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

BioScript: programming safe chemistry on laboratories-on-a-chip

This paper introduces BioScript, a domain-specific language (DSL) for programmable biochemistry which executes on emerging microfluidic platforms. The goal of this research is to provide a simple, intuitive, and type-safe DSL that is accessible to life science practitioners. The novel feature of the language is its syntax, which aims to optimize human readability; the technical contributions of the paper include the BioScript type system and relevant portions of its compiler. The type system ensures that certain types of errors, specific to biochemistry, do not occur, including the interaction of chemicals that may be unsafe. The compiler includes novel optimizations that place biochemical operations to execute concurrently on a spatial 2D array platform on the granularity of a control flow graph, as opposed to individual basic blocks. Results are obtained using both a cycle-accurate microfluidic simulator and a software interface to a real-world platform

Asymmetric Synthesis of the C29-C34 Moiety of Fragment A of the Antascomicin B & Thermal Azole Based Claisen Rearrangements

The dissertation describes asymmetric synthesis towards C29-C34 moiety of fragment A of the Antascomicin B and Thermal azole based Claisen rearrangements. In chapter 1, we describes asymmetric synthesis towards C29-C34 moiety of fragment A of the Antascomicin B. The non-immunosuppressant Rapamycin, Ascomycin, and Tacrolimus (FK506), strongly binds with FKBP12, the ligand FKBP12 complexes responsible for immunosuppressive activity. Antascomicin B structurally related to Rapamycin, Ascomycin, and Tacrolimus (FK506), binds strongly to FKBP12, yet does not shown immunosuppressive activity. The ligand FKBP12 binding complexes shown to have potent neuroprotective and neurogenerative properties in mouse models of Parkinson’s disease. The linear synthesis of C29-C34 moiety of fragment A of the Antascomicin B was highlighted through chemical reactions include an Delis Alder reaction, asymmetric transfer hydrogenation (ATH), epoxide ring opening reactions. In chapter 2, we describes novel methodologies of preparing 2-butenyl benzothiazole derivatives using aza-Claisen rearrangement, through N, S-ketene acetals intermediates. The precursor N-allyl-N, S-ketene acetals were prepared in situ from the reaction of N-allyl benzothiazolium salts. N-allyl benzothiazolium salts synthesized by simply alkylated 2-methyl benzothiazole with various allyl bromide derivatives. Despite of the traditional approaches, our proposed synthetic methodology of N, S-ketene acetals that requires only weak base, possesses broad functional group compatibility, and require no cryogenic conditions

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 140

This bibliography lists 306 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1975

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of computation and data movement. We present the "Nine Motifs of Simulation Intelligence", a roadmap for the development and integration of the essential algorithms necessary for a merger of scientific computing, scientific simulation, and artificial intelligence. We call this merger simulation intelligence (SI), for short. We argue the motifs of simulation intelligence are interconnected and interdependent, much like the components within the layers of an operating system. Using this metaphor, we explore the nature of each layer of the simulation intelligence operating system stack (SI-stack) and the motifs therein: (1) Multi-physics and multi-scale modeling; (2) Surrogate modeling and emulation; (3) Simulation-based inference; (4) Causal modeling and inference; (5) Agent-based modeling; (6) Probabilistic programming; (7) Differentiable programming; (8) Open-ended optimization; (9) Machine programming. We believe coordinated efforts between motifs offers immense opportunity to accelerate scientific discovery, from solving inverse problems in synthetic biology and climate science, to directing nuclear energy experiments and predicting emergent behavior in socioeconomic settings. We elaborate on each layer of the SI-stack, detailing the state-of-art methods, presenting examples to highlight challenges and opportunities, and advocating for specific ways to advance the motifs and the synergies from their combinations. Advancing and integrating these technologies can enable a robust and efficient hypothesis-simulation-analysis type of scientific method, which we introduce with several use-cases for human-machine teaming and automated science

The 2019 materials by design roadmap

Advances in renewable and sustainable energy technologies critically depend on our ability to design and realize materials with optimal properties. Materials discovery and design efforts ideally involve close coupling between materials prediction, synthesis and characterization. The increased use of computational tools, the generation of materials databases, and advances in experimental methods have substantially accelerated these activities. It is therefore an opportune time to consider future prospects for materials by design approaches. The purpose of this Roadmap is to present an overview of the current state of computational materials prediction, synthesis and characterization approaches, materials design needs for various technologies, and future challenges and opportunities that must be addressed. The various perspectives cover topics on computational techniques, validation, materials databases, materials informatics, high-throughput combinatorial methods, advanced characterization approaches, and materials design issues in thermoelectrics, photovoltaics, solid state lighting, catalysts, batteries, metal alloys, complex oxides and transparent conducting materials. It is our hope that this Roadmap will guide researchers and funding agencies in identifying new prospects for materials design

Special Libraries, May-June 1945

Volume 36, Issue 5https://scholarworks.sjsu.edu/sla_sl_1945/1004/thumbnail.jp

The compositional and evolutionary logic of metabolism

Metabolism displays striking and robust regularities in the forms of modularity and hierarchy, whose composition may be compactly described. This renders metabolic architecture comprehensible as a system, and suggests the order in which layers of that system emerged. Metabolism also serves as the foundation in other hierarchies, at least up to cellular integration including bioenergetics and molecular replication, and trophic ecology. The recapitulation of patterns first seen in metabolism, in these higher levels, suggests metabolism as a source of causation or constraint on many forms of organization in the biosphere. We identify as modules widely reused subsets of chemicals, reactions, or functions, each with a conserved internal structure. At the small molecule substrate level, module boundaries are generally associated with the most complex reaction mechanisms and the most conserved enzymes. Cofactors form a structurally and functionally distinctive control layer over the small-molecule substrate. Complex cofactors are often used at module boundaries of the substrate level, while simpler ones participate in widely used reactions. Cofactor functions thus act as "keys" that incorporate classes of organic reactions within biochemistry. The same modules that organize the compositional diversity of metabolism are argued to have governed long-term evolution. Early evolution of core metabolism, especially carbon-fixation, appears to have required few innovations among a small number of conserved modules, to produce adaptations to simple biogeochemical changes of environment. We demonstrate these features of metabolism at several levels of hierarchy, beginning with the small-molecule substrate and network architecture, continuing with cofactors and key conserved reactions, and culminating in the aggregation of multiple diverse physical and biochemical processes in cells.Comment: 56 pages, 28 figure