Physics and simulation of transport processes in hybrid organic semiconductor devices

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Physics, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 48-51).Organic semiconductors and nanomaterials promise to potentially form the basis for future efficient and cost-effective large area optoelectronic devices, such as lightemitting diodes and solar cells. Although these materials' amorphous nature allow utilization of cheap, high-throughput manufacturing techniques, it poses a unique challenge: the physics of carrier and excitation transport in amorphous semiconductors is fundamentally different from their crystalline semiconductor counterparts. Excitations remain localized on single molecules or nanocrystals; the drift-diffusion equations, which describe carrier transport in delocalized states near thermal equilibrium, are no longer valid. A computational model for device operation would give researchers a powerful tool to design and improve devices. This work presents a novel one-dimensional discrete model that combines the computational speed of simulations based on the drift-diffusion equations with the accuracy and flexibility of Monte Carlo simulations. The one-dimensional model is shown to be exactly equivalent to the drift-diffusion model in the limits of small applied field, narrow densities of state, and low carrier concentrations. In this limit, the Einstein relation for Brownian motion holds and the transport parameters in the one-dimensional discrete model can be directly estimated from experimentally-measurable quantities. The model is implemented in an object-oriented Python computational framework. Finally, two test cases are numerically studied: an initial, test device with fictitious parameters and a well-known organic light-emitting diode. Preliminary results demonstrate reproduce experimental current-voltage characteristics over a wide range of bias voltages.by Ian Michael Rousseau.S.B

Bond breaking and making in mixed clusters of fullerene and coronene molecules following keV-ion impact

We have performed classical molecular dynamics simulations of 3 keV Ar + $(\mathrm{C}_{24}\mathrm{H}_{12})_n(\mathrm{C}_{60})_{m}$ collisions where $(n,m)=(3,2), (1,4), (9,4)$ and $(2,11)$. The simulated mass spectra of covalently bound reaction products reproduce the main features of the corresponding experimental results reported by Domaracka et al., PCCP, 2018, 20, 15052. The present results support their conclusion that molecular growth is mainly driven by knockout where individual atoms are promptly removed in Rutherford type scattering processes. The so formed highly reactive fragments may then bind with neighboring molecules in the clusters producing a rich variety of growth products extending up to sizes containing several hundreds of atoms, and here we show examples of such structures. In addition, knocked out atoms may be absorbed such that e.g. hydrogenated coronene and fullerene molecules are formed.Comment: 7 pages, 7 figure

Failure of hydrogenation in protecting polycyclic aromatic hydrocarbons from fragmentation

A recent study of soft X-ray absorption in native and hydrogenated coronene cations, C$_{24}$H$_{12+m}^+$ $m=0-7$, led to the conclusion that additional hydrogen atoms protect (interstellar) Polycyclic Aromatic Hydrocarbon (PAH) molecules from fragmentation [Reitsma et al., Phys. Rev. Lett. 113, 053002 (2014)]. The present experiment with collisions between fast (30-200 eV) He atoms and pyrene (C$_{16}$H$_{10+m}^+$, $m=0$, 6, and 16) and simulations without reference to the excitation method suggests the opposite. We find that the absolute carbon-backbone fragmentation cross section does not decrease but increases with the degree of hydrogenation for pyrene molecules.Comment: 10 pages, 5 figure

Profiles of recruits entering army basic training in new zealand

Introduction A high incidence of musculoskeletal injuries is sustained by army recruits during basic training. Describing recruits’ personal, lifestyle, and physical performance characteristics at the entry to training can help identify existing intrinsic risk factors that may predispose some recruits to injury. Identifying modifiable and preventable intrinsic risk factors may contribute to lower recruit injury and associated burdens during the course of basic training. The aim of this study was to therefore describe the profile of New Zealand Army recruits upon entry to basic training using personal, lifestyle, and physical performance characteristics. Methods New Zealand Army male and female recruits from two intakes in the same year were invited to participate. Recruits’ data on personal (sex, age, height, and weight), lifestyle (self-reported responses to the Military Pre-training Questionnaire comprising physical and injury history, diet, alcohol, and smoking status) and physical performance characteristics (2.4-km timed run, weight-bearing dorsiflexion lunge test, and the Y Balance TestTM for lower limb dynamic stability) were collected and analyzed. Results Participants included 248 New Zealand Army recruits: 228 males (91.9%), 20 females (8.1%), average age of 20.3 ± 2.8 years. Findings indicated 30.9% of recruits reported injury in the 12 months prior to training commencing, with 44.8% of those injuries in the lower limbs. Pre-entry alcohol consumption was higher than recommended and 20.1% of recruits identified as current smokers. Recruits who passed the 2.4-km timed run included 53.8% of males and 28.6% of females. Weight-bearing dorsiflexion lunge test performance was within a normal range (right = 10.3 ± 3.3 cm), however limb asymmetry (>1.5 cm) was present with 30.9% of recruits. For the Y Balance TestTM for dynamic lower limb stability, 70% of female recruits had high posterolateral reach asymmetry (8.1 ± 6.0 cm), while normalized composite reach scores were low (right) for male (92.2 ± 8.1%) and female recruits (89.0 ± 7.5%). Conclusions New Zealand Army recruits entering basic training were predominantly active young males, reported few injuries in the previous year, had higher than recommended alcohol consumption and a minority were smokers. The majority of recruits had low aerobic fitness, average ankle dorsiflexion range, and low dynamic lower limb stability. While a number of adverse characteristics identified are potentially modifiable, more research is required to identify an association to musculoskeletal injury risk in New Zealand Army recruits. Describing the profile of recruits entering training, particularly recruits at risk of injury is one of the first steps in injury prevention

Characterization of the non-functional Fas ligand of gld mice

Mice homozygous for either the gld or Ipr mutation develop autoimmune diseases and progressive lymphadenopathy. The Ipr mutation Is characterized by the absence of unctional Fas, whereas gld mice exhibit an inactive FasL due to a point mutation proximal to the extracellular C-terminus. The structural repercussions of this amino acid substitution remain unknown. Here we report that FasL Is expressed at similar levels on the surface of activated T lymphocytes from gld and wild-type mice. Using a polyclonal anti-FasL antibody, Indistinguishable amounts of a 40 kDa protein are detected In both gld and wild-type splenocytes. The molecular model of FasL, based on the known structure of TNF-α, predicts that the Phe→Leu gld mutation is located at the protomer interface which Is close to the FasR Interaction site. We conclude that the gld mutation allows normal FasL biosynthesis, surface expression and ollgomerlzatlon, but induces structural alterations to the Fas binding region leading to the phenotypic changes observe

Climate Change Contributions to Increasing Compound Flooding Risk in New York City

Efforts to meaningfully quantify the changes in coastal compound surge- and rainfall-driven flooding hazard associated with tropical cyclones (TCs) and extratropical cyclones (ETCs) in a warming climate have increased in recent years. Despite substantial progress, however, obtaining actionable details such as the spatially and temporally varying distribution and proximal causes of changing flooding hazard in cities remains a persistent challenge. Here, for the first time, physics-based hydrodynamic flood models driven by rainfall and storm surge simultaneously are used to estimate the magnitude and frequency of compound flooding events. We apply this to the particular case of New York City. We find that sea level rise (SLR) alone will increase the TC and ETC compound flooding hazard more significantly than changes in storm climatology as the climate warms. We also project that the probability of destructive Sandy-like compound flooding will increase by up to 5 times by the end of the century. Our results have strong implications for climate change adaptation in coastal communities

The PaleoJump database for abrupt transitions in past climates

Tipping points (TPs) in Earth’s climate system have been the subject of increasing interest and concern in recent years, given the risk that anthropogenic forcing could cause abrupt, potentially irreversible, climate transitions. Paleoclimate records are essential for identifying past TPs and for gaining a thorough understanding of the underlying nonlinearities and bifurcation mechanisms. However, the quality, resolution, and reliability of these records can vary, making it important to carefully select the ones that provide the most accurate representation of past climates. Moreover, as paleoclimate time series vary in their origin, time spans, and periodicities, an objective, automated methodology is crucial for identifying and comparing TPs. To address these challenges, we introduce the opensource PaleoJump database, which contains a collection of carefully selected, high-resolution records originating in ice cores, marine sediments, speleothems, terrestrial records, and lake sediments. These records describe climate variability on centennial, millennial and longer time scales and cover all the continents and ocean basins. We provide an overview of their spatial distribution and discuss the gaps in coverage. Our statistical methodology includes an augmented Kolmogorov–Smirnov test and Recurrence Quantification Analysis; it is applied here, for illustration purposes, to selected records in which abrupt transitions are automatically detected and the presence of potential tipping elements is investigated. These transitions are shown in the PaleoJump database along with other essential information about the records, including location, temporal scale and resolution, as well as temporal plots. This open-source database represents, therefore, a valuable resource for researchers investigating TPs in past climates

Social network analysis of white-tailed deer scraping behavior: Implications for disease transmission

Host contact structure affects pathogen transmission in host populations, but many measures of host contact do not distinguish contacts that are relevant to pathogen transmission from those that are not. Scrapes are sites for chemical communication by white-tailed deer (Odocoileus virginianus) during the breeding season and potential sites of transmission of prions, the causative agent of chronic wasting disease (CWD). Scrape-related behaviors vary in their probability of transmitting prions to or from the environment, suggesting that behavior be combined with contact structure to better reflect potential heterogeneity in prion transmission at scrapes. We recorded visits and behaviors by deer at scrapes throughout DeSoto National Wildlife Refuge, Nebraska in 2005 and 2006. We recorded 2013 interactions by 169 unique identifiable males and 75 females. Adult males performed the most scrape-related behaviors and spent the most time at scrapes, especially smelling the overhanging branch (70%), smelling the scrape (59%), licking/grasping the overhanging branch (44%), and scraping (36%). We used social network analysis to test the effect of behavior on indirect contact networks among deer at scrapes. By weighting edges based on the frequency and duration of behaviors, we produced networks representing sources of variation in scrape use and compared these networks to evaluate the effects of behavior on network contact structure. Social networks based on scrape-related behavior were highly connected and dependent upon the frequency, duration, and type of behavior exhibited at scrapes (e.g., scraping, interacting with a scrape or overhanging branch, rub-urinating, grazing) as well as the age of the deer. Accounting for contact frequency produced networks with lower variation in contact, but higher ability to facilitate contact among disparate groups. Including behavior when defining edges did not preserve the network properties of simpler measures (i.e., unweighted networks) suggesting that heterogeneity in behaviors that affect transmission probability is important for inferring transmission networks from contact networks. High connectivity through indirect contacts suggests that scrapes may be effective targets for management. Adult male deer had the highest connectivity, suggesting that management strategies focused on reducing their interaction with scrapes through density reduction or behavioral modification could reduce the connectivity of indirect contact networks

Inverse stochastic-dynamic models for high-resolution Greenland ice core records

Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic–dynamic models from δ¹⁸O and dust records of unprecedented, subdecadal temporal resolution. The records stem from the North Greenland Ice Core Project (NGRIP), and we focus on the time interval 59–22 ka b2k. Our model reproduces the dynamical characteristics of both the δ¹⁸O and dust proxy records, including the millennial-scale Dansgaard–Oeschger variability, as well as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i) high-resolution training data, (ii) cubic drift terms, (iii) nonlinear coupling terms between the δ¹⁸O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects