117 research outputs found
Hot-Hole cooling controls the initial ultrafast relaxation in methylammonium lead iodide perovskite
Funding: EPSRC (grants EP/J009016 and EP/L017008) and the European Research Council (grant 321305). IDWS acknowledges a Royal Society Wolfson Research Merit Award.Understanding the initial ultrafast excited state dynamics of methylammonium lead iodide (MAPI) perovskite is of vital importance to enable its fullest utilisation in optoelectronic devices and the design of improved materials. Here we have combined advanced measurements of the ultrafast photoluminescence from MAPI films up to 0.6 eV above the relaxed excited state with cutting-edge advanced non-adiabatic quantum dynamics simulations, to provide a powerful unique insight into the earliest time behaviour in MAPI. Our joint experimental-theoretical approach highlights that the cooling of holes from deep in the valence band to the valence band edge is fast, occurring on a 100-500 fs timescale. Cooling of electrons from high in the conduction band to the conduction band edge, however, is much slower, on the order of 1-10 ps. Density of states calculations indicate that excited states with holes deep in the valence band are greatly favoured upon photoexcitation, and this matches well with the fast (100-500 fs) formation time for the relaxed excited state observed in our ultrafast PL measurements. Consequently we are able to provide a complete observation of the initial excited state evolution in this important prototypical material.Publisher PDFPeer reviewe
Building connectomes using diffusion MRI: why, how and but
Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments
Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities
This paper proposes a novel test of zero pricing errors for the linear factor pricing model when the number of securities, N, can be large relative to the time dimension, T, of the return series. The test is based on Student t tests of individual securities and has a number of advantages over the existing standardised Wald type tests. It allows for non-Gaussianity and general forms of weakly cross correlated errors. It does not require estimation of an invertible error covariance matrix, it is much faster to implement, and is valid even if N is much larger than T. Monte Carlo evidence shows that the proposed test performs remarkably well even when T = 60 and N = 5;000. The test is applied to monthly returns on securities in the S&P 500 at the end of each month in real time, using rolling windows of size 60. Statistically significant evidence against Sharpe-Lintner CAPM and Fama-French three factor models are found mainly during the recent financial crisis. Also we find a significant negative correlation between a twelve-months moving average p-values of the test and excess returns of long/short equity strategies (relative to the return on S&P 500) over the period November 1994 to June 2015, suggesting that abnormal profits are earned during episodes of market inefficiencies
Text Categorization for Aligning Educational Standards
Standard alignment (where standards describing similar concepts are correlated) is a necessary task in providing full access to educational resources. Manual alignment is time consuming and expensive. We propose an automatic alignment system, using machine learning techniques utilizing natural language processing. In this paper we discuss our experiments on text categorization for automatic alignment. We explore the role of relevant vocabulary sets in automatic alignment
Standards Alignment for Metadata Assignment
The research in this paper describes a Machine Learning technique called hierarchical text categorization which is used to solve the problem of finding equivalents from among different state and national education standards. The approach is based on a set of manually aligned standards and utilizes the hierarchical structure present in the standards to achieve a more accurate result. Details of this approach and its evaluation are presented
A Retrospective on Generating & Evaluating Automatic Metadata for Educational Resources: A Holistic Program
Metadata provides a higher-level description of digital library resources and serves as a searchable record for browsing and accessing digital library content. However, manually assigning metadata is a resource-consuming task for which Natural Language Processing (NLP) can provide a solution. This poster coalesces the findings from research and development accomplished across two multi-year digital library metadata generation and evaluation projects and suggests how the lessons learned might benefit digital libraries with the need for high-quality, but efficient metadata assignment for their resources
Hot-Hole cooling controls the initial ultrafast relaxation in methylammonium lead iodide perovskite
Understanding the initial ultrafast excited state dynamics of methylammonium lead iodide (MAPI) perovskite is of vital importance to enable its fullest utilisation in optoelectronic devices and the design of improved materials. Here we have combined advanced measurements of the ultrafast photoluminescence from MAPI films up to 0.6 eV above the relaxed excited state with cutting-edge advanced non-adiabatic quantum dynamics simulations, to provide a powerful unique insight into the earliest time behaviour in MAPI. Our joint experimental-theoretical approach highlights that the cooling of holes from deep in the valence band to the valence band edge is fast, occurring on a 100-500 fs timescale. Cooling of electrons from high in the conduction band to the conduction band edge, however, is much slower, on the order of 1-10 ps. Density of states calculations indicate that excited states with holes deep in the valence band are greatly favoured upon photoexcitation, and this matches well with the fast (100-500 fs) formation time for the relaxed excited state observed in our ultrafast PL measurements. Consequently we are able to provide a complete observation of the initial excited state evolution in this important prototypical material
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