Showing papers by "University of Paderborn published in 2020"

CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations

Abstract: CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post–Hartree–Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.

CP2K: An Electronic Structure and Molecular Dynamics Software Package -- Quickstep: Efficient and Accurate Electronic Structure Calculations.

Abstract: CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular and biological systems. It is especially aimed at massively-parallel and linear-scaling electronic structure methods and state-of-the-art ab-initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2k to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.

CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings

Abstract: Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge revisits the previous CHiME-5 challenge and further considers the problem of distant multi-microphone conversational speech diarization and recognition in everyday home environments. Speech material is the same as the previous CHiME-5 recordings except for accurate array synchronization. The material was elicited using a dinner party scenario with efforts taken to capture data that is representative of natural conversational speech. This paper provides a baseline description of the CHiME-6 challenge for both segmented multispeaker speech recognition (Track 1) and unsegmented multispeaker speech recognition (Track 2). Of note, Track 2 is the first challenge activity in the community to tackle an unsegmented multispeaker speech recognition scenario with a complete set of reproducible open source baselines providing speech enhancement, speaker diarization, and speech recognition modules.

A High-Rate Two-Dimensional Polyarylimide Covalent Organic Framework Anode for Aqueous Zn-Ion Energy Storage Devices.

Abstract: Rechargeable aqueous Zn-ion energy storage devices are promising candidates for next-generation energy storage technologies. However, the lack of highly reversible Zn2+-storage anode materials with low potential windows remains a primary concern. Here, we report a two-dimensional polyarylimide covalent organic framework (PI-COF) anode with high-kinetics Zn2+-storage capability. The well-organized pore channels of PI-COF allow the high accessibility of the build-in redox-active carbonyl groups and efficient ion diffusion with a low energy barrier. The constructed PI-COF anode exhibits a specific capacity (332 C g-1 or 92 mAh g-1 at 0.7 A g-1), a high rate capability (79.8% at 7 A g-1), and a long cycle life (85% over 4000 cycles). In situ Raman investigation and first-principle calculations clarify the two-step Zn2+-storage mechanism, in which imide carbonyl groups reversibly form negatively charged enolates. Dendrite-free full Zn-ion devices are fabricated by coupling PI-COF anodes with MnO2 cathodes, delivering excellent energy densities (23.9 ∼ 66.5 Wh kg-1) and supercapacitor-level power densities (133 ∼ 4782 W kg-1). This study demonstrates the feasibility of covalent organic framework as Zn2+-storage anodes and shows a promising prospect for constructing reliable aqueous energy storage devices.

Nonlinear optics at all-dielectric nanoantennas and metasurfaces

Abstract: Freed from phase-matching constraints, plasmonic metasurfaces have contributed significantly to the control of the optical nonlinearity and enhancing the nonlinear generation efficiency by engineering subwavelength meta-atoms. However, the high dissipative losses and the inevitable thermal heating limit their applicability in nonlinear nanophotonics. All-dielectric metasurfaces, supporting both electric and magnetic Mie-type resonances in their nanostructures, have appeared as a promising alternative to nonlinear plasmonics. High-index dielectric nanostructures, allowing additional magnetic resonances, can induce magnetic nonlinear effects, which along with electric nonlinearities increase the nonlinear conversion efficiency. In addition, low dissipative losses and high damage thresholds provide an extra degree of freedom for operating at high pump intensities, resulting in a considerable enhancement of the nonlinear processes. In this review, we discuss the current state-of-the-art in the intensely developing area of all-dielectric nonlinear nanostructures and metasurfaces, including the role of Mie modes, Fano resonances and anapole moments for harmonic generation, wave mixing, and ultrafast optical switching. Furthermore, we review the recent progress in the nonlinear phase and wavefront control using all-dielectric metasurfaces. We discuss techniques to realize all-dielectric metasurfaces for multifunctional applications and generation of second-order nonlinear processes from CMOS compatible materials.

Challenges and Perspectives of DNA Nanostructures in Biomedicine

Abstract: DNA nanotechnology holds substantial promise for future biomedical engineering and the development of novel therapies and diagnostic assays. The subnanometer-level addressability of DNA nanostructures allows for their precise and tailored modification with numerous chemical and biological entities, which makes them fit to serve as accurate diagnostic tools and multifunctional carriers for targeted drug delivery. The absolute control over shape, size, and function enables the fabrication of tailored and dynamic devices, such as DNA nanorobots that can execute programmed tasks and react to various external stimuli. Even though several studies have demonstrated the successful operation of various biomedical DNA nanostructures both in vitro and in vivo, major obstacles remain on the path to real-world applications of DNA-based nanomedicine. Here, we summarize the current status of the field and the main implementations of biomedical DNA nanostructures. In particular, we focus on open challenges and untackled issues and discuss possible solutions.

Asteroid: The PyTorch-Based Audio Source Separation Toolkit for Researchers.

Abstract: This paper describes Asteroid, the PyTorch-based audio source separation toolkit for researchers. Inspired by the most successful neural source separation systems, it provides all neu-ral building blocks required to build such a system. To improve reproducibility, Kaldi-style recipes on common audio source separation datasets are also provided. This paper describes the software architecture of Asteroid and its most important features. By showing experimental results obtained with Asteroid's recipes, we show that our implementations are at least on par with most results reported in reference papers. The toolkit is publicly available at github.com/mpariente/asteroid.

Polarization-Encrypted Orbital Angular Momentum Multiplexed Metasurface Holography.

Abstract: Metasurface holography has the advantage of realizing complex wavefront modulation by thin layers together with the progressive technique of computer-generated holographic imaging. Despite the well-known light parameters, such as amplitude, phase, polarization, and frequency, the orbital angular momentum (OAM) of a beam can be regarded as another degree of freedom. Here, we propose and demonstrate orbital angular momentum multiplexing at different polarization channels using a birefringent metasurface for holographic encryption. The OAM selective holographic information can only be reconstructed with the exact topological charge and a specific polarization state. By using an incident beam with different topological charges as erasers, we mimic a super-resolution case for the reconstructed image, in analogy to the well-known STED technique in microscopy. The combination of multiple polarization channels together with the orbital angular momentum selectivity provides a higher security level for holographic encryption. Such a technique can be applied for beam shaping, optical camouflage, data storage, and dynamic displays.

Roadmap on quantum light spectroscopy

Abstract: Conventional spectroscopy uses classical light to detect matter properties through the variation of its response with frequencies or time delays. Quantum light opens up new avenues for spectroscopy by utilizing parameters of the quantum state of light as novel control knobs and through the variation of photon statistics by coupling to matter. This Roadmap article focuses on using quantum light as a powerful sensing and spectroscopic tool to reveal novel information about complex molecules that is not accessible by classical light. It aims at bridging the quantum optics and spectroscopy communities which normally have opposite goals: manipulating complex light states with simple matter e.g. qubits versus studying complex molecules with simple classical light, respectively. Articles cover advances in the generation and manipulation of state-of-the-art quantum light sources along with applications to sensing, spectroscopy, imaging and interferometry.

Single-photon sources: Approaching the ideal through multiplexing.

Abstract: We review the rapid recent progress in single-photon sources based on multiplexing multiple probabilistic photon-creation events. Such multiplexing allows higher single-photon probabilities and lower contamination from higher-order photon states. We study the requirements for multiplexed sources and compare various approaches to multiplexing using different degrees of freedom.

AdapterDrop: On the Efficiency of Adapters in Transformers

Abstract: Massively pre-trained transformer models are computationally expensive to fine-tune, slow for inference, and have large storage requirements. Recent approaches tackle these shortcomings by training smaller models, dynamically reducing the model size, and by training light-weight adapters. In this paper, we propose AdapterDrop, removing adapters from lower transformer layers during training and inference, which incorporates concepts from all three directions. We show that AdapterDrop can dynamically reduce the computational overhead when performing inference over multiple tasks simultaneously, with minimal decrease in task performances. We further prune adapters from AdapterFusion, which improves the inference efficiency while maintaining the task performances entirely.

SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles

Abstract: We present the results and the main findings of SemEval-2020 Task 11 on Detection of Propaganda Techniques in News Articles. The task featured two subtasks. Subtask SI is about Span Identification: given a plain-text document, spot the specific text fragments containing propaganda. Subtask TC is about Technique Classification: given a specific text fragment, in the context of a full document, determine the propaganda technique it uses, choosing from an inventory of 14 possible propaganda techniques. The task attracted a large number of participants: 250 teams signed up to participate and 44 made a submission on the test set. In this paper, we present the task, analyze the results, and discuss the system submissions and the methods they used. For both subtasks, the best systems used pre-trained Transformers and ensembles.

CHiME-6 Challenge: Tackling multispeaker speech recognition for unsegmented recordings

Abstract: Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge revisits the previous CHiME-5 challenge and further considers the problem of distant multi-microphone conversational speech diariza-tion and recognition in everyday home environments. Speech material is the same as the previous CHiME-5 recordings except for accurate array synchronization. The material was elicited using a dinner party scenario with efforts taken to capture data that is representative of natural conversational speech. This paper provides a baseline description of the CHiME-6 challenge for both segmented multispeaker speech recognition (Track 1) and unsegmented multispeaker speech recognition (Track 2). Of note, Track 2 is the first challenge activity in the community to tackle an unsegmented multispeaker speech recognition scenario with a complete set of reproducible open source baselines providing speech enhancement, speaker diarization, and speech recognition modules.

Nonlinear Imaging with All-Dielectric Metasurfaces.

Abstract: Nonlinear metasurfaces incorporate many of the functionalities of their linear counterparts such as wavefront shaping, but simultaneously they perform nonlinear optical transformations. This dual functionality leads to a rather unintuitive physical behavior which is still widely unexplored for many photonic applications. The nonlinear processes render some basic principles governing the functionality of linear metasurfaces. Exemplarily, the superposition principle and the geometric optics approximation become not directly applicable to nonlinear metasurfaces. On the other hand, nonlinear metasurfaces facilitate new phenomena that are not possible in the linear regime. Here, we study the imaging of objects through a dielectric nonlinear metalens. We illuminate objects by infrared light and record their generated images at the visible third-harmonic wavelengths. We revisit the classical lens theory and suggest a generalized Gaussian lens equation for nonlinear imaging, verified both experimentally and analytically. We also demonstrate experimentally higher-order spatial correlations facilitated by the nonlinear metalens, resulting in additional image features.

Mitigating information overload in social media during conflicts and crises: design and evaluation of a cross-platform alerting system

Abstract: The research field of crisis informatics examines, amongst others, the potentials and barriers of social media use during conflicts and crises. Social media allow emergency services to reach the pu...

IoT-based enterprise resource planning: Challenges, open issues, applications, architecture, and future research directions

Abstract: In today's highly competitive markets, organizations can create a competitive advantage through the successful implementation of Enterprise Resource Planning (ERP) systems. ERP works with different technologies, including the Internet of Things (IoT). IoT uses a unique Internet protocol to identify, control, and transfer data to individuals as well as databases. The data is collected through IoT, stored on the cloud, and extracted and managed in through ERP. In this study, we review the challenges, open issues, applications, and architecture of the IoT-based ERP. For this purpose, we review and analyze the latest IoT-related articles to present the unique features of the IoT and discuss its impact on ERP. The results show sensors and devices connected to the Internet can manage the stored data processed in the cloud through ERP without human intervention. We also discuss the challenges and opportunities in the relationship between ERP and the IoT risen by the introduction of the cloud.

A dielectric metasurface optical chip for the generation of cold atoms.

Abstract: Compact and robust cold atom sources are increasingly important for quantum research, especially for transferring cutting-edge quantum science into practical applications. In this study, we report on a novel scheme that uses a metasurface optical chip to replace the conventional bulky optical elements used to produce a cold atomic ensemble with a single incident laser beam, which is split by the metasurface into multiple beams of the desired polarization states. Atom numbers ~107 and temperatures (about 35 μK) of relevance to quantum sensing are achieved in a compact and robust fashion. Our work highlights the substantial progress toward fully integrated cold atom quantum devices by exploiting metasurface optical chips, which may have great potential in quantum sensing, quantum computing, and other areas.

Key activity descriptors of nickel-iron oxygen evolution electrocatalysts in the presence of alkali metal cations.

Abstract: Efficient oxygen evolution reaction (OER) electrocatalysts are pivotal for sustainable fuel production, where the Ni-Fe oxyhydroxide (OOH) is among the most active catalysts for alkaline OER. Elect ...

Pt-Ni@PC900 Hybrid Derived from Layered-Structure Cd-MOF for Fuel Cell ORR Activity

Abstract: Fuel cell technology is the supreme alternate option for the replacement of fossil fuel in the current era. Pt alloys can perform well as fuel cell electrodes for being used as catalytic materials to perform the very notorious oxygen reduction reaction. In this regard, first, a layered metal-organic framework with empirical formula [C8H10CdO7] n ·4H2O is synthesized and characterized using various experimental and theoretical techniques. Then, a nanostructured porous carbon material with a sheet morphology (PC900) having a high BET surface area of 877 m2 g-1 is fabricated by an inert-atmosphere thermal treatment of the framework upon heating up to 900 °C. Pt and Ni nanoparticles are embedded into PC900 to prepare a homogenized hybrid functional material, i.e., Pt-Ni@PC900. The Pt-Ni@PC900 hybrid is proved to be an excellent ORR catalyst in terms of half-wave potential and limiting current density with 7% Pt loading compared with the commercially available 20% Pt/C catalyst. Pt-Ni@PC900 also shows stability of current up to 12 h with only a very small variation in current. This work highlights the importance of Pt alloys in future large-scale commercial applications of fuel cells.

Facing Low Regularity in Chemotaxis Systems

Abstract: PDE systems describing chemotaxis, the directed motion of organisms in response to a chemical signal, contain a cross-diffusive term which in many cases causes the unavailability of strong regularity information. An important part of their mathematical analysis is thus concerned with their behavior in situations where solutions are known to blow-up or where singularities cannot be excluded a priori. In this note we review some results, as well as some underlying fundamental analytical ideas, from the context of rigorous blow-up detection, and discuss some approaches addressing the design of solution theories which are able to adequately cope with the possible destabilizing effects of chemotactic cross-diffusion.

Unraveling the interaction between doxorubicin and DNA origami nanostructures for customizable chemotherapeutic drug release

Abstract: Doxorubicin (DOX) is a commonly employed drug in cancer chemotherapy, and its high DNA-binding affinity can be harnessed in preparing programmable DOX-loaded DNA nanostructures that can be further tailored for targeted delivery and therapeutics. Although DOX has been widely studied, the existing literature of promising DOX-loaded DNA nanocarriers remains limited and incoherent. A number of reports have over-looked the fundamentals of the DOX-DNA interaction, let alone the peculiarities arising from the complexity of the system as a whole. Here, based on an in-depth spectroscopic analysis, we characterize and optimize the DOX loading into different 2D and 3D scaffolded DNA origami nanostructures. In our experimental conditions, all of our DNA origami designs show rather similar DOX binding capacities, which are, however, remarkably lower than previously reported. To simulate the possible physiological degradation pathways, we examine the stability and DOX release properties of the complexes upon DNase I digestion, which reveals that they disintegrate and release DOX into the surroundings at characteristic rates related to the DNA origami superstructure and the loaded DOX content. In addition, we identify DOX self-aggregation and precipitation mechanisms and spectral changes linked to pH, magnesium, and DOX concentration that have been largely ignored in experimenting with DNA nanostructures and in spectroscopic analysis performed with routine UV-Vis and fluorescence techniques. Nevertheless, we demonstrate the possibility of customizing drug release profiles through rational DNA origami design. Therefore, we believe this work can be used as a guide to tailor the release profiles and develop better drug delivery systems based on DNA nanostructures.

Deep model predictive flow control with limited sensor data and online learning

Abstract: The control of complex systems is of critical importance in many branches of science, engineering, and industry, many of which are governed by nonlinear partial differential equations. Controlling an unsteady fluid flow is particularly important, as flow control is a key enabler for technologies in energy (e.g., wind, tidal, and combustion), transportation (e.g., planes, trains, and automobiles), security (e.g., tracking airborne contamination), and health (e.g., artificial hearts and artificial respiration). However, the high-dimensional, nonlinear, and multi-scale dynamics make real-time feedback control infeasible. Fortunately, these high-dimensional systems exhibit dominant, low-dimensional patterns of activity that can be exploited for effective control in the sense that knowledge of the entire state of a system is not required. Advances in machine learning have the potential to revolutionize flow control given its ability to extract principled, low-rank feature spaces characterizing such complex systems. We present a novel deep learning model predictive control framework that exploits low-rank features of the flow in order to achieve considerable improvements to control performance. Instead of predicting the entire fluid state, we use a recurrent neural network (RNN) to accurately predict the control relevant quantities of the system, which are then embedded into an MPC framework to construct a feedback loop. In order to lower the data requirements and to improve the prediction accuracy and thus the control performance, incoming sensor data are used to update the RNN online. The results are validated using varying fluid flow examples of increasing complexity.

Heterogeneous Behavior of Lithium Plating during Extreme Fast Charging

Abstract: Summary Broad use of global or spatially averaging measurements over a cell to characterize highly localized Li plating phenomena in lithium-ion batteries during fast charging has created a disconnect between measurements and the underlying causes. Consequently, the field is missing a clear path to implementing fast charging as well as to expand into extreme fast charging (XFC). Aiming to bridge these gaps, we present a detailed look into local detection of Li plating and the consequent cycle life implications for electrodes and cells under XFC by utilizing electrochemistry and high-energy X-ray diffraction. Significant heterogeneity in Li plating during XFC results in accelerated and non-uniform cycle life losses, in contrast to the prevailing acceptance that C rate is correlated to Li plating for XFC. This behavior is triggered by local electrode heterogeneity, which has yet to be identified and is not apparent in volume-averaged quantifications. A better understanding of these multiscale local electrode heterogeneities is crucial for identifying pathways to enable XFC.

Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging.

Abstract: Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-the-art for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.

Energy transfer within the hydrogen bonding network of water following resonant terahertz excitation

Abstract: Energy dissipation in water is very fast and more efficient than in many other liquids. This behavior is commonly attributed to the intermolecular interactions associated with hydrogen bonding. Here, we investigate the dynamic energy flow in the hydrogen bond network of liquid water by a pump-probe experiment. We resonantly excite intermolecular degrees of freedom with ultrashort single-cycle terahertz pulses and monitor its Raman response. By using ultrathin sample cell windows, a background-free bipolar signal whose tail relaxes monoexponentially is obtained. The relaxation is attributed to the molecular translational motions, using complementary experiments, force field, and ab initio molecular dynamics simulations. They reveal an initial coupling of the terahertz electric field to the molecular rotational degrees of freedom whose energy is rapidly transferred, within the excitation pulse duration, to the restricted translational motion of neighboring molecules. This rapid energy transfer may be rationalized by the strong anharmonicity of the intermolecular interactions.