Morphology of passivating organic ligands around a nanocrystal

Semiconductor nanocrystals are a promising class of materials for a variety of novel optoelectronic devices, since many of their properties, such as the electronic gap and conductivity, can be controlled. Much of this control is achieved via the organic ligand shell, through control of the size of the nanocrystal and the distance to other objects. We here simulate ligand-coated CdSe nanocrystals using atomistic molecular dynamics, allowing for the resolution of novel structural details about the ligand shell. We show that the ligands on the surface can lie flat to form a highly anisotropic 'wet hair' layer as opposed to the 'spiky ball' appearance typically considered. We discuss how this can give rise to a dot-to-dot packing distance of one ligand length since the thickness of the ligand shell is reduced to approximately one-half of the ligand length for the system sizes considered here; these distances imply that energy and charge transfer rates between dots and nearby objects will be enhanced due to the thinner than expected ligand shell. Our model predicts a non-linear scaling of ligand shell thickness as the ligands transition from 'spiky' to 'wet hair'. We verify this scaling using TEM on a PbS nanoarray, confirming that this theory gives a qualitatively correct picture of the ligand shell thickness of colloidal quantum dots.Comment: 17 Pages, 9 Figure

Analysis of a phase variable restriction modification system of the human gut symbiont Bacteroides fragilis

The genomes of gut Bacteroidales contain numerous invertible regions, many of which contain promoters that dictate phase-variable synthesis of surface molecules such as polysaccharides, fimbriae, and outer surface proteins. Here, we characterize a different type of phase-variable system of Bacteroides fragilis, a Type I restriction modification system (R-M). We show that reversible DNA inversions within this R-M locus leads to the generation of eight specificity proteins with distinct recognition sites. In vitro grown bacteria have a different proportion of specificity gene combinations at the expression locus than bacteria isolated from the mammalian gut. By creating mutants, each able to produce only one specificity protein from this region, we identified the R-M recognition sites of four of these S-proteins using SMRT sequencing. Transcriptome analysis revealed that the locked specificity mutants, whether grown in vitro or isolated from the mammalian gut, have distinct transcriptional profiles, likely creating different phenotypes, one of which was confirmed. Genomic analyses of diverse strains of Bacteroidetes from both host-associated and environmental sources reveal the ubiquity of phase-variable R-M systems in this phylum

Simulating energy transfer between nanocrystals and organic semiconductors

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 111-129).Recent trends in renewable energy made silicon based photovoltaics the undisputed leader. Therefore, technologies that enhance, instead of compete with, silicon based solar cells are desirable. One such technology is the use of organic semiconductors and noncrystalline semiconductors for photon up- and down-conversion. However, the understanding of energy transfer in these hybrid systems required to effectively engineer devices is missing. In this thesis, I explore and explain the mechanism of energy transfer between noncrystalline semiconductors and organic semiconductors. Using a combination of density functional calculations, molecular dynamics, and kinetic theory, I have explored the geometry, morphology, electronic structure, and coarse grained kinetics of these system. The result is improved understanding of the transfer mechanism, rate, and the device structure needed for efficient devices. I have also looked at machine learning inspired algorithm for acceleration of density functional theory methods. By training machine learning models on DFT data, a much improved initial guess can be made, greatly accelerating DFT optimizations. Generating and examining this data set also revealed a remarkable degree of structure, that perhaps can be further exploited in the future.by Nadav Geva.Ph. D

Retrospective analysis of efficacy and safety of third-line chemotherapy for metastatic colorectal cancer among elderly patients receiving targeted therapy in early lines

Background/Purpose: About one-half of metastatic colorectal cancer (MCRC) patients are ≥70 years of age. There is uncertainty regarding the benefit patients derive from advanced chemotherapy lines. In this study, we aim to evaluate the efficacy and safety of third-line chemotherapy treatments among MCRC patients. Methods: Consecutive patients 70 years or older at the time of diagnosis of metastatic disease who received third-line chemotherapy at the Tel-Aviv Sourasky Medical Center between the years 2000–2009 were collected. Data on demographics, stage of disease, treatment lines and oncological outcomes were extracted from their medical files. Results: Only 34 out of 63 patients (54%) available patients received third-line treatments. The (median) age of all patients, third-line patients and the remaining patients, were similar (74.5, 74 and 75.3 years, respectively, P = NS). Following third-line treatments, only 9% had a partial response, and the disease was stable in 29% of patients seen. Thirteen weeks is the median duration of third-line treatments. Only three patients had symptomatic relief. Importantly, 15 patients (44%) required dose reduction or treatment delay due to toxicity (neutropenia or thrombocytopenia). The median survival (mOS) is 9 months for patients with first-line treatment, 19 months for second-line treatment and 37 months for third-line treatment (Log Rank < 0.0001). There was a significant association between the number of lines of treatment and the mOS (P = 0.0001). Conclusion: Third-line chemotherapy treatment of elderly MCRC patients was associated with a minor clinical response, a considerable number of side effects, but a longer survival rate. Third-line chemotherapy in fit elderly patients should be pursued, however, protocols must be adjusted before third-line treatment is implemented

Mean field treatment of heterogeneous steady state kinetics

We propose a method to quickly compute steady state populations of species undergoing a set of chemical reactions whose rate constants are heterogeneous. Using an average environment in place of an explicit nearest neighbor configuration, we obtain a set of equations describing a single fluctuating active site in the presence of an averaged bath. We apply this Mean Field Steady State (MFSS) method to a model of H[supscript 2] production on a disordered surface for which the activation energy for the reaction varies from site to site. The MFSS populations quantitatively reproduce the KMC results across the range of rate parameters considered.United States. Department of Energy. Office of Basic Energy Science (BES ER46474

Stacked Ensemble Machine Learning for Range-Separation Parameters

High-throughput virtual materials and drug discovery based on density functional theory has achieved tremendous success in recent decades, but its power on organic semiconducting molecules suffered catastrophically from the self-interaction error until the optimally tuned range-separated hybrid (OT-RSH) exchange-correlation functionals were developed. The accurate but expensive first-principles OT-RSH transitions from a short-range (semi-)local functional to a long-range Hartree-Fock exchange at a distance characterized by the inverse of a molecule-specific, non-empirically-determined range-separation parameter (ω). In the present study, we proposed a promising stacked ensemble machine learning (SEML) model that provides an accelerated alternative of OT-RSH based on system-dependent structural and electronic configurations. We trained ML-ωPBE, the first functional in our series, using a database of 1,970 organic semiconducting molecules with sufficient structural diversity, and assessed its accuracy and efficiency using another 1,956 molecules. Compared with the first-principles OT-ωPBE, our ML-ωPBE reached a mean absolute error of 0:00504a_0^{-1} for the optimal value of ω, reduced the computational cost for the test set by 2.66 orders of magnitude, and achieved comparable predictive powers in various optical properties

A Heterogeneous Kinetics Model for Triplet Exciton Transfer in Solid-State Upconversion

High internal quantum efficiency semiconductor nanocrystal (NC)-based photon upconversion devices are currently based on a single monolayer of active NCs. Devices are therefore limited in their external quantum efficiency based on the low number of photons absorbed. Increasing the number of photons absorbed is expected to increase the upconversion efficiency, yet experimentally increasing the number of layers does not appreciably increase the upconverted light output. We unravel this mystery by combining kinetic modeling and transient photoluminescence spectroscopy. The inherent energetic disorder stemming from the polydispersity of the NCs means that the kinetics are governed by a stochastic transfer matrix. By drawing the rates from a probabilistic distribution and constructing a reaction network with realistic connectivity, we are able to fit complex photoluminescence traces with a very simple model. We use this model to explain the thickness-dependent performance of the upconversion devices and can attribute the reduced efficiencies to the low excitonic diffusivity of the exciton within the NC layers and increased back transfer of the created singlets from the organic annihilator rubrene. We suggest some avenues for overcoming these limitations in future devices.US Department of Energy (Award DE-SC0001088

Automated Device for Multi-Stage Paper-Based Assays Enabled by an Electroosmotic Pumping Valve

This work presents the use of electroosmotic flow generation in porous media in combination with a hydrophobic air gap to create a controllable valve capable of operating in either finite dosing or continuous flow mode, enabling the implementation of multi-step biochemical assays on paper-based devices. A hierarchical superhydrophobic surface placed between two paper pads creates an air gap, keeping the valve nominally closed. To open the valve, a pair of electrodes are activated to generate electroosmotic pressure that overcomes the barrier. The study provides an experimentally validated model describing the governing parameters, and a detailed investigation of the closed valve stability. From these, a straightforward design for a compact and fully automated device is derived. The design is based on paper pads placed on printed circuit boards (PCB), equipped with heating and actuation electrodes and additional power and logic capabilities. The device is applied to the detection of SARS-CoV-2 sequences directly from raw saliva samples, using loop-mediated isothermal amplification (LAMP) requiring sample lysis followed by enzymatic deactivation and sample distribution to multiple amplification pads. Since PCB costs scale favorably with mass production, we believe that this approach could lead to low-cost diagnostic devices with the sensitivity of amplification methods

Organic Electronics: Spatial Mapping of Morphology and Electronic Properties of Air‐Printed Pentacene Thin Films (Adv. Funct. Mater. 25/2014)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107538/1/adfm201470166.pd

Additional file 2: Appendix 2. of Seeking a second medical opinion: composition, reasons and perceived outcomes in Israel

A second medical opinion survey. (DOC 54 kb