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The lack of machine-readable data is a major obstacle in the application of nuclear magnetic resonance (NMR) in artificial intelligence (AI). As a way to overcome this, a procedure for capturing primary NMR spectroscopic instrumental data annotated with rich metadata and publication in a Findable, Accessible, Interoperable and Reusable (FAIR) data repository is described as part of an undergraduate student laboratory experiment in a chemistry department. This couples the techniques of chemical synthesis of a never before made organic ester with illustration of modern data management practices and serves to raise student awareness of how FAIR data might improve research quality and replicability. Searches of the registered metadata are shown, which enable actionable finding and accessing of such data. The potential for re-use of the data in AI applications is discussed.

We present the inscription of narrow-linewidth fiber Bragg gratings (FBGs) into different types of multicore fibers (MCFs) using ultrashort laser pulses and the phase mask technique, which can act as notch filters. Such filters are required, e.g., to suppress light emitted by hydroxyl in the Earth’s upper atmosphere, which disturbs ground-based observation of extraterrestrial objects in the near infrared. However, the inscription into a commercially available seven-core fiber showed a quite large core-to-core deviation of the resonance wavelength of up to 0.45 nm. Two options are presented to overcome this: first, we present the photo-treatment of the FBGs to tune the resonance wavelength, which allows for sufficient resonance shifts. Second, adapted MCFs containing 12 cores, arranged on a circle, are fabricated. For this, two different fabrication procedures were investigated, namely, the mechanical drilling of the preform for a rod-in-tube version as well as a stack-and-draw approach. Both adapted MCFs yielded significant improvements with core-to-core wavelength variations of the FBGs of only about 0.18 nm and 0.11 nm, respectively, sufficient to fulfill the requirements for astronomical filter applications as discussed above.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Introduction Metabolomics is the approach of choice to guide the understanding of biological systems and its molecular intricacies, but compound identification is yet a bottleneck to be overcome. Objective To assay the use of NMRfilter for confidence compound identification based on chemical shift predictions for different datasets. Results We found comparable results using the lead tool COLMAR and NMRfilter. Then, we successfully assayed the use of HMBC to add confidence to the identified compounds. Conclusions NMRfilter is currently under development to become a stand-alone interactive software for high-confidence NMR compound identification and this communication gathers part of its application capabilities.

Laser cooling of a solid is achieved when a coherent laser illuminates the material in the red tail of its absorption spectrum, and the heat is carried out by anti-Stokes fluorescence of the blue-shifted photons. Solid-state laser cooling has been successfully demonstrated in several materials, including rare-earth-doped crystals and glasses. Here we show the net cooling of high-purity Yb-doped silica glass samples that are fabricated with low impurities to reduce their parasitic background loss for fiber laser applications. The non-radiative decay rate of the excited state in Yb ions is very small in these glasses due to the low level of impurities, resulting in near-unity quantum efficiency. We report the measurement of the cooling efficiency as a function of the laser wavelength, from which the quantum efficiency of the Yb-doped silica is calculated. Laser cooling of rare-earth-doped silica may provide a route to vibration-free refrigeration of integrated photonic circuits and quantum sensors to reduce the thermal noise. Here, cooling of high-purity Yb-doped silica to 0.7 K below ambient temperature is demonstrated using sub-optimal laser parameters, and in spite of a substantial extra thermal load.

A large variety of more than sixty Sm3+ doped alumino silicate glass compositions were investigated for their luminescence properties in dependence of their chemical composition. To do so, mainly metaluminous and peralkaline alumino silicate glasses with the network modifiers lithium, sodium, potassium, magnesium, calcium, strontium, barium, yttrium, lanthanum, zinc, and lead were prepared. For some compositions also the effect of fluoride addition, the Al2O3/SiO2 ratio and the substitution of Al2O3 for B2O3 was investigated. A constant Sm3+ doping concentration of 1 × 1020 Sm3+/cm3 was used, which corresponds to about 0.22 mol% Sm2O3. Due to the large quantity of samples, a systematic compositional effect on the Sm3+ emission spectra could be observed: The intensity ratio of the emission peaks at 600 nm and 645 nm is decreased for network modifying ions of larger ionic radii, lower electric field strengths and for higher network modifier concentrations in the glass composition. For exceptionally low network modifier field strengths and concentrations, the emission peak at 645 nm is even stronger than the peak at 600 nm resulting in a more reddish Sm3+ emission in these glasses. The Sm3+ luminescence lifetimes generally decrease with increasing atomic weight, density and refractive index of the glasses. However, peralkaline sodium, potassium, strontium and barium alumino silicate glasses show notably higher luminescence lifetimes than other glass compositions of similar atomic weight. The lifetimes of these glasses are up to 80% higher than their respective metaluminous compositions.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. We introduce a process calculus with a new prefixing operator that allows us to model locally controlled reversibility. Actions can be undone spontaneously, as in other reversible process calculi, or as pairs of concerted actions, where performing a weak action forces undoing of another action. The new operator in its full generality allows us to model out-of-causal order computation, where causes are undone before their effects are undone, which goes beyond what typical reversible calculi can express. However, the core calculus, which uses only the reduced form of the new operator, is well behaved as it satisfied causal consistency. We demonstrate the usefulness of the calculus by modelling the hydration of formaldehyde in water into methanediol, an industrially important reaction, where the creation and breaking of some bonds are examples of locally controlled out-of-causal order computation.

NMR is a mature technique that is well established and adopted in a wide range of research facilities from laboratories to hospitals. This accounts for large amounts of valuable experimental data that may be readily exported into a standard and open format. Yet the publication of these data faces an important issue: Raw data are not made available; instead, the information is slimed down into a string of characters (the list of peaks). Although historical limitations of technology explain this practice, it is not acceptable in the era of Internet. The idea of modernizing the strategy for sharing NMR data is not new, and some repositories exist, but sharing raw data is still not an established practice. Here, we present a powerful toolbox built on recent technologies that runs inside the browser and provides a means to store, share, analyse, and interact with original NMR data. Stored spectra can be streamlined into the publication pipeline, to improve the revision process for instance. The set of tools is still basic but is intended to be extended. The project is open source under the Massachusetts Institute of Technology (MIT) licence.

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Accurate calculation of specific spectral properties for NMR is an important step for molecular structure elucidation. Here we report the development of a novel machine learning technique for accurately predicting chemical shifts of both \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^1\mathrm{H}}$$\end{document}1H and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^{13}\mathrm{C}}$$\end{document}13C nuclei which exceeds DFT-accessible accuracy for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^{13}\mathrm{C}}$$\end{document}13C and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^1\mathrm{H}}$$\end{document}1H for a subset of nuclei, while being orders of magnitude more performant. Our method produces estimates of uncertainty, allowing for robust and confident predictions, and suggests future avenues for improved performance. Electronic supplementary material The online version of this article (10.1186/s13321-019-0374-3) contains supplementary material, which is available to authorized users.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. We suggest an improved software pipeline for mixture analysis. The improvements include combining tandem MS and 2D NMR data for a reliable identification of its constituents in an algorithm based on network analysis aiming for a robust and reliable identification routine. An important part of this pipeline is the use of open-data repositories, although it is not totally reliant on them. The NMR identification step emphasizes robustness and is less sensitive towards changes in data acquisition and processing than existing methods. The process starts with a LC-ESI-MSMS based molecular network dereplication using data from the GNPS collaborative collection. We identify closely related structures by propagating structure elucidation through edges in the network. Those identified compounds are added on top of a candidate list for the following NMR filtering method that predicts HSQC and HMBC NMR data. The similarity of the predicted spectra of the set of closely related structures to the measured spectra of the mixture sample is taken as one indication of the most likely candidates for its compounds. The other indication is the match of the spectra to clusters built by a network analysis from the spectra of the mixture. The sensitivity gap between NMR and MS is anticipated and it will be reflected naturally by the eventual identification of fewer compounds, but with a higher confidence level, after the NMR analysis step. The contributions of the paper are an algorithm combining MS and NMR spectroscopy and a robust nJCH network analysis to explore the complementary aspect of both techniques. This delivers good results even if a perfect computational separation of the compounds in the mixture is not possible. All the scripts will be made available online for users to aid studies such as with plants, marine organisms, and microorganism natural product chemistry and metabolomics as those are the driving force for this project.

openaire: EC/FP7/610446/EU//PAMS We report on first stages toward the formation of a surface-confined metal-organic coordination network (MOCN) by sequential deposition of biphenyl-4,4′-dicarboxylic acid and iron atoms on the surface of a bulk insulator, calcite (10.4). The influence of the deposition order on the structure formation is studied by noncontact atomic force microscopy operated in ultrahigh vacuum at room temperature. It is found that sequential deposition facilitates MOCN formation when the organic linker molecules are first adsorbed on the surface, followed by iron deposition. This observation is explained by first-principles computations, indicating that the metal-molecule interaction dominates over the molecule-molecule interaction on the surface. The observed MOCN islands are elongated in the [010] substrate direction, demonstrating a templating effect of the underlying substrate. This experimental finding is confirmed by calculations suggesting that the MOCN network matches the calcite lattice periodicity in the [010] direction but not in the [421] direction. This work, thus, demonstrates the decisive influence of both deposition order and lattice matching on the formation of an extended MOCN on a bulk insulator surface.

In this contribution we investigate the transversal mode instability behavior of an ytterbium doped commercial 20/400 fiber and obtain 2.9 kW of output power after optimizing the influencing parameters. In this context, we evaluate the influence of the bend diameter and the pump wavelength within the scope of the absorption length and the length of the fiber. Furthermore with a newly developed fiber we report on 4.4 kW of single-mode output power at 40 cm bend diameter.

In previous papers we have introduced a new process calculus inspired by chemical reactions, called the Calculus of Covalent Bonding. The key feature of the calculus was a new prefix operator of the form (s; b), where doing of action b triggers undoing of one of the actions in s. Because of this connection between doing and undoing of actions (or forming and breaking of bonds in a chemical modelling) we called this local reversibility. We have shown that our calculus enables out-of-causal order reversibility. In this paper we demonstrate the Base Excision Repair of DNA, a high-level biological example, using our calculus. We also introduce a software which allows us to check the syntax of processes and to simulate their execution.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Open access article Even though NMR has found countless applications in the field of small molecule characterization, there is no standard file for the NMR data relevant to structure characterization of small molecules. A file format is introduced to associate the NMR parameters extracted from 1D and 2D spectra of organic compounds to the assigned chemical structure. These NMR parameters, which we shall call NMReDATA, include chemical shift values, signal integrals, intensities, multiplicities, scalar coupling constants, lists of 2D correlations, relaxation times and diffusion rates. The file format is an extension of the existing SDF (Structure Data Format), which is compatible with the commonly used MOL format. The association of an NMReDATA file with the raw and spectral data from which it originates constitutes an NMR record. This format is easily readable by humans and computers and provides a simple and efficient way for disseminating results of structural chemistry investigations, automating the verification of published result, and for assisting the constitution of highly needed open-source structural databases.

We present the application of a confocal fluorescence microscope to the analysis of Yb-doped solid-state laser materials, with examples of Yb-doped crystals, photonic crystal fibers and fiber preforms made with different manufacturing processes. Beside the fluorescence lifetime image itself, a microscopic spectral fluorescence emission analysis is presented and spatially resolved emission cross sections are obtained. Doping concentration and its distributions and other laser optical parameters are measured, which help to analyze manufacturing steps. Further properties like photodarkening and saturation are addressed.

We present the amplification of a narrow-bandwidth signal at a wavelength of 1018 nm to a power exceeding 600 W with a stable output polarization state. The beam showed an excellent, nearly diffraction-limited beam quality. The high-power output could be realized using an in-house designed and fabricated fiber with a core-cladding diameter ratio of 32/260, ultra-low NA of 0.041, and ring-up doping. A seed source with high amplified spontaneous emission (ASE) suppression was also required, which was realized by a double-pass pre-amplifier with 13 W output power.

Optomechanical systems, where the mechanical motion of objects is measured and controlled using light, have a huge range of applications, from the metre-scale mirrors of LIGO which detect gravitational waves, to micron scale superconducting systems that can transduce quantum signals. A fascinating addition to this field are free or levitated optomechanical systems, where the oscillator is not physically tethered. We study a variety of nanoparticles which are launched through vacuum (10−8 mbar) and interact with an optical cavity. The centre of mass motion of a nanoparticle can be cooled by the optical cavity field. It is predicted that the quantum ground state of motion can be reached, leaving the particle free to evolve after release from the light field, thus preparing nanoscale matter for quantum interference experiments.

We report on a newly designed and fabricated ytterbium-doped large mode area fiber with an extremely low NA (~0.04) and related systematic investigations on fiber parameters that crucially influence the mode instability threshold. The fiber is used to demonstrate a narrow linewidth, continuous wave, single mode fiber laser amplifier emitting a maximum output power of 3 kW at a wavelength of 1070 nm without reaching the mode-instability threshold. A high slope efficiency of 90 %, excellent beam quality, high temporal stability, and an ASE suppression of 70 dB could be reached with a signal linewidth of only 170 pm.

We introduce a process calculus with a new prefixing operator that allows us to model locally controlled reversibility. Actions can be undone spontaneously, as in other reversible process calculi, or as pairs of concerted actions, where performing a weak action forces undoing of another action. The new operator in its full generality allows us to model out-of-causal order computation, where effects are undone before their causes are undone, which goes beyond what typical reversible calculi can express. However, the core calculus, with a restricted form of the new operator, is well behaved as it satisfied causal consistency. We demonstrate the usefulness of the calculus by modelling the hydration of formaldehyde in water into methanediol, an industrially important reaction, where the creation and breaking of some bonds are examples of locally controlled out-of-causal order computation.

A novel and simple solution doping technique is used to explore the refractive index behavior of Al,P-doped SiO2 in the vicinity of the Al:P-ratio of 1:1 at low doping concentrations (0.4 up to 2.0 mol% Al2O3 and/or P2O5). It is found that even if Al:P = 1:1 is matched precisely, an index increase is observed. This is in contradiction to previous findings in the literature and the already sophisticated models need to be refined in this region. In the proposed model, an incomplete formation of AlPO4 is assumed and solves the contradiction. Furthermore, the presented model can be combined with previous literature models.

We investigate the average power scaling of two diode-pumped Yb-doped fiber amplifiers emitting a diffraction-limited beam. The first fiber under investigation with a core diameter of 30 µm was able to amplify a 10 W narrow linewidth seed laser up to 2.8 kW average output power before the onset of transverse mode instabilities (TMI). A further power scaling was achieved using a second fiber with a smaller core size (23µm), which allowed for a narrow linewidth output power of 3.5 kW limited by stimulated Brillouin scattering (SBS). We mitigated SBS using a spectral broadening mechanism, which allowed us to further increase the output power to 4.3 kW only limited by the available pump power. Up to this power level, a high slope efficiency of 90% with diffraction-limited beam quality and without any sign of TMI or stimulated Raman scattering for a spectral dynamic range of higher than -80 dB was obtained.

Background Contemporary biological research integrates neighboring scientific domains to answer complex questions in fields such as systems biology and drug discovery. This calls for tools that are intuitive to use, yet flexible to adapt to new tasks. Results Bioclipse is a free, open source workbench with advanced features for the life sciences. Version 2.0 constitutes a complete rewrite of Bioclipse, and delivers a stable, scalable integration platform for developers and an intuitive workbench for end users. All functionality is available both from the graphical user interface and from a built-in novel domain-specific language, supporting the scientist in interdisciplinary research and reproducible analyses through advanced visualization of the inputs and the results. New components for Bioclipse 2 include a rewritten editor for chemical structures, a table for multiple molecules that supports gigabyte-sized files, as well as a graphical editor for sequences and alignments. Conclusion Bioclipse 2 is equipped with advanced tools required to carry out complex analysis in the fields of bio- and cheminformatics. Developed as a Rich Client based on Eclipse, Bioclipse 2 leverages on today's powerful desktop computers for providing a responsive user interface, but also takes full advantage of the Web and networked (Web/Cloud) services for more demanding calculations or retrieval of data. The fact that Bioclipse 2 is based on an advanced and widely used service platform ensures wide extensibility, making it easy to add new algorithms, visualizations, as well as scripting commands. The intuitive tools for end users and the extensible architecture make Bioclipse 2 ideal for interdisciplinary and integrative research. Bioclipse 2 is released under the Eclipse Public License (EPL), a flexible open source license that allows additional plugins to be of any license. Bioclipse 2 is implemented in Java and supported on all major platforms; Source code and binaries are freely available at http://www.bioclipse.net.

Background Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE) of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB. Results A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error. Conclusion NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites.

We suggested and developed various components for Computer-Assisted Structure Elucidation (CASE) over the years [1,2]. Our current goal is to integrate these into an easy to use and efficient platform for end users, called SENECA. This is based on Bioclipse [3], an integrated software suite for chemo- and bioinformatics providing plugins for file handling and visualisation of compounds and spectra. The SENECA feature currently comprises the following components and algorithms: • A deterministic structure generator suitable for small chemical spaces. • Simulated Annealing and Genetic Algorithm for random structure walks in large spaces. • Simulation of 13C NMR spectra for ranking results. SENECA is a Bioclipse feature, available via the update site at http://www.ebi.ac.uk/steinbeck-srv/speclipse/net.bioclipse.seneca-updatesite/.