Tuning Electroluminescence from Functionalized SWCNT Networks further into the Near-Infrared

Near-infrared electroluminescence from carbon-based emitters, especially in the second biological window (NIR-II) or at telecommunication wavelengths, is difficult to achieve. Single-walled carbon nanotubes (SWCNTs) have been proposed as a possible solution due to their tunable and narrowband emission in the near-infrared and high charge carrier mobilities. Furthermore, the covalent functionalization of SWCNTs with a controlled number of luminescent sp$^{3}$ defects leads to even more red-shifted photoluminescence with enhanced quantum yields. Here, we demonstrate that by tailoring the binding configuration of the introduced sp$^{3}$ defects and hence tuning their optical trap depth we can generate emission from polymer-sorted (6,5) and (7,5) nanotubes that is mainly occurring in the telecommunication O-band (1260-1360 nm). Networks of these functionalized nanotubes are integrated in ambipolar, light-emitting field-effect transistors to yield the corresponding narrowband near-infrared electroluminescence. Further investigation of the current and carrier density-dependent electro- and photoluminescence spectra enable insights into the impact of different sp$^{3}$ defects on charge transport in networks of functionalized SWCNTs

Absolute Quantification of sp3^3 Defects in Semiconducting Single-Wall Carbon Nanotubes by Raman Spectroscopy

The functionalization of semiconducting single-wall carbon nanotubes (SWCNTs) with luminescent sp$^3$ defects creates red-shifted emission features in the near-infrared and boosts their photoluminescence quantum yields (PLQYs). While multiple synthetic routes for the selective introduction of sp$^3$ defects have been developed, a convenient metric to precisely quantify the number of defects on a SWCNT lattice is not available. Here, we present a direct and simple quantification protocol based on a linear correlation of the integrated Raman D/G+ signal ratios and defect densities as extracted from PLQY measurements. Corroborated by a statistical analysis of single-nanotube emission spectra at cryogenic temperature, this method enables the quantitative evaluation of sp$^3$ defect densities in (6,5) SWCNTs with an error of ±3 defects per micrometer and the determination of oscillator strengths for different defect types. The developed protocol requires only standard Raman spectroscopy and is independent of the defect configuration, dispersion solvent, and nanotube length

Absolute Quantification of sp3^3 Defects in Semiconducting Single-Wall Carbon Nanotubes by Raman Spectroscopy

The functionalization of semiconducting single-wall carbon nanotubes (SWCNTs) with luminescent sp$^3$ defects creates red-shifted emission features in the near-infrared and boosts their photoluminescence quantum yields (PLQYs). While multiple synthetic routes for the selective introduction of sp$^3$ defects have been developed, a convenient metric to precisely quantify the number of defects on a SWCNT lattice is not available. Here, we present a direct and simple quantification protocol based on a linear correlation of the integrated Raman D/G+ signal ratios and defect densities as extracted from PLQY measurements. Corroborated by a statistical analysis of single-nanotube emission spectra at cryogenic temperature, this method enables the quantitative evaluation of sp$^3$ defect densities in (6,5) SWCNTs with an error of ±3 defects per micrometer and the determination of oscillator strengths for different defect types. The developed protocol requires only standard Raman spectroscopy and is independent of the defect configuration, dispersion solvent, and nanotube length

Tetra(peri‐naphthylene)anthracene: A Near‐IR Fluorophore with Four‐Stage Amphoteric Redox Properties

Abstract A novel, benign synthetic strategy towards soluble tetra(peri‐naphthylene)anthracene (TPNA) decorated with triisopropylsilylethynyl substituents has been established. The compound is perfectly stable under ambient conditions in air and features intense and strongly bathochromically shifted UV/vis absorption and emission bands reaching to near‐IR region beyond 900 nm. Cyclic voltammetry measurements revealed four facilitated reversible redox events comprising two oxidations and two reductions. These remarkable experimental findings were corroborated by theoretical studies to identify the TPNA platform a particularly useful candidate for the development of functional near‐IR fluorophores upon appropriate functionalization

Chitosan gated organic transistors printed on ethyl cellulose as a versatile platform for edible electronics and bioelectronics

Edible electronics is an emerging research field targeting electronic devices that can be safely ingested and directly digested or metabolized by the human body. As such, it paves the way to a whole new family of applications, ranging from ingestible medical devices and biosensors, to smart labelling for food quality monitoring and anti-counterfeiting. Being a newborn research field, many challenges need to be addressed to realize fully edible electronic components. In particular, an extended library of edible electronic materials is required, with suitable electronic properties depending on the target device and compatible with large-area printing processes, to allow scalable and cost-effective manufacturing. In this work, we propose a platform for future low-voltage edible transistors and circuits that comprises an edible chitosan gating medium and inkjet printed inert gold electrodes, compatible with low thermal budget edible substrates, such as ethylcellulose. We report the compatibility of the platform, characterized by critical channel features as low as 10 µm, with different inkjet printed carbon-based semiconductors, including biocompatible polymers present in the picograms range per device. A complementary organic inverter is also demonstrated with the same platform as a proof-of-principle logic gate. The presented results offer a promising approach to future low-voltage edible active circuitry, as well as a testbed for non-toxic printable semiconductors

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Large-Scale Screening of a Targeted Enterococcus faecalis Mutant Library Identifies Envelope Fitness Factors

Spread of antibiotic resistance among bacteria responsible for nosocomial and community-acquired infections urges for novel therapeutic or prophylactic targets and for innovative pathogen-specific antibacterial compounds. Major challenges are posed by opportunistic pathogens belonging to the low GC% Gram-positive bacteria. Among those, Enterococcus faecalis is a leading cause of hospital-acquired infections associated with life-threatening issues and increased hospital costs. To better understand the molecular properties of enterococci that may be required for virulence, and that may explain the emergence of these bacteria in nosocomial infections, we performed the first large-scale functional analysis of E. faecalis V583, the first vancomycin-resistant isolate from a human bloodstream infection. E. faecalis V583 is within the high-risk clonal complex 2 group, which comprises mostly isolates derived from hospital infections worldwide. We conducted broad-range screenings of candidate genes likely involved in host adaptation (e.g., colonization and/or virulence). For this purpose, a library was constructed of targeted insertion mutations in 177 genes encoding putative surface or stress-response factors. Individual mutants were subsequently tested for their i) resistance to oxidative stress, ii) antibiotic resistance, iii) resistance to opsonophagocytosis, iv) adherence to the human colon carcinoma Caco-2 epithelial cells and v) virulence in a surrogate insect model. Our results identified a number of factors that are involved in the interaction between enterococci and their host environments. Their predicted functions highlight the importance of cell envelope glycopolymers in E. faecalis host adaptation. This study provides a valuable genetic database for understanding the steps leading E. faecalis to opportunistic virulence

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks