Raman Spectroscopy in Open-World Learning Settings Using the Objectosphere Approach.

Raman spectroscopy, combined with machine learning techniques, holds great promise for many applications as a rapid, sensitive, and label-free identification method. Such approaches perform well when classifying spectra of chemical species that were encountered during the training phase. That is, species that are known to the neural network. However, in real-world settings, such as in clinical applications, there will always be substances whose spectra have not yet been taken. When the neural network encounters these new species during the testing phase, the number of false positives becomes uncontrollable, limiting the usefulness of these techniques, especially in public safety applications. To overcome these barriers, we implemented the recently introduced Entropic Open Set and Objectosphere loss functions. To demonstrate the efficacy and efficiency of this approach, we compiled a database of hyperspectral Raman images of 40 chemical species separating them into three class categorizations. The known class consisted of 20 biologically relevant species comprising amino acids, the ignored class was 10 "irrelevant" species comprising bio-related chemicals, and the never seen before class was 10 various chemical species that the neural network had not seen before. We show that this approach not only enables the network to effectively separate the unknown species while preserving high accuracy on the known ones and reducing false positives but also performs better than the current gold standards in machine learning techniques. This opens the door to using Raman spectroscopy, combined with our novel machine learning algorithm, in a variety of practical applications. Availability and implementation: freely available on the web at https://github.com/BalytskyiJaroslaw/RamanOpenSet.git.

Regioselective Reduction of 1H-1,2,3-Triazole Diesters.

Regioselective reactions can play pivotal roles in synthetic organic chemistry. The reduction of several 1-substituted 1,2,3-triazole 4,5-diesters by sodium borohydride has been found to be regioselective, with the C(5) ester groups being more reactive towards reduction than the C(4) ester groups. The amount of sodium borohydride and reaction time required for reduction varied greatly depending on the N(1)-substituent. The presence of a ß-hydroxyl group on the N(1)-substituent was seen to have a rate enhancing effect on the reduction of the C(5) ester group. The regioselective reduction was attributed to the lower electron densities of the C(5) and the C(5) ester carbonyl carbon of the 1,2,3-triazole, which were further lowered in cases involving intramolecular hydrogen bonding.

Leveling up Organic Semiconductors with Crystal Twisting.

The performance of crystalline organic semiconductors depends on the solid-state structure, especially the orientation of the conjugated components with respect to device platforms. Often, crystals can be engineered by modifying chromophore substituents through synthesis. Meanwhile, dissymetry is necessary for high-tech applications like chiral sensing, optical telecommunications, and data storage. The synthesis of dissymmetric molecules is a labor-intensive exercise that might be undermined because common processing methods offer little control over orientation. Crystal twisting has emerged as a generalizable method for processing organic semiconductors and offers unique advantages, such as patterning of physical and chemical properties and chirality that arises from mesoscale twisting. The precession of crystal orientations can enrich performance because achiral molecules in achiral space groups suddenly become candidates for the aforementioned technologies that require dissymetry.

Self-Patterning Tetrathiafulvalene Crystalline Films.

Tetrathiafulvalene (TTF) crystals grown from the melt are organized as spherulites in which helicoidal fibrils growing radially from the nucleation center twist in concert with one another. Alternating bright and dark concentric bands are apparent when films are viewed between crossed polarizers, indicating an alternating pattern of crystallographic faces exposed at the film surface. Band-dependent reorganization of the TTF crystals was observed during exposure to methanol vapor. Crystalline growth appears on bright bands at the expense of the dark bands. After a 24 h period of exposure to methanol vapor, the original spherulites were completely restructured, and the films comprise isolated, concentric circles of crystallites whose orientations are determined by the initial TTF crystal fibril orientation. While the surface of these outgrowths appears faceted and smooth, cross-sectional SEM images revealed a semiporous inner structure, suggesting solvent-vapor-induced recrystallization. Collectively, these results show that crystal twisting can be used to rhythmically redistribute material. Crystal twisting is a common and often controllable phenomenon independent of molecular or crystal structure and therefore offers a generalizable path to spontaneous pattern formation in a wide range of materials.

Scaffold-Guided Crystallization of Oriented α-FAPbI3 Nanowire Arrays for Solar Cells.

Perovskite nanowire arrays with large surface areas for efficient charge transfer and continuous highly crystalline domains for efficient charge transport exhibit ideal morphologies for solar-cell active layers. Here, we introduce a room temperature two-step method to grow dense, vertical nanowire arrays of formamidinium lead iodide (FAPbI3). PbI2 nanocrystals embedded in the cylindrical nanopores of anodized titanium dioxide scaffolds were converted to FAPbI3 by immersion in a FAI solution for a period of 0.5-30 min. During immersion, FAPbI3 crystals grew vertically from the scaffold surface as nanowires with diameters and densities determined by the underlying scaffold. The presence of butylammonium cations during nanowire growth stabilized the active α polymorph of FAPbI3, precluding the need for a thermal annealing step. Solar cells comprising α-FAPbI3 nanowire arrays exhibited maximum solar conversion efficiencies of >14%. Short-circuit current densities of 22-23 mA cm-2 were achieved, on par with those recorded for the best-performing FAPbI3 solar cells reported to date. Such large photocurrents are attributed to the single-crystalline, low-defect nature of the nanowires and increased interfacial area for photogenerated charge transfer compared with thin films.

Fluorescence microscopy datasets for training deep neural networks.

BACKGROUND: Fluorescence microscopy is an important technique in many areas of biological research. Two factors that limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging and, when imaging live cells, phototoxicity caused by light exposure. Recently developed methods in machine learning are able to greatly improve the signal-to-noise ratio of acquired images. This allows researchers to record images with much shorter exposure times, which in turn minimizes photobleaching and phototoxicity by reducing the dose of light reaching the sample. FINDINGS: To use deep learning methods, a large amount of data is needed to train the underlying convolutional neural network. One way to do this involves use of pairs of fluorescence microscopy images acquired with long and short exposure times. We provide high-quality datasets that can be used to train and evaluate deep learning methods under development. CONCLUSION: The availability of high-quality data is vital for training convolutional neural networks that are used in current machine learning approaches.

Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction.

Background: Structured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high-resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution). Findings: Five complete, freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open-source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods and with newer Bayesian restoration approaches that we are developing. Conclusions: Various methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments are not typically published. Publically available, high-quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data were processed with SIMToolbox, an open-source and freely available software solution for SIM.

Imaging Membrane Curvature inside a FcεRI-Centric Synapse in RBL-2H3 Cells Using TIRF Microscopy with Polarized Excitation.

Total internal reflection fluorescence microscopy with polarized excitation (P-TIRF) can be used to image nanoscale curvature phenomena in live cells. We used P-TIRF to visualize rat basophilic leukemia cells (RBL-2H3 cells) primed with fluorescent anti-dinitrophenyl (anti-DNP) immunoglobulin E (IgE) coming into contact with a supported lipid bilayer containing mobile, monovalent DNP, modeling an immunological synapse. The spatial relationship of the IgE-bound high affinity IgE receptor (FcεRI) to the ratio image of P-polarized excitation and S-polarized excitation was analyzed. These studies help correlate the dynamics of cell surface molecules with the mechanical properties of the plasma membrane during synapse formation.