Unveiling the nature of atomic defects in graphene on a metal surface. - In: Beilstein journal of nanotechnology, ISSN 2190-4286, Bd. 15 (2024), S. 416-425
Low-energy argon ion bombardment of graphene on Ir(111) induces atomic-scale defects at the surface. Using a scanning tunneling microscope, the two smallest defects appear as a depression without discernible interior structure suggesting the presence of vacancy sites in the graphene lattice. With an atomic force microscope, however, only one kind can be identified as a vacancy defect with four missing carbon atoms, while the other kind reveals an intact graphene sheet. Spatially resolved spectroscopy of the differential conductance and the measurement of total-force variations as a function of the lateral and vertical probe–defect distance corroborate the different character of the defects. The tendency of the vacancy defect to form a chemical bond with the microscope probe is reflected by the strongest attraction at the vacancy center as well as by hysteresis effects in force traces recorded for tip approach to and retraction from the Pauli repulsion range of vertical distances.
https://doi.org/10.3762/bjnano.15.37
Adjustable robust energy operation planning under uncertain renewable energy production. - In: Energies, ISSN 1996-1073, Bd. 17 (2024), 8, 1917, S. 1-14
In this paper, the application of the method of affinely adjustable robust optimization to a planning model of an energy system under uncertain parameters is presented, and the total scheduling costs in comparison with the deterministic model are evaluated. First, the basics of optimization under uncertain data are recapped, and it is described how these methods can be used in different applications for energy systems. This is followed by the methodology of adjustable robust optimization by defining the affinely adjustable robust counterpart. Finally, a numerical case study is conducted to compare the adjustable robust method with a rolling deterministic scheduling method. Both are implemented on a model of an energy system and compared with each other by simulation using real-world data. By calculating the total operating costs for both methods, it can be concluded that the adjustable robust optimization provides a significantly more cost-effective solution to the scheduling problem.
https://doi.org/10.3390/en17081917
Chip-integrated non-mechanical microfluidic pump driven by electrowetting on dielectrics. - In: Lab on a chip, ISSN 1473-0189, Bd. 0 (2024), 0, insges. 13 S.
A microfluidic pump is presented that generates its pumping action via the EWOD (electrowetting-on-dielectric) effect. The flow is generated by the periodic movement of liquid-vapor interfaces in a large number (≈10^6) of microcavities resulting in a volume change of approx. 0.5 pl per cavity per pump stroke. The total flow resulting from all microcavities adds up to a few hundred nanolitres per cycle. Passive, topologically optimized, non-mechanical Tesla valves are used to rectify the flow. As a result, the micropump operates without any moving components. The dimensioning, fabrication, and characterization process of the micropump are described. Device fabrication is done using conventional manufacturing processes from microsystems technology, enabling cost-effective mass production on wafer-level without additional assembly steps like piezo chip-level bonding, etc. This allows for direct integration into wafer-based microfluidic or lab-on-a-chip applications. Furthermore, first measurement results obtained with prototypes of the micropump are presented. The voltage- and frequency-dependent pump performance is determined. The measurements show that a continuous flow rate larger than 0.2 ml min^−1 can be achieved at a maximum pump pressure larger than 12 mbar.
https://doi.org/10.1039/D4LC00178H
GraphLearner: an approach to sequence recognition and generation. - In: IEEE Xplore digital library, ISSN 2473-2001, (2024), S. 445-451
This paper presents GraphLearner a neuromorphic sequence generator with similarities to Markov Chain Models. GraphLearner is proposed as an alternative to ‘black box’ deep neural network models which lack explainability and adaptability. Bloom Filters are used to simplify otherwise computationally expensive Markov chain probability calculations. It is demonstrated with Natural Language Processing tasks, generating sentences of remarkable quality.
https://doi.org/10.1109/BigComp60711.2024.00098
The mystery of Carleson frames. - In: Applied and computational harmonic analysis, ISSN 1096-603X, Bd. 72 (2024), 101659, S. 1-5
In 2016 Aldroubi et al. constructed the first class of frames having the form {Tkφ}k=0∞ for a bounded linear operator on the underlying Hilbert space. In this paper we show that a subclass of these frames has a number of additional remarkable features that have not been identified for any other frames in the literature. Most importantly, the subfamily obtained by selecting each Nth element from the frame is itself a frame, regardless of the choice of N∈N. Furthermore, the frame property is kept upon removal of an arbitrarily finite number of elements.
https://doi.org/10.1016/j.acha.2024.101659
Exploring crystal-phase molecular dynamics of the low-viscous mesogen 6CHBT: a combined FFC and high-field NMR relaxometry investigation. - In: The journal of physical chemistry, ISSN 1520-5207, Bd. 128 (2024), 16, S. 3997-4007
The molecular dynamics study of thermotropic mesogens exhibiting the crystal phases is valuable in unraveling the complex global (collective) and local (noncollective) motions executed by liquid crystal molecules, which would further advance the existing knowledge on orientationally disordered crystalline (ODIC) phases. Toward the fulfillment of such a task, a combined nuclear magnetic resonance (NMR) relaxometry approach employing the fast field cycling (FFC) NMR (10 kHz-30 MHz) and high-field pulsed NMR (400 MHz) techniques is utilized to sample the broad frequency range offered by molecular motions in the crystal phase of 4-(trans-4′-n-hexylcyclohexyl)-isothiocyanatobenzene (6CHBT). The validity of the observed relaxation data is tested and interpreted by the Bloembergen-Purcell-Pound (BPP) model involving the superposition of four mutually independent Lorentzian spectral densities, reflecting molecular dynamical processes on different time scales. The salient feature of the detailed analysis reveals that the lengthening of temporal dynamics in the crystal phase due to molecular rotations by jumps, which are of intermolecular origin, is evident and further supports the presence of collective-like local dynamics. The analysis does permit decoupling of the molecular reorientations about their short axes (∼100 ns) as well as long axes (∼50 ns) and methyl group rotations (∼0.5 ns) on distinct time scales. The activation energies for reorientations about the short axes and methyl group rotations are found to be 27.3 ± 2.7 and 15.8 ± 1.1 kJ/mol, respectively. The fast methyl rotations in the crystal phase of 6CHBT obtained from FFC NMR are further well complemented by high-field NMR, where 1H NMR line shapes are relatively narrow when compared to those of the nematic phase.
https://doi.org/10.1021/acs.jpcb.3c08259
Flexible toolbox of high-precision microfluidic modules for versatile droplet-based applications. - In: Micromachines, ISSN 2072-666X, Bd. 15 (2024), 2, 250, S. 1-19
Although the enormous potential of droplet-based microfluidics has been successfully demonstrated in the past two decades for medical, pharmaceutical, and academic applications, its inherent potential has not been fully exploited until now. Nevertheless, the cultivation of biological cells and 3D cell structures like spheroids and organoids, located in serially arranged droplets in micro-channels, has a range of benefits compared to established cultivation techniques based on, e.g., microplates and microchips. To exploit the enormous potential of the droplet-based cell cultivation technique, a number of basic functions have to be fulfilled. In this paper, we describe microfluidic modules to realize the following basic functions with high precision: (i) droplet generation, (ii) mixing of cell suspensions and cell culture media in the droplets, (iii) droplet content detection, and (iv) active fluid injection into serially arranged droplets. The robustness of the functionality of the Two-Fluid Probe is further investigated regarding its droplet generation using different flow rates. Advantages and disadvantages in comparison to chip-based solutions are discussed. New chip-based modules like the gradient, the piezo valve-based conditioning, the analysis, and the microscopy module are characterized in detail and their high-precision functionalities are demonstrated. These microfluidic modules are micro-machined, and as the surfaces of their micro-channels are plasma-treated, we are able to perform cell cultivation experiments using any kind of cell culture media, but without needing to use surfactants. This is even more considerable when droplets are used to investigate cell cultures like stem cells or cancer cells as cell suspensions, as 3D cell structures, or as tissue fragments over days or even weeks for versatile applications.
https://doi.org/10.3390/mi15020250
Hot-pressing enhances mechanical strength of PEO solid polymer electrolyte for all-solid-state sodium metal batteries. - In: Small Methods, ISSN 2366-9608, Bd. 0 (2024), 0, 2301579, S. 1-9
Poly(ethylene oxide) (PEO)-based solid polymer electrolytes (SPEs) are widely utilized in all-solid-state sodium metal batteries (ASSSMBs) due to their excellent flexibility and safety. However, poor ionic conductivity and mechanical strength limit its development. In this work, an emerging solvent-free hot-pressing method is used to prepare mechanically robust PEO-based SPE, while sodium superionic conductors Na3Zr2Si2PO12 (NZSP) and NaClO4 are introduced to improve ionic conductivity. The as-prepared electrolyte exhibits a high ionic conductivity of 4.42 × 10−4 S cm−1 and a suitable electrochemical stability window (4.5 V vs Na/Na+). Furthermore, the SPE enables intimate contact with the electrode. The Na||Na3V2(PO4)3C ASSSMB delivers a high-capacity retention of 97.1% after 100 cycles at 0.5 C and 60 ˚C, and exhibits excellent Coulombic efficiency (CE) (close to 100%). The ASSSMB with the 20 µm thick electrolyte also demonstrates excellent cyclic stability. This study provides a promising strategy for designing stable polymer-ceramic composite electrolyte membranes through hot-pressing to realize high-energy-density sodium metal batteries.
https://doi.org/10.1002/smtd.202301579
Upgrading cycling stability and capability of hybrid Na-CO2 batteries via tailoring reaction environment for efficient conversion CO2 to HCOOH. - In: Advanced energy materials, ISSN 1614-6840, Bd. 14 (2024), 16, 2304365, S. 1-12
Rechargeable Na-CO2 batteries are considered to be an effective way to address the energy crisis and greenhouse effect due to their dual functions of CO2 fixation/utilization and energy storage. However, the insolubility and irreversibility of solid discharge products lead to poor discharge capacity and poor cycle performance. Herein, a novel strategy is proposed to enhance the electrochemical performance of hybrid Na-CO2 batteries, using water-in-salt electrolyte (WiSE) to establish an optimal reaction environment, regulate the CO2 reduction pathway, and ultimately convert the discharge product of the battery from Na2CO3 to formic acid (HCOOH). This strategy effectively resolves the issue of poor reversibility, allowing the battery to exhibit excellent cycle performance (over 1200 cycles at 30 ˚C), especially under low-temperature conditions (2534 cycles at −20 ˚C). Furthermore, density functional theory (DFT) calculations and experiments indicate that by adjusting the relative concentration of H/O atoms at the electrolyte/catalyst interface, the CO2 reduction pathway in the battery can be regulated, thus effectively enhancing CO2 capture capability and consequently achieving an ultra-high discharge specific capacity of 148.1 mAh cm−2. This work effectively promotes the practical application of hybrid Na-CO2 batteries and shall provide a guidance for converting CO2 into products with high-value-added chemicals.
https://doi.org/10.1002/aenm.202304365
Optimization of the bulk refractive index sensitivity of silver nanoprisms. - In: Advanced optical materials, ISSN 2195-1071, Bd. 0 (2024), 0, 2302967, S. 1-11
The sensitivity and optical properties of silver nanoprisms (triangular plates with round-truncated corners) are investigated in this paper. Results of boundary element method simulations are compared with experimental results and literature data. Based on electron microscopy images of the synthesized nanoprisms, a single-particle model is set up for simulations with three running parameters: edge length, thickness, and roundness (defined as the radius of the circumscribed circle divided by the edge length). These geometric parameters can be optimized during chemical synthesis to create sensors with improved sensitivity. The effect of biomolecular layers is also investigated. As a novel approach to improve the agreement between the simulated and experimentally measured extinction spectra, the single-particle model is extended to consider the variation of the prisms' parameters in the form of distributions. The resulting extinction cross-section spectra correspond well with the experimental data. The calculated bulk refractive index sensitivity is 670 nm/RIU (RIU stands for refractive index unit) for the single particle model (length = 150 nm, thickness = 10 nm, and roundness = 0.1), while (690 ± 5) nm/RIU for the extended model. The presented model and obtained relations between sensitivity and geometry can be effectively used to design and optimize the fabrication technologies for silver nanoprism-based sensing applications.
https://doi.org/10.1002/adom.202302967