Search Results
Micromotor-mediated sperm constrictions for improved swimming performance
Sperm-driven micromotors, consisting of a single sperm cell captured in a microcap, utilize the strong propulsion generated by the flagellar beat of motile spermatozoa for locomotion. It enables the movement of such micromotors in biological media, while being steered remotely by means of an external magnetic field. The substantial decrease in swimming speed, caused by the additional hydrodynamic load of the microcap, limits the applicability of sperm-based micromotors. Therefore, to improve the performance of such micromotors, we first investigate the effects of additional cargo on the flagellar beat of spermatozoa. We designed two different kinds of microcaps, which each result in different load responses of the flagellar beat. As an additional design feature, we constrain rotational degrees of freedom of the cell’s motion by modifying the inner cavity of the cap. Particularly, cell rolling is substantially reduced by tightly locking the sperm head inside the microcap. Likewise, cell yawing is decreased by aligning the micromotors under an external static magnetic field. The observed differences in swimming speed of different micromotors are not so much a direct consequence of hydrodynamic effects, but rather stem from changes in flagellar bending waves, hence are an indirect effect. Our work serves as proof-of-principle that the optimal design of microcaps is key for the development of efficient sperm-driven micromotors.
Orders of magnitude loss reduction in photonic bandgap fibers by engineering the core surround
We demonstrate how to reduce the loss in photonic bandgap fibers by orders of magnitude by varying the radius of the corner strands in the core surround. As a fundamental working principle we find that changing the corner strand radius can lead to backscattering of light into the fiber core. Selecting an optimal corner strand radius can thus reduce the loss of the fundamental core mode in a specific wavelength range by almost two orders of magnitude when compared to an unmodified cladding structure. Using the optimal corner radius for each transmission window, we observe the low-loss behavior for the first and second bandgaps, with the losses in the second bandgap being even lower than that of the first one. Our approach of reducing the confinement loss is conceptually applicable to all kinds of photonic bandgap fibers including hollow core and all-glass fibers as well as on-chip light cages. Therefore, our concept paves the way to low-loss light guidance in such systems with substantially reduced fabrication complexity.
Bioactive glass–ceramics containing fluorapatite, xonotlite, cuspidine and wollastonite form apatite faster than their corresponding glasses
Crystallisation of bioactive glasses has been claimed to negatively affect the ion release from bioactive glasses. Here, we compare ion release and mineralisation in Tris–HCl buffer solution for a series of glass–ceramics and their parent glasses in the system SiO2–CaO–P2O5–CaF2. Time-resolved X-ray diffraction analysis of glass–ceramic degradation, including quantification of crystal fractions by full pattern refinement, show that the glass–ceramics precipitated apatite faster than the corresponding glasses, in agreement with faster ion release from the glass–ceramics. Imaging by transmission electron microscopy and X-ray nano-computed tomography suggest that this accelerated degradation may be caused by the presence of nano-sized channels along the internal crystal/glassy matrix interfaces. In addition, the presence of crystalline fluorapatite in the glass–ceramics facilitated apatite nucleation and crystallisation during immersion. These results suggest that the popular view of bioactive glass crystallisation being a disadvantage for degradation, apatite formation and, subsequently, bioactivity may depend on the actual system study and, thus, has to be reconsidered.
Research data management in agricultural sciences in Germany: We are not yet where we want to be
To meet the future challenges and foster integrated and holistic research approaches in agricultural sciences, new and sustainable methods in research data management (RDM) are needed. The involvement of scientific users is a critical success factor for their development. We conducted an online survey in 2020 among different user groups in agricultural sciences about their RDM practices and needs. In total, the questionnaire contained 52 questions on information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in RDM in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. We received 196 (partially) completed questionnaires from data providers, data users, infrastructure and information service providers. In addition to the diversity in the research data landscape of agricultural sciences in Germany, the study reveals challenges, deficits and uncertainties in handling research data in agricultural sciences standing in the way of access and efficient reuse of valuable research data. However, the study also suggests and discusses potential solutions to enhance data publications, facilitate and secure data re-use, ensure data quality and develop services (i.e. training, support and bundling services). Therefore, our research article provides the basis for the development of common RDM, future infrastructures and services needed to foster the cultural change in handling research data across agricultural sciences in Germany and beyond.
Strong and ductile high temperature soft magnets through Widmanstätten precipitates
Fast growth of sustainable energy production requires massive electrification of transport, industry and households, with electrical motors as key components. These need soft magnets with high saturation magnetization, mechanical strength, and thermal stability to operate efficiently and safely. Reconciling these properties in one material is challenging because thermally-stable microstructures for strength increase conflict with magnetic performance. Here, we present a material concept that combines thermal stability, soft magnetic response, and high mechanical strength. The strong and ductile soft ferromagnet is realized as a multicomponent alloy in which precipitates with a large aspect ratio form a Widmanstätten pattern. The material shows excellent magnetic and mechanical properties at high temperatures while the reference alloy with identical composition devoid of precipitates significantly loses its magnetization and strength at identical temperatures. The work provides a new avenue to develop soft magnets for high-temperature applications, enabling efficient use of sustainable electrical energy under harsh operating conditions.
Anharmonic strong-coupling effects at the origin of the charge density wave in CsV3Sb5
The formation of charge density waves is a long-standing open problem, particularly in dimensions higher than one. Various observations in the vanadium antimonides discovered recently further underpin this notion. Here, we study the Kagome metal CsV3Sb5 using polarized inelastic light scattering and density functional theory calculations. We observe a significant gap anisotropy with 2Δmax/kBTCDW≈20, far beyond the prediction of mean-field theory. The analysis of the A1g and E2g phonons, including those emerging below TCDW, indicates strong phonon-phonon coupling, presumably mediated by a strong electron-phonon interaction. Similarly, the asymmetric Fano-type lineshape of the A1g amplitude mode suggests strong electron-phonon coupling below TCDW. The large electronic gap, the enhanced anharmonic phonon-phonon coupling, and the Fano shape of the amplitude mode combined are more supportive of a strong-coupling phonon-driven charge density wave transition than of a Fermi surface instability or an exotic mechanism in CsV3Sb5.
Characterizing the sectoral development of cities
Previous research has identified a predictive model of how a nation’s distribution of gross domestic product (GDP) among agriculture (a), industry (i), and services (s) changes as a country develops. Here we use this national model to analyze the composition of GDP for US Metropolitan Statistical Areas (MSA) over time. To characterize the transfer of GDP shares between the sectors in the course of economic development we explore a simple system of differential equations proposed in the country-level model. Fitting the model to more than 120 MSAs we find that according to the obtained parameters MSAs can be classified into 6 groups (consecutive, high industry, re-industrializing; each of them also with reversed development direction). The consecutive transfer (a → i → s) is common but does not represent all MSAs examined. At the 95% confidence level, 40% of MSAs belong to types exhibiting an increasing share of GDP from agriculture. In California, such MSAs, which we classify as part of an agriculture renaissance, are found in the Central Valley.
Evolutionary design of explainable algorithms for biomedical image segmentation
An unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histopathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches.
Two-color two-dimensional terahertz spectroscopy: A new approach for exploring even-order nonlinearities in the nonperturbative regime
Nonlinear two-dimensional terahertz (2D-THz) spectroscopy at frequencies of the emitted THz signal different from the driving frequencies allows for exploring the regime of (off-)resonant even-order nonlinearities in condensed matter. To demonstrate the potential of this method, we study two phenomena in the nonlinear THz response of bulk GaAs: (i) The nonlinear THz response to a pair of femtosecond near-infrared pulses unravels novel fourth- and sixth-order contributions involving interband shift currents, Raman-like excitations of transverse-optical phonon and intervalence-band coherences. (ii) Transient interband tunneling of electrons driven by ultrashort mid-infrared pulses can be effectively controlled by a low-frequency THz field with amplitudes below 50 kV/cm. The THz field controls the electron–hole separation modifying decoherence and the irreversibility of carrier generation.
Ultrafast vibrational control of organohalide perovskite optoelectronic devices using vibrationally promoted electronic resonance
Vibrational control (VC) of photochemistry through the optical stimulation of structural dynamics is a nascent concept only recently demonstrated for model molecules in solution. Extending VC to state-of-the-art materials may lead to new applications and improved performance for optoelectronic devices. Metal halide perovskites are promising targets for VC due to their mechanical softness and the rich array of vibrational motions of both their inorganic and organic sublattices. Here, we demonstrate the ultrafast VC of FAPbBr3 perovskite solar cells via intramolecular vibrations of the formamidinium cation using spectroscopic techniques based on vibrationally promoted electronic resonance. The observed short (~300 fs) time window of VC highlights the fast dynamics of coupling between the cation and inorganic sublattice. First-principles modelling reveals that this coupling is mediated by hydrogen bonds that modulate both lead halide lattice and electronic states. Cation dynamics modulating this coupling may suppress non-radiative recombination in perovskites, leading to photovoltaics with reduced voltage losses.