Recent Submissions
Halide perovskites in wide‐spectrum photodetection
(2026) Gholipour, Somayeh; Rahighi, Reza; Panahi, Mohammad; Lintangpradipto, Muhammad Naufal; Ghayoor, Reza; Saliba, Michael
Metal‐halide perovskites have emerged as promising semiconductors for wide‐spectrum photodetection owing to their exceptional optoelectronic properties, tunable band gaps, and facile synthesis. Their strong light–matter interactions and long carrier diffusion lengths have enabled devices capable of detecting radiation across an extraordinary spectral range, from γ‐rays and x‐rays to ultraviolet (UV), visible, and near‐infrared (NIR) light. This review highlights key advancements in perovskite‐based photodetectors (PPDs) and phototransistors, with an emphasis on high responsivity, detectivity, and ultrafast response times. We categorize device architectures by dimensionality (0D-3D) and detection regime, covering recent innovations such as flexible, lead‐free, and self‐powered PPDs. Special attention is given to novel chiral perovskites and polarization‐sensitive photodetectors enabling circularly polarized light (CPL) discrimination. Furthermore, this work discusses the extension of perovskite detection to the single‐photon level and evaluates underlying mechanisms for optical, ionizing, and near‐infrared regimes. The review concludes with perspectives on challenges and future trends, emphasizing interface engineering, stability enhancement, and scalable fabrication toward next‐generation optoelectronic imaging and communication systems.
Quantification and correction of motion influence for nacelle-based lidar systems on floating wind turbines
(2023) Gräfe, Moritz; Pettas, Vasilis; Gottschall, Julia; Cheng, Po Wen
Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement
(2023) Tischler, Ingo; Schlaich, Alexander; Holm, Christian
A passively self-adjusting floating wind farm layout to increase the annual energy production
(2022) Mahfouz, Mohammad Youssef; Cheng, Po-Wen
The Turing test as a sceptical scenario
(2026) Tritschler, Marvin
The Turing test is usually seen as an operationalisation of the question whether machines can think. In this paper, my aim is to show that by understanding the test in this way, one ends up in scepticism about the existence of minds in general. By focusing on whether some particular machine can pass the test, or whether it can be said to be an accurate criterion for thinking, most scholars accept the underlying assumption of the scenario, namely that we need an empirical procedure in order to secure the knowledge that someone thinks. I argue that the Turing test can not only be fruitfully paralleled to Descartes' language test, of which Turing knew, but should also be related to the former's sceptical method in the Meditations . Such a comparison makes clear why the scenario Turing imagined implies a scepticism not only about others′ minds but also one's own, as it abandons the idea that one can non‐empirically know in the first person that one thinks. I will end by sketching a solution to the sceptical problem of the knowledge of other minds by introducing the concept of second‐personal knowledge that someone is thinking by thinking the very same thought the other thinker thinks.
Polarization‐dependent elliptical and rectangular Mie voids
(2026) Arslan, Serkan; Sulejman, Shaban B.; Klein, Sebastian; Haehner, Jonathan; Schwab, Julian; Ludescher, Dominik; Wesemann, Lukas; Roberts, Ann; Giessen, Harald; Hentschel, Mario
Polarization is a key element in the design of nanophotonic devices, such as metasurfaces. It can be used as a parameter to change the performance of an optical device, for example, its transmission spectrum, or in conjunction with tailored anisotropies in nanostructures to control the geometric phase. To design polarization‐sensitive nanophotonic systems, we therefore require anisotropic elements with tailored optical properties. Mie voids, which take the form of lower‐index inclusions in a higher‐index material, have exhibited unique optical properties, such as the confinement of light in air at visible and ultraviolet wavelengths. In this study, we introduce anisotropy to this system to create polarization‐dependent Mie void resonances in elliptical and rectangular voids. We systemically investigate the dependence of the resonances on the geometry of the voids, study the optical mode formation in the system, and demonstrate polarization‐dependent nanoscale color printing. The combination of polarization‐dependent Mie voids and established nanophotonic elements can enable the design of new classes of metasurface designs and advanced polarization‐sensitive photonic devices.
Developing a framework for the quality‐driven migration to microservices : a multi‐method design science study
(2026) Fritzsch, Jonas; Bogner, Justus; Haller, Tobias; Koch, Daniel; Knodel, Marvin; Zimmermann, Alfred; Wagner, Stefan
Context. The microservices architectural style has revolutionized the way modern software systems are developed and operated. While the development of new microservices systems can leverage a wide range of resources and proven strategies, the migration of an existing monolithic system is not easily generalizable. Software architects look for guidance and predictable results in this highly individual process, in particular for generating a targeted, quality‐oriented, and semi‐automated decomposition.
Objective. To systematically guide software architects and developers in modernizing their software systems, we propose a holistic and quality‐oriented methodology to transform monolithic applications into microservices. Our work aims to provide industry‐relevant methods that address the gap between academia and practice by facilitating the transfer of knowledge.
Methods. In an overarching design science research process, we developed a framework that we implemented as a web‐based application. As a preliminary work, we conducted two initial interview studies with 25 software professionals to collect evidence on the intentions, strategies, and challenges in a migration process. An essential groundwork of our framework design constitute 110 scientific publications on approaches for architectural refactoring and migration to microservices, which we reviewed over four iterations. In a multifaceted evaluation with 26 participants, we examined our methodology's capability of providing actionable guidance for practitioners. This evaluation was complemented by two longitudinal case studies in an industrial context.
Results. We provide a framework for transforming monolithic applications to microservices, along with a dedicated quality assurance concept that supports a quality‐driven migration process. The evaluations among 19 software professionals showed an overall positive result in terms of effectiveness, usefulness, and usability. Two industrial case studies confirmed these promising results. Among practitioners, we discerned a need for flexibility, ease of use, and holistic guidance in a migration process. In this regard, we see potential to evolve our concept using artificial intelligence techniques for even more precise recommendations in a human‐like conversational dialog.
Deep reinforcement learning with instance-invariant baseline regularization for joint retrieval and relocation scheduling in multi-deep warehouses
(2026) Li, Funing; Zhou, Jifeng; Tian, Yuan; Noortwyck, Ruben; Ounissi, Aya; Hong, Bingyuan; Wen, Kai; Kang, Qi; Schulz, Robert
Multi-deep automated vehicle storage and retrieval systems (AVS/RS) offer high storage density, making them increasingly prevalent in modern logistics. However, their operational efficiency is often constrained by the need to relocate blocking items during retrieval. In this work, we consider a realistic scenario where only a subset of stored items is requested, and relocation naturally arises when target items are blocked by non-requested ones. We propose a deep reinforcement learning (DRL) framework for makespan minimization in multi-deep AVS/RS. The framework features a heterogeneous graph-based state representation that captures three distinct entity types (requested items, non-requested items, and empty locations) along with their structural relationships. The action space is designed to correspond to these node types, enabling the agent to handle both retrieval and relocation decisions within a unified framework. To address the high variance inherent in this problem, we propose the Instance-Invariant Baseline Regularization, which decouples the agent’s performance from the instance’s inherent complexity by deriving a computationally efficient lower bound for each state. Extensive experiments validate the effectiveness of the proposed approach. The agent trained with the proposed regularization demonstrates stable convergence and, more crucially, strong generalization across 64 unseen warehouse configurations of varying scale, consistently outperforming heuristic baselines. These results highlight the potential of DRL for intelligent decision-making in complex warehouse management problems.
Combined system of renewable heat supply and DAC based on the technical lime cycle
(2026) Klockow, Eva; Linder, Marc
A novel concept is proposed and analyzed, in which long-term thermochemical energy storage based on CaO is combined with direct air capture (DAC) by utilizing the carbonation of Ca(OH)2 under ambient conditions. With a theoretical heat storage density of approximately 320 kWh/t CaO and an intrinsic DAC functionality with a CO2 storage capacity of 44 wt%, the technical lime cycle offers two storage functions and thus promotes flexibility in energy networks with the goal to enable CO2-negative heat supply. Since CO2 uptake is the rate-determining step in the closed technical lime cycle, the parameters affecting the carbonation of powdered Ca(OH)2 are identified and analyzed to assess the feasibility of the proposed concept. Influence of CO2 concentration, layer thickness and air flow are experimentally investigated, each showing a dependency on the carbonation rate. With a 2.0 mm Ca(OH)2 layer, 72.3% carbonation could be achieved in 62 h. Based on these experimental results, initial system estimates indicate that with a hydration efficiency of 95%, 240 kWh of heat on demand, corresponding to the heating demand of an average week, require 0.78 t of CaO and could capture up to 430 kg CO2 from the atmosphere.
Additive manufacturing enabled annular μ-slit injection in low NOX jet-stabilised liquid fuel combustion
(2026) Kang, Yeonse; Lammel, Oliver; Ruf, Matthias; Steeb, Holger; Möhring, Hans-Christian; Hampp, Fabian
Advanced fuel injection systems are vital for improving combustion performance and reducing emissions in liquid-fuel-powered, high-momentum jet-stabilised combustion systems. This paper introduces an additively manufactured (AM) μ-scale annular slit injector with a nominal gap width of 50μm, realised by laser powder bed fusion in Inconel 718. μ-XRCT measurements confirm a manufacturable width of 52μm and reveal a transition towards statistically isotropic circumferential discharge at the slit exit. Compared with conventional dual airblast injection (AB), the μ-slit topology generates more uniformly fine droplets (d32 ≈ 10μm) and a markedly reduced radial asymmetry in fuel placement. The homogenised annular fuel discharge suppresses sectional bias and intermittency at the nozzle edge while enhancing fuel-air mixing, redistributing clustering length scales, and promoting more robust combustion across variations in jet velocity and fuel loading. Structural variants, e.g., μ-bumps and a low-swirler configuration, further modulate near-field multi-phase interaction and flame anchoring while enhancing overall flame homogeneity. This mixing-optimised stabilisation enhances the symmetry of the OH∗-marked heat-release structures and enables stable low-NOX combustion under lean atmospheric conditions. The injector operates with a comparatively low pressure drop with excellent reproducibility across all investigated mass flow rates, facilitating a wide dynamic operating range, yet heat transfer within the μ-channels under elevated preheating conditions requires further investigation. These results establish the AM μ-slit injector as a scalable low-emission architecture for compact, jet-stabilised micro gas turbine and hybrid aero-engine combustors.