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Showing papers by "Aalto University published in 2015"


Journal ArticleDOI
TL;DR: An overview of the key aspects of graphene and related materials, ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries are provided.
Abstract: We present the science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems, targeting an evolution in technology, that might lead to impacts and benefits reaching into most areas of society. This roadmap was developed within the framework of the European Graphene Flagship and outlines the main targets and research areas as best understood at the start of this ambitious project. We provide an overview of the key aspects of graphene and related materials (GRMs), ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries. We also define an extensive list of acronyms in an effort to standardize the nomenclature in this emerging field.

2,560 citations


Journal ArticleDOI
TL;DR: In this paper, the authors examined the existing literature in the analysis of life cycle costs of utility-scale electricity storage systems, providing an updated database for the cost elements (capital costs, operational and maintenance costs, and replacement costs).
Abstract: Large-scale deployment of intermittent renewable energy (namely wind energy and solar PV) may entail new challenges in power systems and more volatility in power prices in liberalized electricity markets. Energy storage can diminish this imbalance, relieving the grid congestion, and promoting distributed generation. The economic implications of grid-scale electrical energy storage technologies are however obscure for the experts, power grid operators, regulators, and power producers. A meticulous techno-economic or cost-benefit analysis of electricity storage systems requires consistent, updated cost data and a holistic cost analysis framework. To this end, this study critically examines the existing literature in the analysis of life cycle costs of utility-scale electricity storage systems, providing an updated database for the cost elements (capital costs, operational and maintenance costs, and replacement costs). Moreover, life cycle costs and levelized cost of electricity delivered by electrical energy storage is analyzed, employing Monte Carlo method to consider uncertainties. The examined energy storage technologies include pumped hydropower storage, compressed air energy storage (CAES), flywheel, electrochemical batteries (e.g. lead–acid, NaS, Li-ion, and Ni–Cd), flow batteries (e.g. vanadium-redox), superconducting magnetic energy storage, supercapacitors, and hydrogen energy storage (power to gas technologies). The results illustrate the economy of different storage systems for three main applications: bulk energy storage, T&D support services, and frequency regulation.

1,279 citations


Journal ArticleDOI
Peter A. R. Ade1, Nabila Aghanim2, Zeeshan Ahmed3, Randol W. Aikin4  +354 moreInstitutions (75)
TL;DR: Strong evidence for dust and no statistically significant evidence for tensor modes is found and various model variations and extensions are probe, including adding a synchrotron component in combination with lower frequency data, and find that these make little difference to the r constraint.
Abstract: We report the results of a joint analysis of data from BICEP2/Keck Array and Planck. BICEP2 and Keck Array have observed the same approximately 400 deg2 patch of sky centered on RA 0h, Dec. −57.5deg. The combined maps reach a depth of 57 nK deg in Stokes Q and U in a band centered at 150 GHz. Planck has observed the full sky in polarization at seven frequencies from 30 to 353 GHz, but much less deeply in any given region (1.2 μK deg in Q and U at 143 GHz). We detect 150×353 cross-correlation in B-modes at high significance. We fit the single- and cross-frequency power spectra at frequencies above 150 GHz to a lensed-ΛCDM model that includes dust and a possible contribution from inflationary gravitational waves (as parameterized by the tensor-to-scalar ratio r). We probe various model variations and extensions, including adding a synchrotron component in combination with lower frequency data, and find that these make little difference to the r constraint. Finally we present an alternative analysis which is similar to a map-based cleaning of the dust contribution, and show that this gives similar constraints. The final result is expressed as a likelihood curve for r, and yields an upper limit r0.05<0.12 at 95% confidence. Marginalizing over dust and r, lensing B-modes are detected at 7.0σ significance.

1,255 citations


Journal ArticleDOI
TL;DR: This review looks at the concepts and state-of-the-art concerning the strong coupling of surface plasmon-polariton modes to states associated with quantum emitters such as excitons in J-aggregates, dye molecules and quantum dots.
Abstract: In this review we look at the concepts and state-of-the-art concerning the strong coupling of surface plasmon-polariton modes to states associated with quantum emitters such as excitons in J-aggregates, dye molecules and quantum dots. We explore the phenomenon of strong coupling with reference to a number of examples involving electromagnetic fields and matter. We then provide a concise description of the relevant background physics of surface plasmon polaritons. An extensive overview of the historical background and a detailed discussion of more recent relevant experimental advances concerning strong coupling between surface plasmon polaritons and quantum emitters is then presented. Three conceptual frameworks are then discussed and compared in depth: classical, semi-classical and fully quantum mechanical; these theoretical frameworks will have relevance to strong coupling beyond that involving surface plasmon polaritons. We conclude our review with a perspective on the future of this rapidly emerging field, one we are sure will grow to encompass more intriguing physics and will develop in scope to be of relevance to other areas of science.

1,190 citations


Journal ArticleDOI
TL;DR: In this paper, the authors review different approaches, technologies, and strategies to manage large-scale schemes of variable renewable electricity such as solar and wind power, considering both supply and demand side measures.
Abstract: The paper reviews different approaches, technologies, and strategies to manage large-scale schemes of variable renewable electricity such as solar and wind power. We consider both supply and demand side measures. In addition to presenting energy system flexibility measures, their importance to renewable electricity is discussed. The flexibility measures available range from traditional ones such as grid extension or pumped hydro storage to more advanced strategies such as demand side management and demand side linked approaches, e.g. the use of electric vehicles for storing excess electricity, but also providing grid support services. Advanced batteries may offer new solutions in the future, though the high costs associated with batteries may restrict their use to smaller scale applications. Different “P2Y”-type of strategies, where P stands for surplus renewable power and Y for the energy form or energy service to which this excess in converted to, e.g. thermal energy, hydrogen, gas or mobility are receiving much attention as potential flexibility solutions, making use of the energy system as a whole. To “functionalize” or to assess the value of the various energy system flexibility measures, these need often be put into an electricity/energy market or utility service context. Summarizing, the outlook for managing large amounts of RE power in terms of options available seems to be promising.

1,180 citations


Proceedings Article
07 Dec 2015
TL;DR: This work builds on top of the Ladder network proposed by Valpola which is extended by combining the model with supervision and shows that the resulting model reaches state-of-the-art performance in semi-supervised MNIST and CIFAR-10 classification in addition to permutation-invariant MNIST classification with all labels.
Abstract: We combine supervised learning with unsupervised learning in deep neural networks. The proposed model is trained to simultaneously minimize the sum of supervised and unsupervised cost functions by backpropagation, avoiding the need for layer-wise pre-training. Our work builds on top of the Ladder network proposed by Valpola [1] which we extend by combining the model with supervision. We show that the resulting model reaches state-of-the-art performance in semi-supervised MNIST and CIFAR-10 classification in addition to permutation-invariant MNIST classification with all labels.

1,162 citations


Journal ArticleDOI
TL;DR: In this paper, the authors demonstrate the relevance and robustness of the theory of planned behavior in the prediction of business start-up intentions and subsequent behavior based on longitudinal survey data from the adult population in Austria and Finland.
Abstract: This analysis demonstrates the relevance and robustness of the theory of planned behavior in the prediction of business start-up intentions and subsequent behavior based on longitudinal survey data (2011 and 2012; n = 969) from the adult population in Austria and Finland. By doing so, the study addresses two weaknesses in current research: the limited scope of samples used in the majority of prior studies and the scarcity of investigations studying the translation of entrepreneurial intentions into behavior. The paper discusses conceptual and methodological issues related to studying the intention–behavior relationship and outlines avenues for future research.

881 citations



Journal ArticleDOI
TL;DR: A survey of the literature for ca. one thousand B-site substituted perovskite oxides can be found in this article, together with their electronic and magnetic properties and properties.

815 citations


Journal ArticleDOI
TL;DR: This work presents CSI:FingerID, which combines fragmentation tree computation and machine learning for searching molecular structure databases using tandem MS data of small molecules, and is shown to improve on the competing methods for computational metabolite identification by a considerable margin.
Abstract: Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin.

598 citations


Journal ArticleDOI
23 Jul 2015-Nature
TL;DR: This work presents a general method of folding arbitrary polygonal digital meshes in DNA that readily produces structures that would be very difficult to realize using previous approaches.
Abstract: It was suggested more than thirty years ago that Watson-Crick base pairing might be used for the rational design of nanometre-scale structures from nucleic acids. Since then, and especially since the introduction of the origami technique, DNA nanotechnology has enabled increasingly more complex structures. But although general approaches for creating DNA origami polygonal meshes and design software are available, there are still important constraints arising from DNA geometry and sense/antisense pairing, necessitating some manual adjustment during the design process. Here we present a general method of folding arbitrary polygonal digital meshes in DNA that readily produces structures that would be very difficult to realize using previous approaches. The design process is highly automated, using a routeing algorithm based on graph theory and a relaxation simulation that traces scaffold strands through the target structures. Moreover, unlike conventional origami designs built from close-packed helices, our structures have a more open conformation with one helix per edge and are therefore stable under the ionic conditions usually used in biological assays.

Journal ArticleDOI
TL;DR: In this paper, the authors organize the last 10 years of empirical work around 10 main themes: research design, team inputs, team virtuality, technology, globalization, leadership, mediators and moderators, trust, outcomes, and ways to enhance virtual team success.

Journal ArticleDOI
TL;DR: It is demonstrated that efficiencies above 22% can be reached, even in thick interdigitated back-contacted cells, where carrier transport is very sensitive to front surface passivation, meaning that the surface recombination issue has truly been solved and black silicon solar cells have real potential for industrial production.
Abstract: A power conversion efficiency of 22% is achieved in black silicon back-contacted solar cells through passivation of the nanostructured surface by a conformal alumina layer.

01 Jan 2015
TL;DR: MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions.
Abstract: Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne.


Journal ArticleDOI
TL;DR: In this article, the physics, design principles, and classification of thin perfect absorbers are reviewed, and several avenues for progress are outlined, including the application of perfect absorption of incident light, with no reflection or transmission.
Abstract: In recent years we have learned to fabricate structures smaller than electromagnetic wavelengths, and to assemble them into metamaterials with exotic optical properties for previously unimaginable applications. One such property is perfect absorption of incident light, with no reflection or transmission, across many wavelengths. The authors review the physics, design principles, and classification of thin perfect absorbers, and outline avenues for progress.

Journal ArticleDOI
TL;DR: In this paper, the authors show that electrical switching of the interfacial oxidation state allows for voltage control of magnetic properties to an extent never before achieved through conventional magneto-electric coupling mechanisms.
Abstract: In metal/oxide heterostructures, rich chemical, electronic, magnetic and mechanical properties can emerge from interfacial chemistry and structure. The possibility to dynamically control interface characteristics with an electric field paves the way towards voltage control of these properties in solid-state devices. Here, we show that electrical switching of the interfacial oxidation state allows for voltage control of magnetic properties to an extent never before achieved through conventional magneto-electric coupling mechanisms. We directly observe in situ voltage-driven O(2-) migration in a Co/metal-oxide bilayer, which we use to toggle the interfacial magnetic anisotropy energy by >0.75 erg cm(-2) at just 2 V. We exploit the thermally activated nature of ion migration to markedly increase the switching efficiency and to demonstrate reversible patterning of magnetic properties through local activation of ionic migration. These results suggest a path towards voltage-programmable materials based on solid-state switching of interface oxygen chemistry.

Journal ArticleDOI
TL;DR: This paper analyzes security threats to application, control, and data planes of SDN and describes the security platforms that secure each of the planes followed by various security approaches for network-wide security in SDN.
Abstract: Software defined networking (SDN) decouples the network control and data planes. The network intelligence and state are logically centralized and the underlying network infrastructure is abstracted from applications. SDN enhances network security by means of global visibility of the network state where a conflict can be easily resolved from the logically centralized control plane. Hence, the SDN architecture empowers networks to actively monitor traffic and diagnose threats to facilitates network forensics, security policy alteration, and security service insertion. The separation of the control and data planes, however, opens security challenges, such as man-in-the middle attacks, denial of service (DoS) attacks, and saturation attacks. In this paper, we analyze security threats to application, control, and data planes of SDN. The security platforms that secure each of the planes are described followed by various security approaches for network-wide security in SDN. SDN security is analyzed according to security dimensions of the ITU-T recommendation, as well as, by the costs of security solutions. In a nutshell, this paper highlights the present and future security challenges in SDN and future directions for secure SDN.

Journal ArticleDOI
TL;DR: The results suggest that the relationship between utilitarian benefits and use is mediated by the attitude toward the use of gamification, while hedonic aspects have a direct positive relationship with use.

Journal ArticleDOI
TL;DR: This study presents a roadmap from the current cellular technologies toward fully MTC-capable 5G mobile systems, and provides a clear mapping between the main MTC service requirements and their associated challenges.
Abstract: Machine-type communications (MTC) enables a broad range of applications from mission- critical services to massive deployment of autonomous devices. To spread these applications widely, cellular systems are considered as a potential candidate to provide connectivity for MTC devices. The ubiquitous deployment of these systems reduces network installation cost and provides mobility support. However, based on the service functions, there are key challenges that currently hinder the broad use of cellular systems for MTC. This article provides a clear mapping between the main MTC service requirements and their associated challenges. The goal is to develop a comprehensive understanding of these challenges and the potential solutions. This study presents, in part, a roadmap from the current cellular technologies toward fully MTC-capable 5G mobile systems.

Journal ArticleDOI
TL;DR: In this paper, the formation energies of neutral and charged defects, determine the charge transition levels, and from these self-consistently assess the concentration of defects at thermal equilibrium as well as the resulting positions of the Fermi level.
Abstract: We present an extensive first-principles study of a large set of native defects in ${\mathrm{MoS}}_{2}$ in order to find out the types and concentrations of the most important defects in this system. The calculations are carried out for both bulk and monolayer forms of ${\mathrm{MoS}}_{2}$, which allows us to study how defect properties change between these two limiting cases. We consider single- and few-atom vacancies, antisites, adatoms on monolayer, and interstitials between layers in the bulk material. We calculate the formation energies of neutral and charged defects, determine the charge transition levels, and from these self-consistently assess the concentration of defects at thermal equilibrium as well as the resulting positions of the Fermi level. The chemical potential values corresponding to different growth conditions are carefully accounted for, and for all values of chemical potentials relevant to the growth of ${\mathrm{MoS}}_{2}$, the S vacancies are found to be the most abundant defects. However, they are acceptors and cannot be the cause of the often observed $n$-type doping. At the same time, Re impurities, which are often present in natural ${\mathrm{MoS}}_{2}$ samples, naturally provide good $n$-type doping behavior. We also calculate migration barriers for adatoms and interstitials and discuss how they can affect the growth process.

Journal ArticleDOI
TL;DR: GigaSight is described, an Internet-scale repository of crowd-sourced video content, with strong enforcement of privacy preferences and access controls, and a federated system of VM-based cloudlets that perform video analytics at the edge of the Internet, thus reducing the demand for ingress bandwidth into the cloud.
Abstract: High-data-rate sensors, such as video cameras, are becoming ubiquitous in the Internet of Things. This article describes GigaSight, an Internet-scale repository of crowd-sourced video content, with strong enforcement of privacy preferences and access controls. The GigaSight architecture is a federated system of VM-based cloudlets that perform video analytics at the edge of the Internet, thus reducing the demand for ingress bandwidth into the cloud. Denaturing, which is an owner-specific reduction in fidelity of video content to preserve privacy, is one form of analytics on cloudlets. Content-based indexing for search is another form of cloudlet-based analytics. This article is part of a special issue on smart spaces.

Journal ArticleDOI
TL;DR: The results establish that a topologically nontrivial flat band is a promising concept for increasing the critical temperature of the superconducting transition and provides Ds for the time-reversal invariant attractive Harper–Hubbard model that can be experimentally tested in ultracold gases.
Abstract: Topological invariants built from the periodic Bloch functions characterize new phases of matter, such as topological insulators and topological superconductors. The most important topological invariant is the Chern number that explains the quantized conductance of the quantum Hall effect. Here we provide a general result for the superfluid weight Ds of a multiband superconductor that is applicable to topologically nontrivial bands with nonzero Chern number C. We find that the integral over the Brillouin-zone of the quantum metric, an invariant calculated from the Bloch functions, gives the superfluid weight in a flat band, with the bound Ds⩾|C|. Thus, even a flat band can carry finite superfluid current, provided the Chern number is nonzero. As an example, we provide Ds for the time-reversal invariant attractive Harper-Hubbard model that can be experimentally tested in ultracold gases. In general, our results establish that a topologically nontrivial flat band is a promising concept for increasing the critical temperature of the superconducting transition.

Journal ArticleDOI
TL;DR: This work prepares a nearly macroscopic moving body, realized as a micromechanical resonator, in a squeezed quantum state, and obtains squeezing of one quadrature amplitude 1.1±0.4 dB below the standard quantum limit, thus achieving a long-standing goal of obtaining motional squeezing in a macroscopy object.
Abstract: The act of a quantum measurement reduces the uncertainty in the motion of a vibrating membrane below the fundamental quantum limit.

Journal ArticleDOI
Jukka P. Pekola1
TL;DR: In this paper, the authors review some recent experiments on quantum heat transport, fluctuation relations and implementations of Maxwell's demon, revealing the rich physics yet to be fully probed in these systems.
Abstract: Electronic circuits operating at sub-kelvin temperatures are attractive candidates for studying classical and quantum thermodynamics: their temperature can be controlled and measured locally with exquisite precision, and they allow experiments with large statistical samples. The availability and rapid development of devices such as quantum dots, single-electron boxes and superconducting qubits only enhance their appeal. But although these systems provide fertile ground for studying heat transport, entropy production and work in the context of quantum mechanics, the field remains in its infancy experimentally. Here, we review some recent experiments on quantum heat transport, fluctuation relations and implementations of Maxwell’s demon, revealing the rich physics yet to be fully probed in these systems. Experiments probing non-equilibrium processes have so far been tailored largely to classical systems. The endeavour to extend our understanding into the quantum realm is finding traction in studies of electronic circuits at sub-kelvin temperatures.

Journal ArticleDOI
TL;DR: Structural properties and the chemical nature of the NO-reacted B-GNR are determined by a combination of scanning tunnelling microscopy, high-resolution atomic force microscopy with a CO tip, and density functional and classical computations.
Abstract: Boron is a unique element in terms of electron deficiency and Lewis acidity Incorporation of boron atoms into an aromatic carbon framework offers a wide variety of functionality However, the intrinsic instability of organoboron compounds against moisture and oxygen has delayed the development Here, we present boron-doped graphene nanoribbons (B-GNRs) of widths of N=7, 14 and 21 by on-surface chemical reactions with an employed organoboron precursor The location of the boron dopant is well defined in the centre of the B-GNR, corresponding to 48 atom%, as programmed The chemical reactivity of B-GNRs is probed by the adsorption of nitric oxide (NO), which is most effectively trapped by the boron sites, demonstrating the Lewis acid character Structural properties and the chemical nature of the NO-reacted B-GNR are determined by a combination of scanning tunnelling microscopy, high-resolution atomic force microscopy with a CO tip, and density functional and classical computations

Journal ArticleDOI
TL;DR: This work synthesizes the narrowest possible GNR belonging to this family (five carbon atoms wide, N=5), and studies the evolution of the electronic bandgap and orbital structure of GNR segments as a function of their length using low-temperature scanning tunnelling microscopy and density-functional theory calculations.
Abstract: Graphene nanoribbons (GNRs)-narrow stripes of graphene-have emerged as promising building blocks for nanoelectronic devices. Recent advances in bottom-up synthesis have allowed production of atomically well-defined armchair GNRs with different widths and doping. While all experimentally studied GNRs have exhibited wide bandgaps, theory predicts that every third armchair GNR (widths of N=3m+2, where m is an integer) should be nearly metallic with a very small bandgap. Here, we synthesize the narrowest possible GNR belonging to this family (five carbon atoms wide, N=5). We study the evolution of the electronic bandgap and orbital structure of GNR segments as a function of their length using low-temperature scanning tunnelling microscopy and density-functional theory calculations. Already GNRs with lengths of 5 nm reach almost metallic behaviour with ∼100 meV bandgap. Finally, we show that defects (kinks) in the GNRs do not strongly modify their electronic structure.

Journal ArticleDOI
Peter A. R. Ade1, Nabila Aghanim2, D. Alina3, D. Alina4  +252 moreInstitutions (60)
TL;DR: In this article, the authors presented an overview of the polarized sky as seen by Planck HFI at 353 GHz, which is the most sensitive Planck channel for dust polarization.
Abstract: This paper presents an overview of the polarized sky as seen by Planck HFI at 353 GHz, which is the most sensitive Planck channel for dust polarization. We construct and analyse maps of dust polarization fraction and polarization angle at 1° resolution, taking into account noise bias and possible systematic effects. The sensitivity of the Planck HFI polarization measurements allows for the first time a mapping of Galactic dust polarized emission on large scales, including low column density regions. We find that the maximum observed dust polarization fraction is high (pmax = 19.8%), in particular in some regions of moderate hydrogen column density (NH < 2 × 1021 cm-2). The polarization fraction displays a large scatter at NH below a few 1021 cm-2. There is a general decrease in the dust polarization fraction with increasing column density above NH ≃ 1 × 1021 cm-2 and in particular a sharp drop above NH ≃ 1.5 × 1022 cm-2. We characterize the spatial structure of the polarization angle using the angle dispersion function. We find that the polarization angle is ordered over extended areas of several square degrees, separated by filamentary structures of high angle dispersion function. These appear as interfaces where the sky projection of the magnetic field changes abruptly without variations in the column density. The polarization fraction is found to be anti-correlated with the dispersion of polarization angles. These results suggest that, at the resolution of 1°, depolarization is due mainly to fluctuations in the magnetic field orientation along the line of sight, rather than to the loss of grain alignment in shielded regions. We also compare the polarization of thermal dust emission with that of synchrotron measured with Planck, low-frequency radio data, and Faraday rotation measurements toward extragalactic sources. These components bear resemblance along the Galactic plane and in some regions such as the Fan and North Polar Spur regions. The poor match observed in other regions shows, however, that dust, cosmic-ray electrons, and thermal electrons generally sample different parts of the line of sight.

Journal ArticleDOI
TL;DR: In this paper, the effect of residual lignin on the interfacial, physical and mechanical properties of lignocellulose nanofibrils (LCNF) and respective nanopapers was elucidated.

Journal ArticleDOI
TL;DR: WWTPs may operate as a route for microplastics entering the sea because the average fibre concentration was 25 times higher and the particle concentration was three times higher in the effluent compared to the receiving body of water.