identified 60% more peptides in comparison with conventional 1D nanoLC-MS/MS analysis with ca. 4 times lower throughput while retaining the quantitative information. Serum sample preparation related changes were revealed by applying unsupervised classification techniques and, therefore, must be taken into account while planning multicentric biomarker discovery and validation studies. Overall, this novel method reduces sample complexity and boosts the number of peptide and protein identifications without the need for extra sample handling procedures for samples equivalent to less than 1 μL of blood, which expands the space for potential biomarker discovery by looking deeper into the composition of biofluids.

Machine learning initialization to accelerate Stokes profile inversions

Context. At present, an exponential growth in scientific data from current and upcoming solar observatories is expected. Most of the data consist of high spatial and temporal resolution cubes of Stokes profiles taken in both local thermodynamic equilibrium (LTE) and non-LTE spectral lines. The analysis of such solar observations requires complex inversion codes. Hence, it is necessary to develop new tools to boost the speed and efficiency of inversions and reduce computation times and costs. Aims. In this work we discuss the application of convolutional neural networks (CNNs) as a tool to advantageously initialize Stokes profile inversions. Methods. To demonstrate the usefulness of CNNs, we concentrate in this paper on the inversion of LTE Stokes profiles. We use observations taken with the spectropolarimeter on board the Hinode spacecraft as a test bench mark. First, we carefully analyse the data with the SIR inversion code using a given initial atmospheric model. The code provides a set of atmospheric models that reproduce the observations well. These models are then used to train a CNN. Afterwards, the same data are again inverted with SIR but using the trained CNN to provide the initial guess atmospheric models for SIR. Results. The CNNs allow us to significantly reduce the number of inversion cycles when used to compute initial guess model atmospheres (‘assisted inversions’), therefore decreasing the computational time for LTE inversions by a factor of two to four. CNNs alone are much faster than assisted inversions, but the latter are more robust and accurate. CNNs also help to automatically cluster pixels with similar physical properties, allowing the association with different solar features on the solar surface, which is useful when inverting huge datasets where completely different regimes are present. The advantages and limitations of machine learning techniques for estimating optimum initial atmospheric models for spectral line inversions are discussed. Finally, we describe a python wrapper for the SIR and DeSIRe codes that allows for the easy setup of parallel inversions. The tool implements the assisted inversion method described in this paper. The parallel wrapper can also be used to synthesize Stokes profiles with the RH code. Conclusions. The assisted inversions can speed up the inversion process, but the efficiency and accuracy of the inversion results depend strongly on the solar scene and the data used for the CNN training. This method (assisted inversions) will not obviate the need for analysing individual events with the utmost care but will provide solar scientists with a much better opportunity to sample large amounts of inverted data, which will undoubtedly broaden the physical discovery space.

Shakespeare’s Statuary Women and the Indoor Theatre’s Discovery Space

This article places three scenes by Shakespeare within a specific architectural history. It reads the statuary female bodies of Desdemona, Hermione, and Imogen as revered and desecrated objects within the niched spaces of the indoor theatre’s discovery space.

Computational Discovery of New 2D Materials Using Deep Learning Generative Models.

Two-dimensional (2D) materials have emerged as promising functional materials with many applications such as semiconductors and photovoltaics because of their unique optoelectronic properties. Although several thousand 2D materials have been screened in existing materials databases, discovering new 2D materials remains challenging. Herein, we propose a deep learning generative model for composition generation combined with a random forest-based 2D materials classifier to discover new hypothetical 2D materials. Furthermore, a template-based element substitution structure prediction approach is developed to predict the crystal structures of a subset of the newly predicted hypothetical formulas, which allows us to confirm their structure stability using DFT calculations. So far, we have discovered 267 489 new potential 2D materials compositions, where 1485 probability scores are more then 0.95. Among them, we have predicted 101 crystal structures and confirmed 92 2D/layered materials by DFT formation energy calculation. Our results show that generative machine learning models provide an effective way to explore the vast chemical design space for new 2D materials discovery.

New horizons in cosmology with spectral distortions of the cosmic microwave background

This Voyage 2050 paper highlights the unique science opportunities using spectral distortions of the cosmic microwave background (CMB). CMB spectral distortions probe many processes throughout the history of the Universe, delivering novel information that complements past, present and future efforts with CMB anisotropy and large-scale structure studies. Precision spectroscopy, possible with existing technology, would not only provide key tests for processes expected within the cosmological standard model but also open an enormous discovery space to new physics. This offers unique scientific opportunities for furthering our understanding of inflation, recombination, reionization and structure formation as well as dark matter and particle physics. A dedicated experimental approach could open this new window to the early Universe in the decades to come, allowing us to turn the long-standing upper distortion limits obtained with COBE/FIRAS some 25 years ago into clear detections of the expected standard distortion signals and also challenge our current understanding of the laws of nature.

Bayesian search for gravitational wave bursts in pulsar timing array data

The nanohertz frequency band explored by pulsar timing arrays provides a unique discovery space for gravitational wave (GW) signals. In addition to signals from anticipated sources, such as those from supermassive black hole binaries, some previously unimagined sources may emit transient GWs (a.k.a. bursts) with unknown morphology. Unmodeled transients are not currently searched for in this frequency band, and they require different techniques from those currently employed. Possible sources of such GW bursts in the nanohertz regime are parabolic encounters of supermassive black holes, cosmic string cusps and kinks, or other, as-yet-unknown phenomena. In this paper we present BayesHopperBurst, a Bayesian search algorithm capable of identifying generic GW bursts by modeling both coherent and incoherent transients as a sum of Morlet–Gabor wavelets. A trans-dimensional reversible jump Markov chain Monte Carlo sampler is used to select the number of wavelets best describing the data. We test BayesHopperBurst on various simulated datasets including different combinations of signals and noise transients. Its capability to run on real data is demonstrated by analyzing data of the pulsar B1855 + 09 from the NANOGrav 9 year dataset. Based on a simulated dataset resembling the NANOGrav 12.5 year data release, we predict that at our most sensitive time–frequency location we will be able to probe GW bursts with a root-sum-squared amplitude higher than ∼5 × 10−11 Hz−1/2, which corresponds to ∼40M ⊙ c 2 emitted in GWs at a fiducial distance of 100 Mpc.

Recent efforts for drug identification from phytochemicals against SARS-CoV-2: Exploration of the chemical space to identify druggable leads

Nature, which remains a central drug discovery pool, is always looked upon to find a putative druggable lead. The natural products and phytochemical derived from plants are essential during a global health crisis. This class represents one of the most practical and promising approaches to decrease pandemic's intensity owing to their therapeutic potential. The present manuscript is therefore kept forth to give the researchers updated information on undergoing research in allied areas of natural product-based drug discovery, particularly for Covid-19 disease. The study briefly shreds evidence from in vitro and in silico researches done so far to find a lead molecule against Covid-19. Following this, we exhaustively explored the concept of chemical space and molecular similarity parameters for the drug discovery about the lead(s) generated from in silico-based studies. The comparison was drawn using FDA-approved anti-infective agents during 2015–2020 using key descriptors to evaluate druglike properties. The outcomes of results were further corroborated using Molecular Dynamics studies which suggested the outcomes in alignment with chemical space ranking. In a nutshell, current research work aims to provide a holistic strategic approach to drug design, keeping in view the identified phytochemicals against Covid-19.

Expanding the drug discovery space with predicted metabolite\u2013target interactions

Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite–host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potential metabolite–target interactions using the Inflammatory Bowel Disease (IBD) cohort dataset of the Human Microbiome Project 2 (HMP2). Using a consensus of multiple machine learning methods, we ranked metabolites based on importance to IBD, followed by virtual ligand-based screening to identify possible human targets and adding evidence from compound assay, differential gene expression, pathway enrichment, and genome-wide association studies. We confirmed known metabolite–target pairs such as nicotinic acid–GPR109a or linoleoyl ethanolamide–GPR119 and inferred interactions of interest including oleanolic acid–GABRG2 and alpha-CEHC–THRB. Eleven metabolites were tested for bioactivity in vitro using human primary cell-types. By expanding the universe of possible microbial metabolite–host protein interactions, we provide multiple drug targets for potential immune-therapies.

Fast Li-Ion Conductivity in Superadamantanoid Lithium Thioborate Halides.

Lithium thioborates are promising fast Li-ion conducting materials, with similar properties to their lithium thiophosphate counterparts that have enabled the development of solid-state Li-ion batteries. By comparison, thioborates have scarcely been developed, however, offering new space for materials discovery. Here we report a new class of lithium thioborate halides that adopt a so-called supertetrahedral adamantanoid structure that houses mobile lithium ions and halide anions within interconnected 3D structural channels. Investigation of the structure using single-crystal XRD, neutron powder diffraction, and neutron PDF reveals significant lithium and halide anion disorder. The phases are non-stoichiometric, adopting slightly varying halide contents within the materials. These new superadamantanoid materials exhibit high ionic conductivities up to 1.4 mS cm-1 , which can be effectively tuned by the polarizability of the halide anion within the channels.

Fast Li‐Ion Conductivity in Superadamantanoid Lithium Thioborate Halides

AbstractLithium thioborates are promising fast Li‐ion conducting materials, with similar properties to their lithium thiophosphate counterparts that have enabled the development of solid‐state Li‐ion batteries. By comparison, thioborates have scarcely been developed, however, offering new space for materials discovery. Here we report a new class of lithium thioborate halides that adopt a so‐called supertetrahedral adamantanoid structure that houses mobile lithium ions and halide anions within interconnected 3D structural channels. Investigation of the structure using single‐crystal XRD, neutron powder diffraction, and neutron PDF reveals significant lithium and halide anion disorder. The phases are non‐stoichiometric, adopting slightly varying halide contents within the materials. These new superadamantanoid materials exhibit high ionic conductivities up to 1.4 mS cm−1, which can be effectively tuned by the polarizability of the halide anion within the channels.

Relative occurrence rates of terrestrial planets orbiting FGK stars

ABSTRACT This paper aims to derive a map of relative planet occurrence rates that can provide constraints on the overall distribution of terrestrial planets around FGK stars. Based on the planet candidates in the Kepler DR25 data release, I first generate a continuous density map of planet distribution using a Gaussian kernel model and correct the geometric factor that the discovery space of a transit event decreases along with the increase of planetary orbital distance. Then, I fit two exponential decay functions of detection efficiency along with the increase of planetary orbital distance and the decrease of planetary radius. Finally, the density map of planet distribution is compensated for the fitted exponential decay functions of detection efficiency to obtain a relative occurrence rate distribution of terrestrial planets. The result shows two regions with planet abundance: one corresponds to planets with radii between 0.5 and 1.5 R⊕ within 0.2 au, and the other corresponds to planets with radii between 1.5 and 3 R⊕ beyond 0.5 au. It also confirms the features that may be caused by atmospheric evaporation: there is a vacancy of planets of sizes between 2.0 and 4.0 R⊕ inside of ∼0.5 au, and a valley with relatively low occurrence rates between 0.2 and 0.5 au for planets with radii between 1.5 and 3.0 R⊕.

Shakespeare, Spectatorship and the Technologies of Performance by Pascale Aebischer

Reviewed by: Shakespeare, Spectatorship and the Technologies of Performance by Pascale Aebischer Susan Bennett Shakespeare, Spectatorship and the Technologies of Performance. By Pascale Aebischer. Cambridge: Cambridge University Press, 2020. Pp. xv + 242. $99.99. Shakespeare, Spectatorship and the Technologies of Performance opens with the story of Emma Rice’s short and controversial stint as the Artistic Director at Shakespeare’s Globe, an appointment that ended in cancellation by technology—Rice’s installation of sound and light equipment apparently a bridge too far at the seventeenth-century replica. Aebischer reads the decision to terminate Rice’s tenure as symptomatic of the fraught character of the UK’s stance toward Shakespeare, caught “between purist nostalgia for a simpler past of human interaction, associated with the Shakespeare brand as a universal guarantor of humanist value, continuity and national pride, and the acceleration of the technological innovation and digital communication that contribute to globalisation” (2). Her book, then, sets out to explore this tension via “a historically grounded spatial theory of technologically mediated spectatorship” (2), and to argue that the ways in which audiences receive, understand, and enjoy performances of Shakespeare’s plays have been fundamentally changed by the technologies exploited in many contemporary productions. Before this introduction and the book proper, however, Aebischer hails her readers through a short injunction, “How to Read this Book” (xv). She wants us to know that, while each of the substantial case studies can be profitably engaged on its own terms, it will be better understood if the introduction is fully digested first. This is good advice. The introduction provides a smart, detailed, and accessible walkthrough of key theoretical debates that range from the perennially knotty problem of liveness to practices of intermedial performance, from affective responses to impacts of spatiality. Aebischer’s meticulous engagement with relevant theory and criticism places the reader on a secure footing from which to investigate her case studies—the first of these, a study of two productions at the indoor Sam Wanamaker Playhouse at Shakespeare’s Globe; the second, a survey of the burgeoning incorporation of digital technologies in live performance during her period of study (2009–16); and the third, an evaluation of live-to-screen broadcasting (a topic that has certainly become all the more commonplace and vital during the extended period of COVID lockdowns). [End Page 317] At the heart of Aebischer’s methodology lies a reanimated and technology-informed version of Robert Weimann’s concepts of locus, the fictional world of the stage and its most powerful occupants, and platea, the liminal areas of the stage and less powerful inhabitants. Added to this spatial dynamic is what she calls “offstage obscenity” (12)—scenes that are “hidden behind the tiring-house façade” or “fully or partially revealed in the discovery space” (19) and intended to pressure the audience to see what it might prefer to avoid. For Aebischer, the obscene “requires a mode of viewing which, with its strong gravitational pull on the spectator, intrinsically demands that spectators be response-able/responsible” (19). Part I offers finely detailed analyses of two Wanamaker productions, both directed by then-Artistic Director Dominic Dromgoole: The Changeling (2015) and The Tempest (2016). The discussion is prefaced by a short chapter on the theater’s architecture and its deployment of candlelight. Aebischer reminds us that these elements are not authentic replications of a seventeenth-century indoor theater, but are “deeply implicated in current theatrical trends” (35). The “sensory environment” (35) of the space shares much, she suggests, with contemporary immersive and site-specific performances. This section also pays careful attention to the relationship between ticket prices and audience experience: “positions within the playhouse determine what is seen, how what is seen is perceived, and what it feels like” (43, emphasis in original). In the case of the theater’s use of candlelight, Aebischer argues that visual and olefactory experiences vary significantly by audience position: for example, someone seated in the upper gallery smells more and sees less than a person in the pit. Aebischer’s reviews of The Changeling and The Tempest—certainly effective for those who know the plays but did not see these specific productions—ably demonstrate that those who...

Expanding organofluorine chemical space: the design of chiral fluorinated isosteres enabled by I(i)/I(iii) catalysis.

Short aliphatic groups are prevalent in bioactive small molecules and play an essential role in regulating physicochemistry and molecular recognition phenomena. Delineating their biological origins and significance have resulted in landmark developments in synthetic organic chemistry: Arigoni's venerable synthesis of the chiral methyl group is a personal favourite. Whilst radioisotopes allow the steric footprint of the native group to be preserved, this strategy was never intended for therapeutic chemotype development. In contrast, leveraging H → F bioisosterism provides scope to complement the chiral, radioactive bioisostere portfolio and to reach unexplored areas of chiral chemical space for small molecule drug discovery. Accelerated by advances in I(i)/I(iii) catalysis, the current arsenal of achiral 2D and 3D drug discovery modules is rapidly expanding to include chiral units with unprecedented topologies and van der Waals volumes. This Perspective surveys key developments in the design and synthesis of short multivicinal fluoroalkanes under the auspices of main group catalysis paradigms.

Australian square kilometre array pathfinder: I. system description

AbstractIn this paper, we describe the system design and capabilities of the Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope at the conclusion of its construction project and commencement of science operations. ASKAP is one of the first radio telescopes to deploy phased array feed (PAF) technology on a large scale, giving it an instantaneous field of view that covers$31\,\textrm{deg}^{2}$at$800\,\textrm{MHz}$. As a two-dimensional array of 36$\times$12 m antennas, with baselines ranging from 22 m to 6 km, ASKAP also has excellent snapshot imaging capability and 10 arcsec resolution. This, combined with 288 MHz of instantaneous bandwidth and a unique third axis of rotation on each antenna, gives ASKAP the capability to create high dynamic range images of large sky areas very quickly. It is an excellent telescope for surveys between 700 and$1800\,\textrm{MHz}$and is expected to facilitate great advances in our understanding of galaxy formation, cosmology, and radio transients while opening new parameter space for discovery of the unknown.