The Local Emergence and Global Diffusion of Research Technologies: An Exploration of Patterns of Network Formation

Grasping the fruits of "emerging technologies" is an objective of many government priority programs in a knowledge-based and globalizing economy. We use the publication records (in the Science Citation Index) of two emerging technologies to study the mechanisms of diffusion in the case of two innovation trajectories: small interference RNA (siRNA) and nano-crystalline solar cells (NCSC). Methods for analyzing and visualizing geographical and cognitive diffusion are specified as indicators of different dynamics. Geographical diffusion is illustrated with overlays to Google Maps; cognitive diffusion is mapped using an overlay to a map based on the ISI Subject Categories. The evolving geographical networks show both preferential attachment and small-world characteristics. The strength of preferential attachment decreases over time, while the network evolves into an oligopolistic control structure with small-world characteristics. The transition from disciplinary-oriented ("mode-1") to transfer-oriented ("mode-2") research is suggested as the crucial difference in explaining the different rates of diffusion between siRNA and NCSC

On-line Tools for Solar Data Compiled at the Debrecen Observatory and their Extensions with the Greenwich Sunspot Data

The primary task of the Debrecen Heliophysical Observatory (DHO) has been the most detailed, reliable, and precise documentation of the solar photospheric activity since 1958. This long-term effort resulted in various solar catalogs based on ground-based and space-borne observations. A series of sunspot databases and on-line tools were compiled at DHO: the Debrecen Photoheliographic Data (DPD, 1974--), the dataset based on the Michelson Doppler Imager (MDI) of the Solar and Heliospheric Observatory (SOHO) called SOHO/MDI--Debrecen Data (SDD, 1996--2010), and the dataset based on the Helioseismic and Magnetic Imager (HMI) of the Solar Dynamics Observatory (SDO) called SDO/HMI--Debrecen Data (HMIDD, 2010--). User-friendly web-presentations and on-line tools were developed to visualize and search data. As a last step of compilation, the revised version of Greenwich Photoheliographic Results (GPR, 1874--1976) catalog was converted to DPD format, and a homogeneous sunspot database covering more than 140 years was created. The database of images for the GPR era was completed with the full-disc drawings of the Hungarian historical observatories \'Ogyalla and Kalocsa (1872--1919) and with the polarity drawings of Mount Wilson Observatory. We describe the main characteristics of the available data and on-line tools.Comment: 25 pages, 11 figures, accepted for publication in Solar Physic

Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks

The combination of high throughput computation and machine learning has led to a new paradigm in materials design by allowing for the direct screening of vast portions of structural, chemical, and property space. The use of these powerful techniques leads to the generation of enormous amounts of data, which in turn calls for new techniques to efficiently explore and visualize the materials space to help identify underlying patterns. In this work, we develop a unified framework to hierarchically visualize the compositional and structural similarities between materials in an arbitrary material space with representations learned from different layers of graph convolutional neural networks. We demonstrate the potential for such a visualization approach by showing that patterns emerge automatically that reflect similarities at different scales in three representative classes of materials: perovskites, elemental boron, and general inorganic crystals, covering material spaces of different compositions, structures, and both. For perovskites, elemental similarities are learned that reflects multiple aspects of atom properties. For elemental boron, structural motifs emerge automatically showing characteristic boron local environments. For inorganic crystals, the similarity and stability of local coordination environments are shown combining different center and neighbor atoms. The method could help transition to a data-centered exploration of materials space in automated materials design.Comment: 22 + 7 pages, 6 + 5 figure

Scientific Visualization Using the Flow Analysis Software Toolkit (FAST)

Over the past few years the Flow Analysis Software Toolkit (FAST) has matured into a useful tool for visualizing and analyzing scientific data on high-performance graphics workstations. Originally designed for visualizing the results of fluid dynamics research, FAST has demonstrated its flexibility by being used in several other areas of scientific research. These research areas include earth and space sciences, acid rain and ozone modelling, and automotive design, just to name a few. This paper describes the current status of FAST, including the basic concepts, architecture, existing functionality and features, and some of the known applications for which FAST is being used. A few of the applications, by both NASA and non-NASA agencies, are outlined in more detail. Described in the Outlines are the goals of each visualization project, the techniques or 'tricks' used lo produce the desired results, and custom modifications to FAST, if any, done to further enhance the analysis. Some of the future directions for FAST are also described

Scanning Ultrafast Electron Microscopy: A Novel Technique to Probe Photocarrier Dynamics with High Spatial and Temporal Resolutions

The dynamics of photo-excited charge carriers, particularly their transport and interactions with defects and interfaces, play an essential role in determining the performance of a wide range of solar and optoelectronic devices. A thorough understanding of these processes requires tracking the motion of photocarriers in both space and time simultaneously with extremely high resolutions, which poses a significant challenge for previously developed techniques, mostly based on ultrafast optical spectroscopy. Scanning ultrafast electron microscopy (SUEM) is a recently developed photon-pump-electron-probe technique that combines the spatial resolution of scanning electron microscopes (SEM) and the temporal resolution of femtosecond ultrafast lasers. Despite many recent excellent reviews for the ultrafast electron microscopy, we dedicate this article specifically to SUEM, where we review the working principle and contrast mechanisms of SUEM in the secondary-electron-detection mode from a users' perspective and discuss the applications of SUEM to directly image photocarrier dynamics in various materials. Furthermore, we propose future theoretical and experimental directions for better understanding and fully utilizing the SUEM measurements to obtain detailed information about the dynamics of photocarriers. To conclude, we envision the potential of expanding SUEM into a versatile platform for probing photophysical processes beyond photocarrier dynamics.Comment: 23 pages, 6 figure

Charge separation: From the topology of molecular electronic transitions to the dye/semiconductor interfacial energetics and kinetics

Charge separation properties, that is the ability of a chromophore, or a chromophore/semiconductor interface, to separate charges upon light absorption, are crucial characteristics for an efficient photovoltaic device. Starting from this concept, we devote the first part of this book chapter to the topological analysis of molecular electronic transitions induced by photon capture. Such analysis can be either qualitative or quantitative, and is presented here in the framework of the reduced density matrix theory applied to single-reference, multiconfigurational excited states. The qualitative strategies are separated into density-based and wave function-based approaches, while the quantitative methods reported here for analysing the photoinduced charge transfer nature are either fragment-based, global or statistical. In the second part of this chapter we extend the analysis to dye-sensitized metal oxide surface models, discussing interfacial charge separation, energetics and electron injection kinetics from the dye excited state to the semiconductor conduction band states

A Method for Data-Driven Simulations of Evolving Solar Active Regions

We present a method for performing data-driven simulations of solar active region formation and evolution. The approach is based on magnetofriction, which evolves the induction equation assuming the plasma velocity is proportional to the Lorentz force. The simulations of active region coronal field are driven by temporal sequences of photospheric magnetograms from the Helioseismic Magnetic Imager (HMI) instrument onboard the Solar Dynamics Observatory (SDO). Under certain conditions, the data-driven simulations produce flux ropes that are ejected from the modeled active region due to loss of equilibrium. Following the ejection of flux ropes, we find an enhancement of the photospheric horizontal field near the polarity inversion line. We also present a method for the synthesis of mock coronal images based on a proxy emissivity calculated from the current density distribution in the model. This method yields mock coronal images that are somewhat reminiscent of images of active regions taken by instruments such as SDO's Atmospheric Imaging Assembly (AIA) at extreme ultraviolet wavelengths.Comment: Accepted to ApJ; comments/questions related to this article are welcome via e-mail, even after publicatio

Viewpoints: A high-performance high-dimensional exploratory data analysis tool

Scientific data sets continue to increase in both size and complexity. In the past, dedicated graphics systems at supercomputing centers were required to visualize large data sets, but as the price of commodity graphics hardware has dropped and its capability has increased, it is now possible, in principle, to view large complex data sets on a single workstation. To do this in practice, an investigator will need software that is written to take advantage of the relevant graphics hardware. The Viewpoints visualization package described herein is an example of such software. Viewpoints is an interactive tool for exploratory visual analysis of large, high-dimensional (multivariate) data. It leverages the capabilities of modern graphics boards (GPUs) to run on a single workstation or laptop. Viewpoints is minimalist: it attempts to do a small set of useful things very well (or at least very quickly) in comparison with similar packages today. Its basic feature set includes linked scatter plots with brushing, dynamic histograms, normalization and outlier detection/removal. Viewpoints was originally designed for astrophysicists, but it has since been used in a variety of fields that range from astronomy, quantum chemistry, fluid dynamics, machine learning, bioinformatics, and finance to information technology server log mining. In this article, we describe the Viewpoints package and show examples of its usage.Comment: 18 pages, 3 figures, PASP in press, this version corresponds more closely to that to be publishe