147 research outputs found

    General formalism for vibronic Hamiltonians in tetragonal symmetry and beyond

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    We derive general expansion formulas in vibrational coordinates for all bimodal Jahn–Teller and pseudo-Jahn–Teller Hamiltonians in tetragonal symmetry. Symmetry information of all the vibronic Hamiltonian matrix elements is fully carried by up to only 4 eigenvalues of symmetry operators. This problem-to-eigenvalue reduction enables us to handle thousands of vibronic problems in one work. The derived bimodal formulas can be easily extended to cover problems with one or more than two vibrational modes. They lay a solid foundation for future vibronic coupling studies of tetragonal systems. More importantly, the efficient derivation can be applied to handle (pseudo-)Jahn–Teller Hamiltonians for all problems with one principal symmetry axis

    Bayesian optimization with known experimental and design constraints for chemistry applications

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    Optimization strategies driven by machine learning, such as Bayesian optimization, are being explored across experimental sciences as an efficient alternative to traditional design of experiment. When combined with automated laboratory hardware and high-performance computing, these strategies enable next-generation platforms for autonomous experimentation. However, the practical application of these approaches is hampered by a lack of flexible software and algorithms tailored to the unique requirements of chemical research. One such aspect is the pervasive presence of constraints in the experimental conditions when optimizing chemical processes or protocols, and in the chemical space that is accessible when designing functional molecules or materials. Although many of these constraints are known a priori, they can be interdependent, non-linear, and result in non-compact optimization domains. In this work, we extend our experiment planning algorithms Phoenics and Gryffin such that they can handle arbitrary known constraints via an intuitive and flexible interface. We benchmark these extended algorithms on continuous and discrete test functions with a diverse set of constraints, demonstrating their flexibility and robustness. In addition, we illustrate their practical utility in two simulated chemical research scenarios: the optimization of the synthesis of o-xylenyl Buckminsterfullerene adducts under constrained flow conditions, and the design of redox active molecules for flow batteries under synthetic accessibility constraints. The tools developed constitute a simple, yet versatile strategy to enable model-based optimization with known experimental constraints, contributing to its applicability as a core component of autonomous platforms for scientific discovery.Comment: 15 pages, 5 figures (SI with 13 pages, 8 figures

    Optical monitoring of polymerizations in droplets with high temporal dynamic range

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    The ability to optically monitor a chemical reaction and generate an in situ readout is an important enabling technology, with applications ranging from the monitoring of reactions in flow, to the critical assessment step for combinatorial screening, to mechanistic studies on single reactant and catalyst molecules. Ideally, such a method would be applicable to many polymers and not require only a specific monomer for readout. It should also be applicable if the reactions are carried out in microdroplet chemical reactors, which offer a route to massive scalability in combinatorial searches. We describe a convenient optical method for monitoring polymerization reactions, fluorescence polarization anisotropy monitoring, and show that it can be applied in a robotically generated microdroplet. Further, we compare our method to an established optical reaction monitoring scheme, the use of Aggregation-Induced Emission (AIE) dyes, and find the two monitoring schemes offer sensitivity to different temporal regimes of the polymerization, meaning that the combination of the two provides an increased temporal dynamic range. Anisotropy is sensitive at early times, suggesting it will be useful for detecting new polymerization “hits” in searches for new reactivity, while the AIE dye responds at longer times, suggesting it will be useful for detecting reactions capable of reaching higher molecular weights

    A Geologic Play Book for Utica Shale Appalachian Basin Exploration

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    This “Geologic Play Book for Utica Shale Appalachian Basin Exploration” (hereafter referred to as the “Utica Shale Play Book Study” or simply “Study”) represents the results of a two-year research effort by workers in five different states with the financial support of fifteen oil and gas industry partners. The Study was made possible through a coordinated effort between the Appalachian Basin Oil & Natural Gas Research Consortium (AONGRC) and the West Virginia University Shale Research, Education, Policy and Economic Development Center

    Utilizing Technology for Diet and Exercise Change in Complex Chronic Conditions Across Diverse Environments (U-DECIDE): Protocol for a Randomized Controlled Trial

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    BACKGROUND: The metabolic syndrome is common across many complex chronic disease groups. Advances in health technology have provided opportunities to support lifestyle interventions. OBJECTIVE: The purpose of this study is to test the feasibility of a health technology-assisted lifestyle intervention in a patient-led model of care. METHODS: The study is a single-center, 26-week, randomized controlled trial. The setting is specialist kidney and liver disease clinics at a large Australian tertiary hospital. The participants will be adults with a complex chronic condition who are referred for dietetic assessment and display at least one feature of the metabolic syndrome. All participants will receive an individualized assessment and advice on diet quality from a dietitian, a wearable activity monitor, and standard care. Participants randomized to the intervention group will receive access to a suite of health technologies from which to choose, including common base components (text messages) and optional components (online and mobile app–based nutrition information, an online home exercise program, and group-based videoconferencing). Exposure to the optional aspects of the intervention will be patient-led, with participants choosing their preferred level of engagement. The primary outcome will be the feasibility of delivering the program, determined by safety, recruitment rate, retention, exposure uptake, and telehealth adherence. Secondary outcomes will be clinical effectiveness, patient-led goal attainment, treatment fidelity, exposure demand, and participant perceptions. Primary outcome data will be assessed descriptively and secondary outcomes will be assessed using an analysis of covariance. This study will provide evidence on the feasibility of the intervention in a tertiary setting for patients with complex chronic disease exhibiting features of the metabolic syndrome. RESULTS: The study was funded in 2019. Enrollment has commenced and is expected to be completed by June 2022. Data collection and follow up are expected to be completed by December 2022. Results from the analyses based on primary outcomes are expected to be submitted for publication by June 2023. CONCLUSIONS: The study will test the implementation of a health technology–assisted lifestyle intervention in a tertiary outpatient setting for a diverse group of patients with complex chronic conditions. It is novel in that it embeds patient choice into intervention exposure and will inform health service decision-makers in regards to the feasibility of scale and spread of technology-assisted access to care for a broader reach of specialist services. TRIAL REGISTRATION: Australian New Zealand Clinical Trial Registry ACTRN12620001282976; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378337 INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/3755

    Alkylation damage causes MMR-dependent chromosomal instability in vertebrate embryos

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    SN1-type alkylating agents, like N-methyl-N-nitrosourea (MNU) and N-ethyl-N-nitrosourea (ENU), are potent mutagens. Exposure to alkylating agents gives rise to O6-alkylguanine, a modified base that is recognized by DNA mismatch repair (MMR) proteins but is not repairable, resulting in replication fork stalling and cell death. We used a somatic mutation detection assay to study the in vivo effects of alkylation damage on lethality and mutation frequency in developing zebrafish embryos. Consistent with the damage-sensing role of the MMR system, mutant embryos lacking the MMR enzyme MSH6 displayed lower lethality than wild-type embryos after exposure to ENU and MNU. In line with this, alkylation-induced somatic mutation frequencies were found to be higher in wild-type embryos than in the msh6 loss-of-function mutants. These mutations were found to be chromosomal aberrations that may be caused by chromosomal breaks that arise from stalled replication forks. As these chromosomal breaks arise at replication, they are not expected to be repaired by non-homologous end joining. Indeed, Ku70 loss-of-function mutants were found to be equally sensitive to ENU as wild-type embryos. Taken together, our results suggest that in vivo alkylation damage results in chromosomal instability and cell death due to aberrantly processed MMR-induced stalled replication forks

    Bridging the gap between omics and earth system science to better understand how environmental change impacts marine microbes

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    The advent of genomic-, transcriptomic- and proteomic-based approaches has revolutionized our ability to describe marine microbial communities, including biogeography, metabolic potential and diversity, mechanisms of adaptation, and phylogeny and evolutionary history. New interdisciplinary approaches are needed to move from this descriptive level to improved quantitative, process-level understanding of the roles of marine microbes in biogeochemical cycles and of the impact of environmental change on the marine microbial ecosystem. Linking studies at levels from the genome to the organism, to ecological strategies and organism and ecosystem response, requires new modelling approaches. Key to this will be a fundamental shift in modelling scale that represents micro-organisms from the level of their macromolecular components. This will enable contact with omics data sets and allow acclimation and adaptive response at the phenotype level (i.e. traits) to be simulated as a combination of fitness maximization and evolutionary constraints. This way forward will build on ecological approaches that identify key organism traits and systems biology approaches that integrate traditional physiological measurements with new insights from omics. It will rely on developing an improved understanding of ecophysiology to understand quantitatively environmental controls on microbial growth strategies. It will also incorporate results from experimental evolution studies in the representation of adaptation. The resulting ecosystem-level models can then evaluate our level of understanding of controls on ecosystem structure and function, highlight major gaps in understanding and help prioritize areas for future research programs. Ultimately, this grand synthesis should improve predictive capability of the ecosystem response to multiple environmental drivers
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