Showing papers by "University of Stuttgart published in 2021"

Data-Driven Model Predictive Control With Stability and Robustness Guarantees

Abstract: We propose a robust data-driven model predictive control (MPC) scheme to control linear time-invariant systems. The scheme uses an implicit model description based on behavioral systems theory and past measured trajectories. In particular, it does not require any prior identification step, but only an initially measured input–output trajectory as well as an upper bound on the order of the unknown system. First, we prove exponential stability of a nominal data-driven MPC scheme with terminal equality constraints in the case of no measurement noise. For bounded additive output measurement noise, we propose a robust modification of the scheme, including a slack variable with regularization in the cost. We prove that the application of this robust MPC scheme in a multistep fashion leads to practical exponential stability of the closed loop w.r.t. the noise level. The presented results provide the first (theoretical) analysis of closed-loop properties, resulting from a simple, purely data-driven MPC scheme.

Knowledge Graphs

Abstract: In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.

Detection of two interstellar polycyclic aromatic hydrocarbons via spectral matched filtering.

Abstract: Unidentified infrared emission bands are ubiquitous in many astronomical sources. These bands are widely, if not unanimously, attributed to collective emissions from polycyclic aromatic hydrocarbon (PAH) molecules, yet no single species of this class has been identified in space. Using spectral matched filtering of radio data from the Green Bank Telescope, we detected two nitrile-group-functionalized PAHs, 1- and 2-cyanonaphthalene, in the interstellar medium. Both bicyclic ring molecules were observed in the TMC-1 molecular cloud. In this paper, we discuss potential in situ gas-phase PAH formation pathways from smaller organic precursor molecules.

Defect Passivation in Lead-Halide Perovskite Nanocrystals and Thin Films: Toward Efficient LEDs and Solar cells

Abstract: Lead-halide perovskites (LHPs), in the form of both colloidal nanocrystals (NCs) and thin films, have emerged over the past decade as leading candidates for next-generation, efficient light-emitting diodes (LEDs) and solar cells. Owing to their high photoluminescence quantum yields (PLQYs), LHPs efficiently convert injected charge carriers into light and vice versa. However, despite the defect-tolerance of LHPs, defects at the surface of colloidal NCs and grain boundaries in thin films play a critical role in charge-carrier transport and nonradiative recombination, which lowers the PLQYs, device efficiency, and stability. Therefore, understanding the defects that play a key role in limiting performance, and developing effective passivation routes are critical for achieving advances in performance. This Review presents the current understanding of defects in halide perovskites and their influence on the optical and charge-carrier transport properties. Passivation strategies toward improving the efficiencies of perovskite-based LEDs and solar cells are also discussed.

Real-time optimal quantum control of mechanical motion at room temperature

Abstract: The ability to accurately control the dynamics of physical systems by measurement and feedback is a pillar of modern engineering1. Today, the increasing demand for applied quantum technologies requires adaptation of this level of control to individual quantum systems2,3. Achieving this in an optimal way is a challenging task that relies on both quantum-limited measurements and specifically tailored algorithms for state estimation and feedback4. Successful implementations thus far include experiments on the level of optical and atomic systems5–7. Here we demonstrate real-time optimal control of the quantum trajectory8 of an optically trapped nanoparticle. We combine confocal position sensing close to the Heisenberg limit with optimal state estimation via Kalman filtering to track the particle motion in phase space in real time with a position uncertainty of 1.3 times the zero-point fluctuation. Optimal feedback allows us to stabilize the quantum harmonic oscillator to a mean occupation of 0.56 ± 0.02 quanta, realizing quantum ground-state cooling from room temperature. Our work establishes quantum Kalman filtering as a method to achieve quantum control of mechanical motion, with potential implications for sensing on all scales. In combination with levitation, this paves the way to full-scale control over the wavepacket dynamics of solid-state macroscopic quantum objects in linear and nonlinear systems. Optimal quantum control of an optically trapped nanoparticle in its ground state is demonstrated at room temperature, using Kalman filtering to track its quantum trajectory in real time.

Digital twins for collaborative robots: A case study in human-robot interaction

Abstract: Human-robot collaboration (HRC) can expand the level of automation in areas that have conventionally been difficult to automate such as assembly. However, the need of adaptability and the dynamics of human presence are keeping the full potential of human-robot collaborative systems difficult to achieve. This paper explores the opportunities of using a digital twin to address the complexity of collaborative production systems through an industrial case and a demonstrator. A digital twin, as a virtual counterpart of a physical human-robot assembly system, is built as a ‘front-runner’ for validation and control throughout its design, build and operation. The forms of digital twins along system's life cycle, its building blocks and the potential advantages are presented and discussed. Recommendations for future research and practice in the use of digital twins in the field of cobotics are given.

Data-Driven Control of Soft Robots Using Koopman Operator Theory

Abstract: Controlling soft robots with precision is a challenge due to the difficulty of constructing models that are amenable to model-based control design techniques. Koopman operator theory offers a way to construct explicit dynamical models of soft robots and to control them using established model-based control methods. This approach is data driven, yet yields an explicit control-oriented model rather than just a “black-box” input–output mapping. This work describes a Koopman-based system identification method and its application to model predictive control (MPC) design for soft robots. Three MPC controllers are developed for a pneumatic soft robot arm via the Koopman-based approach, and their performances are evaluated with respect to several real-world trajectory following tasks. In terms of average tracking error, these Koopman-based controllers are more than three times more accurate than a benchmark MPC controller based on a linear state-space model of the same system, demonstrating the utility of the Koopman approach in controlling real soft robots.

A Computationally Efficient Robust Model Predictive Control Framework for Uncertain Nonlinear Systems

Abstract: In this article, we present a nonlinear robust model predictive control (MPC) framework for general (state and input dependent) disturbances. This approach uses an online constructed tube in order to tighten the nominal (state and input) constraints. To facilitate an efficient online implementation, the shape of the tube is based on an offline computed incremental Lyapunov function with a corresponding (nonlinear) incrementally stabilizing feedback. Crucially, the online optimization only implicitly includes these nonlinear functions in terms of scalar bounds, which enables an efficient implementation. Furthermore, to account for an efficient evaluation of the worst case disturbance, a simple function is constructed offline that upper bounds the possible disturbance realizations in a neighborhood of a given point of the open-loop trajectory. The resulting MPC scheme ensures robust constraint satisfaction and practical asymptotic stability with a moderate increase in the online computational demand compared to a nominal MPC. We demonstrate the applicability of the proposed framework in comparison to state-of-the-art robust MPC approaches with a nonlinear benchmark example.

Phyllotaxis-inspired nanosieves with multiplexed orbital angular momentum

Abstract: Nanophotonic platforms such as metasurfaces, achieving arbitrary phase profiles within ultrathin thickness, emerge as miniaturized, ultracompact and kaleidoscopic optical vortex generators. However, it is often required to segment or interleave independent sub-array metasurfaces to multiplex optical vortices in a single nano-device, which in turn affects the device’s compactness and channel capacity. Here, inspired by phyllotaxis patterns in pine cones and sunflowers, we theoretically prove and experimentally report that multiple optical vortices can be produced in a single compact phyllotaxis nanosieve, both in free space and on a chip, where one meta-atom may contribute to many vortices simultaneously. The time-resolved dynamics of on-chip interference wavefronts between multiple plasmonic vortices was revealed by ultrafast time-resolved photoemission electron microscopy. Our nature-inspired optical vortex generator would facilitate various vortex-related optical applications, including structured wavefront shaping, free-space and plasmonic vortices, and high-capacity information metaphotonics.

New states of matter with fine-tuned interactions: quantum droplets and dipolar supersolids.

Abstract: Quantum fluctuations can stabilize Bose-Einstein condensates (BEC) against the mean-field collapse. Stabilization of the condensate has been observed in quantum degenerate Bose-Bose mixtures and dipolar BECs. The fine-tuning of the interatomic interactions can lead to the emergence of two new states of matter: liquid-like self-bound quantum droplets and supersolid crystals formed from these droplets. We review the properties of these exotic states of matter and summarize the experimental progress made using dipolar quantum gases and Bose-Bose mixtures. We conclude with an outline of important open questions that could be addressed in the future.

Emerging perovskite monolayers.

Abstract: The library of two-dimensional (2D) materials has been enriched over recent years with novel crystal architectures endowed with diverse exciting functionalities. Bulk perovskites, including metal-halide and oxide systems, provide access to a myriad of properties through molecular engineering. Their tunable electronic structure offers remarkable features from long carrier-diffusion lengths and high absorption coefficients in metal-halide perovskites to high-temperature superconductivity, magnetoresistance and ferroelectricity in oxide perovskites. Emboldened by the 2D materials research, perovskites down to the monolayer limit have recently emerged. Like other 2D species, perovskites with reduced dimensionality are expected to exhibit new physics and to herald next-generation multifunctional devices. In this Review, we critically assess the preliminary studies on the synthetic routes and inherent properties of monolayer perovskite materials. We also discuss how to exploit them for widespread applications and provide an outlook on the challenges and opportunities that lie ahead for this enticing class of 2D materials. Metal-halide and oxide perovskites are a rich playground for fundamental studies and applications. This Review focuses on the opportunities opened by reducing the dimensionality of these materials to two-dimensional monolayers.

Single-spin resonance in a van der Waals embedded paramagnetic defect.

Abstract: A plethora of single-photon emitters have been identified in the atomic layers of two-dimensional van der Waals materials1–8. Here, we report on a set of isolated optical emitters embedded in hexagonal boron nitride that exhibit optically detected magnetic resonance. The defect spins show an isotropic ge-factor of ~2 and zero-field splitting below 10 MHz. The photokinetics of one type of defect is compatible with ground-state electron-spin paramagnetism. The narrow and inhomogeneously broadened magnetic resonance spectrum differs significantly from the known spectra of in-plane defects. We determined a hyperfine coupling of ~10 MHz. Its angular dependence indicates an unpaired, out-of-plane delocalized π-orbital electron, probably originating from substitutional impurity atoms. We extracted spin–lattice relaxation times T1 of 13–17 μs with estimated spin coherence times T2 of less than 1 μs. Our results provide further insight into the structure, composition and dynamics of single optically active spin defects in hexagonal boron nitride. The optically detected magnetic resonance of a single defect in hexagonal boron nitride is reported.

Synergistically integrated phosphonated poly(pentafluorostyrene) for fuel cells.

Abstract: Modern electrochemical energy conversion devices require more advanced proton conductors for their broad applications. Phosphonated polymers have been proposed as anhydrous proton conductors for fuel cells. However, the anhydride formation of phosphonic acid functional groups lowers proton conductivity and this prevents the use of phosphonated polymers in fuel cell applications. Here, we report a poly(2,3,5,6-tetrafluorostyrene-4-phosphonic acid) that does not undergo anhydride formation and thus maintains protonic conductivity above 200 °C. We use the phosphonated polymer in fuel cell electrodes with an ion-pair coordinated membrane in a membrane electrode assembly. This synergistically integrated fuel cell reached peak power densities of 1,130 mW cm−2 at 160 °C and 1,740 mW cm−2 at 240 °C under H2/O2 conditions, substantially outperforming polybenzimidazole- and metal phosphate-based fuel cells. Our result indicates a pathway towards using phosphonated polymers in high-performance fuel cells under hot and dry operating conditions. Phosphonated polymers have been proposed as anhydrous proton conductors for fuel cells but anhydride formation of phosphonic acid functional groups lowers conductivity. A synergistically integrated phosphonated poly(pentafluorostyrene) is shown to maintain high protonic conductivity above 200 °C.

Upper mantle structure of Mars from InSight seismic data

Abstract: For 2 years, the InSight lander has been recording seismic data on Mars that are vital to constrain the structure and thermochemical state of the planet. We used observations of direct (P and S) and surface-reflected (PP, PPP, SS, and SSS) body-wave phases from eight low-frequency marsquakes to constrain the interior structure to a depth of 800 kilometers. We found a structure compatible with a low-velocity zone associated with a thermal lithosphere much thicker than on Earth that is possibly related to a weak S-wave shadow zone at teleseismic distances. By combining the seismic constraints with geodynamic models, we predict that, relative to the primitive mantle, the crust is more enriched in heat-producing elements by a factor of 13 to 20. This enrichment is greater than suggested by gamma-ray surface mapping and has a moderate-to-elevated surface heat flow.

Interstellar detection of the highly polar five-membered ring cyanocyclopentadiene

Abstract: Much like six-membered rings, five-membered rings are ubiquitous in organic chemistry, frequently serving as the building blocks for larger molecules, including many of biochemical importance. From a combination of laboratory rotational spectroscopy and a sensitive spectral line survey in the radio band toward the starless cloud core TMC-1, we report the astronomical detection of 1-cyano-1,3-cyclopentadiene (1-cyano-CPD, c-C5H5CN), a highly polar, cyano derivative of cyclopentadiene. The derived abundance of 1-cyano-CPD is far greater than predicted from astrochemical models that well reproduce the abundance of many carbon chains. This finding implies that either an important production mechanism or a large reservoir of aromatic material may need to be considered. The apparent absence of its closely related isomer, 2-cyano-1,3-cyclopentadiene, may arise from that isomer’s lower stability or may be indicative of a more selective pathway for formation of the 1-cyano isomer, perhaps one starting from acyclic precursors. The absence of N-heterocycles such as pyrrole and pyridine is discussed in light of the astronomical finding of 1-cyano-CPD. A five-membered carbon ring molecule, cyanocyclopentadiene, has been detected in a molecular cloud at a higher abundance than expected. This result from the GOTHAM survey indicates a rich aromatic chemistry in molecular clouds that is not fully understood theoretically.

COVID-19 risk perception and coping mechanisms: Does gender make a difference?

Abstract: The novel coronavirus disease (COVID-19) emerged as a real threat to humans, drastically disrupting everyday life in 2020-21. Although the pandemic affected people from all walks of life, irrespective of age or gender, the way the risk is perceived varies from one person to another. The pandemic risk reduction strategies can only be effective if individuals and communities respond positively to them, and for that, it is important to understand how the risk is perceived and responded to, differently by different groups of people. Gender plays a vital role in shaping risk perceptions and coping strategies, reflecting the predisposition of the public to accept health interventions and take precautionary measures. This study aims to understand the gender differences in COVID-19 risk perception and coping mechanisms - Pakistan is selected as a case study area. Following on from designing the questionnaire, which included 40 indicators grouped into domains (four risk perception and three coping mechanisms domains), an online survey was conducted, and a sample of 389 respondents was collected (248 male and 141 female). An index-based approach was used to quantify risk perception and its domains (fear, behaviour, awareness, and trust), and likewise coping mechanisms and their domains (problem, emotion, and action). Statistical tests were employed to ascertain the differences among both genders, whereas regression modelling was used to measure the effect of gender on overall risk perception and coping mechanisms. Results reveal that perceived fear and trust varied significantly between Pakistani men and women, while coping mechanisms were also notably different between the two genders. Females were found to perceive risks higher, complied more with the government's guidelines, and coped better than males in response to COVID-19. These findings imply that the gender aspect must be incorporated in designing effective communication and risk reduction strategies to efficiently address the current and potential future pandemic situations.

Atom probe tomography

Abstract: Atom probe tomography (APT) provides three-dimensional compositional mapping with sub-nanometre resolution. The sensitivity of APT is in the range of parts per million for all elements, including light elements such as hydrogen, carbon or lithium, enabling unique insights into the composition of performance-enhancing or lifetime-limiting microstructural features and making APT ideally suited to complement electron-based or X-ray-based microscopies and spectroscopies. Here, we provide an introductory overview of APT ranging from its inception as an evolution of field ion microscopy to the most recent developments in specimen preparation, including for nanomaterials. We touch on data reconstruction, analysis and various applications, including in the geosciences and the burgeoning biological sciences. We review the underpinnings of APT performance and discuss both strengths and limitations of APT, including how the community can improve on current shortcomings. Finally, we look forwards to true atomic-scale tomography with the ability to measure the isotopic identity and spatial coordinates of every atom in an ever wider range of materials through new specimen preparation routes, novel laser pulsing and detector technologies, and full interoperability with complementary microscopy techniques. This Primer on atom probe tomography introduces the fundamentals of the technique and its experimental set-up, describes recent developments in specimen preparation, highlights aspects of data reconstruction and analysis, and showcases various applications of atom probe tomography in the materials sciences, geosciences and biological sciences.

Direct visualization of magnetic domains and moiré magnetism in twisted 2D magnets.

Abstract: Moire superlattices of twisted nonmagnetic two-dimensional (2D) materials are highly controllable platforms for the engineering of exotic correlated and topological states. Here, we report emerging...

Roadmap on organic–inorganic hybrid perovskite semiconductors and devices

Abstract: Metal halide perovskites are the first solution processed semiconductors that can compete in their functionality with conventional semiconductors, such as silicon. Over the past several years, perovskite semiconductors have reported breakthroughs in various optoelectronic devices, such as solar cells, photodetectors, light emitting and memory devices, and so on. Until now, perovskite semiconductors face challenges regarding their stability, reproducibility, and toxicity. In this Roadmap, we combine the expertise of chemistry, physics, and device engineering from leading experts in the perovskite research community to focus on the fundamental material properties, the fabrication methods, characterization and photophysical properties, perovskite devices, and current challenges in this field. We develop a comprehensive overview of the current state-of-the-art and offer readers an informed perspective of where this field is heading and what challenges we have to overcome to get to successful commercialization.

Fluoride ion batteries – past, present, and future

Abstract: Fluoride-Ion Batteries (FIBs) have been recently proposed as a post-lithium-ion battery system. This review article presents recent progress of the synthesis and application aspects of the cathode, electrolyte, and anode materials for fluoride-ion batteries. In this respect, improvements in solid-state electrolytes for FIBs as well as liquid electrolytes will be discussed. Furthermore, the achievements regarding the development of cathode and anode materials will be considered. With the improvements made, the field is currently attracting a steady increase of interest, and we will discuss the potentials of this technology together with necessary future milestones to be achieved in order to develop FIBs for future energy storage.

DuMux 3 – an open-source simulator for solving flow and transport problems in porous media with a focus on model coupling

Abstract: We present version 3 of the open-source simulator for flow and transport processes in porous media DuMux. DuMux is based on the modular C++ framework Dune (Distributed and Unified Numerics Environment) and is developed as a research code with a focus on modularity and reusability. We describe recent efforts in improving the transparency and efficiency of the development process and community-building, as well as efforts towards quality assurance and reproducible research. In addition to a major redesign of many simulation components in order to facilitate setting up complex simulations in DuMux, version 3 introduces a more consistent abstraction of finite volume schemes. Finally, the new framework for multi-domain simulations is described, and three numerical examples demonstrate its flexibility.

Photoelectrochemical Water-Splitting Using CuO-Based Electrodes for Hydrogen Production: A Review

Abstract: The cost-effective, robust, and efficient electrocatalysts for photoelectrochemical (PEC) water-splitting has been extensively studied over the past decade to address a solution for the energy crisis. The interesting physicochemical properties of CuO have introduced this promising photocathodic material among the few photocatalysts with a narrow bandgap. This photocatalyst has a high activity for the PEC hydrogen evolution reaction (HER) under simulated sunlight irradiation. Here, the recent advancements of CuO-based photoelectrodes, including undoped CuO, doped CuO, and CuO composites, in the PEC water-splitting field, are comprehensively studied. Moreover, the synthesis methods, characterization, and fundamental factors of each classification are discussed in detail. Apart from the exclusive characteristics of CuO-based photoelectrodes, the PEC properties of CuO/2D materials, as groups of the growing nanocomposites in photocurrent-generating devices, are discussed in separate sections. Regarding the particular attention paid to the CuO heterostructure photocathodes, the PEC water splitting application is reviewed and the properties of each group such as electronic structures, defects, bandgap, and hierarchical structures are critically assessed.

The DUNE framework: Basic concepts and recent developments

Abstract: This paper presents the basic concepts and the module structure of the Distributed and Unified Numerics Environment and reflects on recent developments and general changes that happened since the release of the first Dune version in 2007 and the main papers describing that state Bastian etal. (2008a, 2008b). This discussion is accompanied with a description of various advanced features, such as coupling of domains and cut cells, grid modifications such as adaptation and moving domains, high order discretizations and node level performance, non-smooth multigrid methods, and multiscale methods. A brief discussion on current and future development directions of the framework concludes the paper.