Aalto University

About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.

Lasing in dark and bright modes of a finite-sized plasmonic lattice

Abstract: Lasing at the nanometre scale promises strong light-matter interactions and ultrafast operation. Plasmonic resonances supported by metallic nanoparticles have extremely small mode volumes and high field enhancements, making them an ideal platform for studying nanoscale lasing. At visible frequencies, however, the applicability of plasmon resonances is limited due to strong ohmic and radiative losses. Intriguingly, plasmonic nanoparticle arrays support non-radiative dark modes that offer longer life-times but are inaccessible to far-field radiation. Here, we show lasing both in dark and bright modes of an array of silver nanoparticles combined with optically pumped dye molecules. Linewidths of 0.2 nm at visible wavelengths and room temperature are observed. Access to the dark modes is provided by a coherent out-coupling mechanism based on the finite size of the array. The results open a route to utilize all modes of plasmonic lattices, also the high-Q ones, for studies of strong light-matter interactions, condensation and photon fluids. Plasmonic dark modes are promising candidates for lasing applications. Here, Hakalaet al. show lasing at visible wavelengths in dark and bright modes of an array of silver nanoparticles combined with optically pumped dye molecules, opening up a route to utilization of all modes of plasmonic lattices.

Fundamentals and Recent Developments in Approximate Bayesian Computation

Abstract: Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments. [ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models.]

Production of cellulose nanocrystals using hydrobromic acid and click reactions on their surface

Abstract: Cellulose nanocrystals (CNCs) were prepared by acidic hydrolysis of cotton fibers (Whatman #1 filter paper). In our efforts to select conditions in which the hydrolysis media does not install labile protons on the cellulose crystals, a mineral acid other than sulfuric acid (H2SO4) was used. Furthermore, in our attempts to increase the yields of nanocrystals ultrasonic energy was applied during the hydrolysis reaction. The primary objective was to develop hydrolysis reaction conditions for the optimum and reproducible CNC production. As such, the use of hydrobromic acid (HBr) with the application of sonication as a function of concentration (1.5–4.0 M), temperature (80–100 °C), and time (1–4 h) was examined. Applying sonic energy during the reaction was found to have significant positive effects as far as reproducible high yields are concerned. Overall, the combination of 2.5 M HBr, 100 °C, and 3 h associated with the sonication during the reaction generated the highest nanocrystal yields. In addition to the optimization study three types of surface modifications including TEMPO-mediated oxidation, alkynation, and azidation were used to prepare surface-activated, reactive CNCs. Subsequently, click chemistry was employed for bringing together the modified nanocrystalline materials in a unique regularly packed arrangement demonstrating a degree of molecular control for creating these structures at the nano level.

Geometric Origin of Superfluidity in the Lieb-Lattice Flat Band.

Abstract: The ground state and transport properties of the Lieb lattice flat band in the presence of an attractive Hubbard interaction are considered. It is shown that the superfluid weight can be large even for an isolated and strictly flat band. Moreover the superfluid weight is proportional to the interaction strength and to the quantum metric, a band structure quantity derived solely from the flat-band Bloch functions. These predictions are amenable to verification with ultracold gases and may explain the anomalous behavior of the superfluid weight of high-${T}_{c}$ superconductors.

Business model innovation vs replication: financial performance implications of strategic emphases

Abstract: The purpose of this article is to examine the financial performance implications of a firm's strategic emphases with respect to business model innovation vs replication. It is also examined how the financial performance implications differ between larger and smaller firms. Based on survey data including top managers' reports from approximately 500 firms, the authors analyze the differences in average profitable growth across firms that differ in their strategic orientations. It is found that firms that have a high strategic emphasis on business model innovation as well as a high emphasis on replication exhibit a higher average value of profitable growth than firms that do not strategically emphasize either dimension. Concerning a strategy that puts a high emphasis on business model innovation but low on replication, a difference is found between small and large firms. Large firms with a high emphasis on business model innovation but low on replication exhibit, on average, weaker profitable growth than lar...