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Mathew, Sobin; Lebedev, Sergey P.; Lebedev, Alexander A.; Hähnlein, Bernd; Stauffenberg, Jaqueline; Udas, Kashyap; Jacobs, Heiko O.; Manske, Eberhard; Pezoldt, Jörg
Nanoscale surface morphology modulation of graphene - i-SiC heterostructures. - In: Materials today, ISSN 2214-7853, Bd. 53 (2022), 2, S. 289-292

A multitude gratings design consists of gratings with different pitches ranging from the micrometre down to sub 40 nm scale combined with sub 10 nm step heights modulating the surface morphology for length scale measurements is proposed. The surface morphology modulation was performed using electron beam lithography incorporating a standard semiconductor processing technology. The critical dimension, edge roughness, step heights and line morphology in dependence on the grating pitch is studied.



https://doi.org/10.1016/j.matpr.2021.06.427
Dong, Yulian; Yan, Chengzhan; Zhao, Huaping; Lei, Yong
Recent advances in 2D heterostructures as advanced electrode materials for potassium-ion batteries. - In: Small structures, ISSN 2688-4062, Bd. 3 (2022), 3, 2100221, insges. 19 S.

Owing to the cost-effectiveness, Earth abundance, and suitable redox potential, potassium-ion batteries (PIBs) stand out as one of the best candidates for large-scale energy storage systems. However, the large radius of K+ and the unsatisfied specific capacity are the main challenges for their commercial applications. To address these challenges, constructing heterostructures by selecting and integrating 2D materials as host and other materials as guest are proposed as an emerging strategy to obtain electrode materials with high capacity and long lifespan, thus improving the energy storage capability of PIBs. Recently, numerous studies are devoted to developing 2D-based heterostructures as electrode materials for PIBs, and significant progress is achieved. However, there is a lack of a review article for systematically summarizing the recent advances and profoundly understanding the relationship between heterostructure electrodes and their performance. In this sense, it is essential to outline the promising advanced features, to summarize the electrochemical properties and performances, and to discuss future research focuses about 2D-based heterostructures in PIBs.



https://doi.org/10.1002/sstr.202100221
Hülser, Tobias; Köster, Felix; Jaurigue, Lina; Lüdge, Kathy
Role of delay-times in delay-based photonic reservoir computing. - In: Optical materials express, ISSN 2159-3930, Bd. 12 (2022), 3, S. 1214-1231

Delay-based reservoir computing has gained a lot of attention due to the relative simplicity with which this concept can be implemented in hardware. However, unnecessary constraints are commonly placed on the relationship between the delay-time and the input clock-cycle, which can have a detrimental effect on the performance. We review the existing literature on this subject and introduce the concept of delay-based reservoir computing in a manner that demonstrates that no predefined relationship between the delay-time and the input clock-cycle is required for this computing concept to work. Choosing the delay-times independent of the input clock-cycle, one gains an important degree of freedom. Consequently, we discuss ways to improve the computing performance of a reservoir formed by delay-coupled oscillators and show the impact of delay-time tuning in such systems.



https://doi.org/10.1364/OME.451016
Karmo, Marsel; Ruiz Alvarado, Isaac Azahel; Schmidt, W. Gero; Runge, Erich
Reconstructions of the As-terminated GaAs(001) surface exposed to atomic hydrogen. - In: ACS omega, ISSN 2470-1343, Bd. 7 (2022), 6, S. 5064-5068

We explore the atomic structures and electronic properties of the As-terminated GaAs(001) surface in the presence of hydrogen based on ab initio density functional theory. We calculate a phase diagram dependent on the chemical potentials of As and H, showing which surface reconstruction is the most stable for a given set of chemical potentials. The findings are supported by the calculation of energy landscapes of the surfaces, which indicate possible H bonding sites as well as the density of states, which show the effect of hydrogen adsorption on the states near the fundamental band gap.



https://doi.org/10.1021/acsomega.1c06019
Gao, Yueyue; Cui, Minghuan; Qu, Shengchun; Zhao, Huaping; Shen, Zhitao; Tan, Furui; Dong, Yulian; Qin, Chaochao; Wang, Zhijie; Zhang, Weifeng; Wang, Zhangguo; Lei, Yong
Efficient organic solar cells enabled by simple non-fused electron donors with low synthetic complexity. - In: Small, ISSN 1613-6829, Bd. 18 (2022), 3, 2104623, insges. 10 S.

https://doi.org/10.1002/smll.202104623
Jaurigue, Lina; Lüdge, Kathy
Connecting reservoir computing with statistical forecasting and deep neural networks. - In: Nature Communications, ISSN 2041-1723, Bd. 13 (2022), 227, S. 1-3

Among the existing machine learning frameworks, reservoir computing demonstrates fast and low-cost training, and its suitability for implementation in various physical systems. This Comment reports on how aspects of reservoir computing can be applied to classical forecasting methods to accelerate the learning process, and highlights a new approach that makes the hardware implementation of traditional machine learning algorithms practicable in electronic and photonic systems.



https://doi.org/10.1038/s41467-021-27715-5
Li, Yangguang; Yan, Chengzhan; Chen, Xuan; Lei, Yong; Ye, Bang-Ce
A highly robust self-supporting nickel nanoarray based on anodic alumina oxide template for determination of dopamine. - In: Sensors and actuators, ISSN 0925-4005, Bd. 350 (2022), 130835

Ratiometric electrochemical sensors can effectively reduce system errors and environmental interference during the detection of a target, affording good sensitivity, reproducibility, and a linear response range. However, traditional proportional electrochemical sensors are limited by the need for complex modifications and the lack of internal reference probes. In this study, we developed a ratiometric electrochemical sensing platform based on nickel nanoarrays as a self-supporting electrode (NiNASSE) by using an anodic alumina oxide template method. An internal reference probe was developed based on nickel nanoparticles (NiNPs) as nickel nanoarrays, presenting a facile modification process and stable redox signal. Furthermore, the highly ordered nanoarray structure expands the specific surface area of NiNASSE and accelerates the electron transfer rate. This new self-supporting proportional electrochemical sensor was successfully applied for the detection of dopamine and displayed good electrocatalytic ability, stability, and feasibility.



https://doi.org/10.1016/j.snb.2021.130835
Zhou, Yujia; Wang, Zidong; Zheng, Chunfang; Fu, Qun; Wu, Minghong; Zhao, Huaping; Lei, Yong
Construction of Co0.85Se@nickel nanopores array hybrid electrode for high-performance asymmetric supercapacitors. - In: Chemical engineering science, Bd. 247 (2022), 117081, insges. 9 S.

Nanostructured current collectors have larger specific surface area and short ion/electron transport path, which are highly desirable for supercapacitors applications. Herein, Co0.85SeNiNPs (Co0.85Se@NiNP) hybrid electrodes are proposed and fabricated, in which NiNP is served as nanostructured current collectors. NiNP has a vertical pore structure and a large specific surface area, which could effectively promote the ion/electron transport efficiency and reduce internal electrical resistance. Compared with Ni foam and Ni foil as current collectors, NiNP enables Co0.85Se@NiNP electrodes show significantly improved specific capacity, rate performance and cycle stability. Finally, an asymmetric supercapacitor device was assembled with Co0.85Se@NiNP hybrid electrode as the binder-free positive electrode and activated carbon (AC) coated on nickel foam as negative electrode. The Co0.85Se@NiNP//AC asymmetric supercapacitors can work in a wide potential window of 0 - 1.6 V with an ultrahigh specific capacity of 182.3 F g^-1 at 1 A g^-1. Most importantly, Co0.85Se@NiNP//AC has a high energy density of 64.81 Wh kg^-1 at 800 W kg^-1 and an outstanding cycle stability of up to 12000 cycles, indicating that Co0.85Se@NiNP electrode has great application potential in supercapacitors.



https://doi.org/10.1016/j.ces.2021.117081
Wu, Yanjie; Yang, Huaqin; Li, Wei; Mattea, Carlos; Stapf, Siegfried; Zhang, Letian; Ye, Chunlin; Ye, Xiaofeng
Tailored crystalline order of nascent polyethylene from metallocene supported on confined polystyrene. - In: Catalysis today, ISSN 1873-4308, Bd. 368 (2021), S. 272-280

Building the desirable superstructure of polyethylene is one of the important topics for developing high value-added products, which brings potential benefits for society and sustainable development. Crystalline order is the ubiquitous superstructure for enhancing mechanical properties of polymeric materials. In this work, polystyrene copolymers (c-PS) are incorporated into pores of silica through the wet-impregnation procedure of styrene and p-chloromethyl styrene followed by the in-situ free-radical copolymerization. Metallocene catalyst is further immobilized on supported silica. This incorporated c-PS is proved to be coated on the surface of silica pore walls rather than blocking the interparticle channels. The swelling behavior of c-PS inside the pores are performed by pulsed field gradient NMR (PFG-NMR) and thermoporosimetry (TPM-DSC), where a swelling behavior is shown in the toluene owing to the matched solubility parameters between the c-PS and toluene. According to the swelling behavior of c-PS confined in the pores, a compartmentalization is created hindering the formation of chain overlaps and increasing the crystallinity order of nascent polymers. As a result, the nascent polyethylene with a high crystallinity (i.e., bulk crystallinity Xc,DSC=72.9 % and linear crystallinity Xc,WAXD=90.5 %) is synthesized. There is a considerable activity (i.e., 3.8×106 g PE&hahog;(molZr&hahog;h)^-1) at 70˚C. Finally, the particle morphology of the nascent polyethylene is investigated based on the swelling behavior of c-PS.



https://doi.org/10.1016/j.cattod.2019.12.032
Selzer, Silas Aaron; Bauer, Fabian; Bohm, Sebastian; Bretschneider, Peter; Runge, Erich
Physik-geführte NARXnets (PGNARXnets) zur Zeitreihenvorhersage. - In: Proceedings 31. Workshop Computational Intelligence, (2021), S. 235-261