We have increased organic field-effect transistor (OFET) NH3 response using tris-(pentafluorophenyl)borane (TPFB) as receptor. OFETs with this additive detect concentrations of 450 ppb v/v, with a limit of detection of 350 ppb, the highest sensitivity yet from semiconductor films; in comparison, when triphenylmethane (TPM) and triphenylborane (TFB) were used as an additive, no obvious improvement of sensitivity was observed. These OFETs also show considerable selectivity with respect to common organic vapors, and stability to storage. Furthermore, excellent memory of exposure was achieved by keeping the exposed devices in a sealed container stored at −30°C, the first such capability demonstrated with OFETs.

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Organic bulk heterojunction solar cells (BHJSCs) are the focus of a burgeoning research effort. While extensive characterization is performed in the course of many reported experimental studies, correlation of performance and physical parameters among studies done in different laboratories is low, pointing out the need to address some aspects of BHJSC active materials that have received relatively little attention. This Perspective describes how a new polymer additive series described by Lobez et al. in this issue of ACS Nano, along with some emerging morphological tools and scanning electronic nanoprobes, can help fill in some of this needed insight. A brief statistical discussion of interstudy correlations and a summary of past work on additives and interfacial studies are presented.

Complement is an important pathway in innate immunity, inflammation, and many disease processes. However, despite its importance, there are few validated mathematical models of complement activation. In this study, we developed an ensemble of experimentally validated reduced order complement models. We combined ordinary differential equations with logical rules to produce a compact yet predictive model of complement activation. The model, which described the lectin and alternative pathways, was an order of magnitude smaller than comparable models in the literature. We estimated an ensemble of model parameters from in vitro dynamic measurements of the C3a and C5a complement proteins. Subsequently, we validated the model on unseen C3a and C5a measurements not used for model training. Despite its small size, the model was surprisingly predictive. Global sensitivity and robustness analysis suggested complement was robust to any single therapeutic intervention. Only the simultaneous knockdown of both C3 and C5 consistently reduced C3a and C5a formation from all pathways. Taken together, we developed a validated mathematical model of complement activation that was computationally inexpensive, and could easily be incorporated into pre-existing or new pharmacokinetic models of immune system function. The model described experimental data, and predicted the need for multiple points of therapeutic intervention to fully disrupt complement activation.

On page 14651, the chemical shift in the 19 F NMR spectrum of free tris(pentafluorophenyl)borane (top 19 F NMR spectrum in scheme 1) was influenced by the water (about 640 ppm) in ordinary C 6 D 6. Therefore, we would like to offer corrected spectra, taken in anhydrous C 6 D 6 (< 10ppm water): The tris(pentafluorophenyl)borane purity is nominally 95% (from Sigma Aldrich), and it was handled in a glove bag filled with dry nitrogen, and stored in dynamic vacuum. Due to the possibility that the 5% impurity may be a water-borane or other adduct and may be exchanging in solution, the peaks in the tris(pentafluorophenyl)borane 19 F NMR spectrum appear broad and slightly shifted. The 19 F NMR peaks for 100% pure tris(pentafluorophenyl)borane in C 6 D 6 are available in the references given below: δ-129.1(o-F),-142.0 (p-F),-160.3 (m-F). The conclusions originally presented regarding response of devices to ammonia are unaffected by this revision; in fact, the spectra provide additional confirmation that the compound used in the published study was indeed anhydrous. Corrected Scheme 1. NH 3-TPFB interaction (blue, hydrogen bonding; red, B-N Interaction) and 19 F NMR Spectra of TPFB and the TPFB-NH 3 complex synthesized and isolated from toluene-chloroform solution

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BackgroundMathematical modeling is a powerful tool to analyze, and ultimately design biochemical networks. However, the estimation of the parameters that appear in biochemical models is a significant challenge. Parameter estimation typically involves expensive function evaluations and noisy data, making it difficult to quickly obtain optimal solutions. Further, biochemical models often have many local extrema which further complicates parameter estimation. Toward these challenges, we developed Dynamic Optimization with Particle Swarms (DOPS), a novel hybrid meta-heuristic that combined multi-swarm particle swarm optimization with dynamically dimensioned search (DDS). DOPS uses a multi-swarm particle swarm optimization technique to generate candidate solution vectors, the best of which is then greedily updated using dynamically dimensioned search.ResultsWe tested DOPS using classic optimization test functions, biochemical benchmark problems and real-world biochemical models. We performed = 25 trials with = 4000 function evaluations per trial, and compared the performance of DOPS with other commonly used meta-heuristics such as differential evolution (DE), simulated annealing (SA) and dynamically dimensioned search (DDS). On average, DOPS outperformed other common meta-heuristics on the optimization test functions, benchmark problems and a real-world model of the human coagulation cascade.ConclusionsDOPS is a promising meta-heuristic approach for the estimation of biochemical model parameters in relatively few function evaluations. DOPS source code is available for download under a MIT license at http://www.varnerlab.org.Electronic supplementary materialThe online version of this article (10.1186/s12918-018-0610-x) contains supplementary material, which is available to authorized users.