Max Planck Institute for Dynamics and Self-Organization

Herein, recent experiments on the spectroscopy and chemical reactions of molecules and complexes embedded in helium droplets are reviewed. In the droplets, a high spectroscopic resolution, which is comparable to the gas phase is achieved, while an isothermal low-temperature environment is maintained by evaporative cooling at T =0.37 K (4He droplets) or 0.15 K (3He droplets), lower than possible in most solid matrices. Thus the helium-droplet technique combines the benefits of both the gas phase and the classical matrix-isolation techniques. Most important, the superfluid helium facilitates binary encounters, and absorbs the released binding energy upon recombination. Thus the droplet can be viewed as an isothermal nanoscopic reactor, which isolates single molecules, clusters, or even a single reactive encounter at ultralow temperatures.

BACKGROUND: Erythropoietin (EPO) and its receptor play a major role in embryonic brain, are weakly expressed in normal postnatal/adult brain and up-regulated upon metabolic stress. EPO protects neurons from hypoxic/ ischemic injury. The objective of this trial is to study the safety and efficacy of recombinant human EPO (rhEPO) for treatment of ischemic stroke in man. MATERIALS AND METHODS: The trial consisted of a safety part and an efficacy part. In the safety study, 13 patients received rhEPO intravenously (3.3 X 10(4) IU/50 ml/30 min) once daily for the first 3 days after stroke. In the double-blind randomized proof-of-concept trial, 40 patients received either rhEPO or saline. Inclusion criteria were age <80 years, ischemic stroke within the middle cerebral artery territory confirmed by diffusion-weighted MRI, symptom onset <8 hr before drug administration, and deficits on stroke scales. The study endpoints were functional outcome at day 30 (Barthel Index, modified Rankin scale), NIH and Scandinavian stroke scales, evolution of infarct size (sequential MRI evaluation using diffusion-weighted [DWI] and fluid-attenuated inversion recovery sequences [FLAIR]) and the damage marker S100ss. RESULTS: No safety concerns were identified. Cerebrospinal fluid EPO increased to 60-100 times that of nontreated patients, proving that intravenously administered rhEPO reaches the brain. In the efficacy trial, patients received rhEPO within 5 hr of onset of symptoms (median, range 2:40-7:55). Admission neurologic scores and serum S100beta concentrations were strong predictors ofoutcome. Analysis of covariance controlled for these two variables indicated that rhEPO treatment was associated with an improvement in follow-up and outcome scales. A strong trend for reduction in infarct size in rhEPO patients as compared to controls was observed by MRI. CONCLUSION: Intravenous high-dose rhEPO is well tolerated in acute ischemic stroke and associated with an improvement in clinical outcome at 1 month. A larger scale clinical trial is warranted.

Droplet based microfluidics is a rapidly growing interdisciplinary field of research combining soft matter physics, biochemistry and microsystems engineering. Its applications range from fast analytical systems or the synthesis of advanced materials to protein crystallization and biological assays for living cells. Precise control of droplet volumes and reliable manipulation of individual droplets such as coalescence, mixing of their contents, and sorting in combination with fast analysis tools allow us to perform chemical reactions inside the droplets under defined conditions. In this paper, we will review available drop generation and manipulation techniques. The main focus of this review is not to be comprehensive and explain all techniques in great detail but to identify and shed light on similarities and underlying physical principles. Since geometry and wetting properties of the microfluidic channels are crucial factors for droplet generation, we also briefly describe typical device fabrication methods in droplet based microfluidics. Examples of applications and reaction schemes which rely on the discussed manipulation techniques are also presented, such as the fabrication of special materials and biophysical experiments.

▪ Abstract This review summarizes results for Rayleigh-Bénard convection that have been obtained over the past decade or so. It concentrates on convection in compressed gases and gas mixtures with Prandtl numbers near one and smaller. In addition to the classical problem of a horizontal stationary fluid layer heated from below, it also briefly covers convection in such a layer with rotation about a vertical axis, with inclination, and with modulation of the vertical acceleration.

As coronavirus disease 2019 (COVID-19) is rapidly spreading across the globe, short-term modeling forecasts provide time-critical information for decisions on containment and mitigation strategies. A major challenge for short-term forecasts is the assessment of key epidemiological parameters and how they change when first interventions show an effect. By combining an established epidemiological model with Bayesian inference, we analyzed the time dependence of the effective growth rate of new infections. Focusing on COVID-19 spread in Germany, we detected change points in the effective growth rate that correlate well with the times of publicly announced interventions. Thereby, we could quantify the effect of interventions and incorporate the corresponding change points into forecasts of future scenarios and case numbers. Our code is freely available and can be readily adapted to any country or region.

It is shown that a certain class of self-affine profiles of surface roughness may render any substrate with a non-zero microscopic contact angle non-wet, i.e., give it a macroscopic contact angle close to 180 degrees. This is in some contrast to previous work and not only of potential applicational interest, but may also contribute to the amazing water repellency of some plant leaves.

Surface nanobubbles are nanoscopic gaseous domains on immersed substrates which can survive for days. They were first speculated to exist about 20 years ago, based on stepwise features in force curves between two hydrophobic surfaces, eventually leading to the first atomic force microscopy (AFM) image in 2000. While in the early years it was suspected that they may be an artifact caused by AFM, meanwhile their existence has been confirmed with various other methods, including through direct optical observation. Their existence seems to be paradoxical, as a simple classical estimate suggests that they should dissolve in microseconds, due to the large Laplace pressure inside these nanoscopic spherical-cap-shaped objects. Moreover, their contact angle (on the gas side) is much smaller than one would expect from macroscopic counterparts. This review will not only give an overview on surface nanobubbles, but also on surface nanodroplets, which are nanoscopic droplets (e.g., of oil) on (hydrophobic) substrates immersed in water, as they show similar properties and can easily be confused with surface nanobubbles and as they are produced in a similar way, namely, by a solvent exchange process, leading to local oversaturation of the water with gas or oil, respectively, and thus to nucleation. The review starts with how surface nanobubbles and nanodroplets can be made, how they can be observed (both individually and collectively), and what their properties are. Molecular dynamic simulations and theories to account for the long lifetime of the surface nanobubbles are then reported on. The crucial element contributing to the long lifetime of surface nanobubbles and nanodroplets is pinning of the three-phase contact line at chemical or geometric surface heterogeneities. The dynamical evolution of the surface nanobubbles then follows from the diffusion equation, Laplace's equation, and Henry's law. In particular, one obtains stable surface nanobubbles when the gas influx from the gas-oversaturated water and the outflux due to Laplace pressure balance. This is only possible for small enough surface bubbles. It is therefore the gas or oil oversaturation $\ensuremath{\zeta}$ that determines the contact angle of the surface nanobubble or nanodroplet and not the Young equation. The review also covers the potential technological relevance of surface nanobubbles and nanodroplets, namely, in flotation, in (photo)catalysis and electrolysis, in nanomaterial engineering, for transport in and out of nanofluidic devices, and for plasmonic bubbles, vapor nanobubbles, and energy conversion. Also given is a discussion on surface nanobubbles and nanodroplets in a nutshell, including theoretical predictions resulting from it and future directions. Studying the nucleation, growth, and dissolution dynamics of surface nanobubbles and nanodroplets will shed new light on the problems of contact line pinning and contact angle hysteresis on the submicron scale.

The Lagrangian description of turbulence is characterized by a unique conceptual simplicity and by an immediate connection with the physics of dispersion and mixing. In this article, we report some motivations behind the Lagrangian description of turbulence and focus on the statistical properties of particles when advected by fully developed turbulent flows. By means of a detailed comparison between experimental and numerical results, we review the physics of particle acceleration, Lagrangian velocity structure functions, and pairs and shapes evolution. Recent results for nonideal particles are discussed, providing an outlook on future directions.

We show that nonlinear optical structures involving a balanced gain-loss profile can act as unidirectional optical valves. This is made possible by exploiting the interplay between the fundamental symmetries of parity ($\mathcal{P}$) and time ($\mathcal{T}$), with optical nonlinear effects. This unidirectional dynamics is specifically demonstrated for the case of an integrable $\mathcal{PT}$-symmetric nonlinear system.

The synchronization of coupled oscillators is a fascinating manifestation of self-organization that nature uses to orchestrate essential processes of life, such as the beating of the heart. Although it was long thought that synchrony and disorder were mutually exclusive steady states for a network of identical oscillators, numerous theoretical studies in recent years have revealed the intriguing possibility of "chimera states," in which the symmetry of the oscillator population is broken into a synchronous part and an asynchronous part. However, a striking lack of empirical evidence raises the question of whether chimeras are indeed characteristic of natural systems. This calls for a palpable realization of chimera states without any fine-tuning, from which physical mechanisms underlying their emergence can be uncovered. Here, we devise a simple experiment with mechanical oscillators coupled in a hierarchical network to show that chimeras emerge naturally from a competition between two antagonistic synchronization patterns. We identify a wide spectrum of complex states, encompassing and extending the set of previously described chimeras. Our mathematical model shows that the self-organization observed in our experiments is controlled by elementary dynamical equations from mechanics that are ubiquitous in many natural and technological systems. The symmetry-breaking mechanism revealed by our experiments may thus be prevalent in systems exhibiting collective behavior, such as power grids, optomechanical crystals, or cells communicating via quorum sensing in microbial populations.

Inkjet printing is the most widespread technological application of microfluidics. It is characterized by its high drop productivity, small volumes, and extreme reproducibility. This review gives a synopsis of the fluid dynamics of inkjet printing and discusses the main challenges for present and future research. These lie both on the printhead side—namely, the detailed flow inside the printhead, entrained bubbles, the meniscus dynamics, wetting phenomena at the nozzle plate, and jet formation—and on the receiving substrate side—namely, droplet impact, merging, wetting of the substrate, droplet evaporation, and drying. In most cases the droplets are multicomponent, displaying rich physicochemical hydrodynamic phenomena. The challenges on the printhead side and on the receiving substrate side are interwoven, as optimizing the process and the materials with respect to either side alone is not enough: As the same ink (or other jetted liquid) is used and as droplet frequency and size matter on both sides, the process must be optimized as a whole.

Shear flows undergo a sudden transition from laminar to turbulent motion as the velocity increases, and the onset of turbulence radically changes transport efficiency and mixing properties. Even for the well-studied case of pipe flow, it has not been possible to determine at what Reynolds number the motion will be either persistently turbulent or ultimately laminar. We show that in pipes, turbulence that is transient at low Reynolds numbers becomes sustained at a distinct critical point. Through extensive experiments and computer simulations, we were able to identify and characterize the processes ultimately responsible for sustaining turbulence. In contrast to the classical Landau-Ruelle-Takens view that turbulence arises from an increase in the temporal complexity of fluid motion, here, spatial proliferation of chaotic domains is the decisive process and intrinsic to the nature of fluid turbulence.

Surfactants are an essential part of the droplet-based microfluidic technology. They are involved in the stabilization of droplet interfaces, in the biocompatibility of the system and in the process of molecular exchange between droplets. The recent progress in the applications of droplet-based microfluidics has been made possible by the development of new molecules and their characterizations. In this review, the role of the surfactant in droplet-based microfluidics is discussed with an emphasis on the new molecules developed specifically to overcome the limitations of ‘standard’ surfactants. Emulsion properties and interfacial rheology of surfactant-laden layers strongly determine the overall capabilities of the technology. Dynamic properties of droplets, interfaces and emulsions are therefore very important to be characterized, understood and controlled. In this respect, microfluidic systems themselves appear to be very powerful tools for the study of surfactant dynamics at the time- and length-scale relevant to the corresponding microfluidic applications. More generally, microfluidic systems are becoming a new type of experimental platform for the study of the dynamics of interfaces in complex systems.

In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking. Therefore, we analyzed highly parallel spike recordings from awake rats and monkeys, anesthetized cats, and also local field potentials from humans. We compared these to spiking activity from two established critical models: the Bak-Tang-Wiesenfeld model, and a stochastic branching model. We found fundamental differences between the neural and the model activity. These differences could be overcome for both models through a combination of three modifications: (1) subsampling, (2) increasing the input to the model (this way eliminating the separation of time scales, which is fundamental to SOC and its avalanche definition), and (3) making the model slightly sub-critical. The match between the neural activity and the modified models held not only for the classical avalanche size distributions and estimated branching parameters, but also for two novel measures (mean avalanche size, and frequency of single spikes), and for the dependence of all these measures on the temporal bin size. Our results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step. This implies that neural activity does not reflect a SOC state but a slightly sub-critical regime without a separation of time scales. Potential advantages of this regime may be faster information processing, and a safety margin from super-criticality, which has been linked to epilepsy.

Functional connectivity (FC) sheds light on the interactions between different brain regions. Besides basic research, it is clinically relevant for applications in Alzheimer's disease, schizophrenia, presurgical planning, epilepsy, and traumatic brain injury. Simulations of whole-brain mean-field computational models with realistic connectivity determined by tractography studies enable us to reproduce with accuracy aspects of average FC in the resting state. Most computational studies, however, did not address the prominent non-stationarity in resting state FC, which may result in large intra- and inter-subject variability and thus preclude an accurate individual predictability. Here we show that this non-stationarity reveals a rich structure, characterized by rapid transitions switching between a few discrete FC states. We also show that computational models optimized to fit time-averaged FC do not reproduce these spontaneous state transitions and, thus, are not qualitatively superior to simplified linear stochastic models, which account for the effects of structure alone. We then demonstrate that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks. Because of the noise-driven exploration of this repertoire, the dynamics of FC qualitatively change now and display non-stationary switching similar to empirical resting state recordings (Functional Connectivity Dynamics (FCD)). Thus FCD bear promise to serve as a better biomarker of resting state neural activity and of its pathologic alterations.

Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, we find only 17 unique networks are present in daily mobility and they follow simple rules. These networks, called here motifs, are sufficient to capture up to 90 per cent of the population in surveys and mobile phone datasets for different countries. Each individual exhibits a characteristic motif, which seems to be stable over several months. Consequently, daily human mobility can be reproduced by an analytically tractable framework for Markov chains by modelling periods of high-frequency trips followed by periods of lower activity as the key ingredient.

Somatic mutations within tumoral DNA can be used as highly specific biomarkers to distinguish cancer cells from their normal counterparts. These DNA biomarkers are potentially useful for the diagnosis, prognosis, treatment and follow-up of patients. In order to have the required sensitivity and specificity to detect rare tumoral DNA in stool, blood, lymph and other patient samples, a simple, sensitive and quantitative procedure to measure the ratio of mutant to wild-type genes is required. However, techniques such as dual probe TaqMan(®) assays and pyrosequencing, while quantitative, cannot detect less than ∼1% mutant genes in a background of non-mutated DNA from normal cells. Here we describe a procedure allowing the highly sensitive detection of mutated DNA in a quantitative manner within complex mixtures of DNA. The method is based on using a droplet-based microfluidic system to perform digital PCR in millions of picolitre droplets. Genomic DNA (gDNA) is compartmentalized in droplets at a concentration of less than one genome equivalent per droplet together with two TaqMan(®) probes, one specific for the mutant and the other for the wild-type DNA, which generate green and red fluorescent signals, respectively. After thermocycling, the ratio of mutant to wild-type genes is determined by counting the ratio of green to red droplets. We demonstrate the accurate and sensitive quantification of mutated KRAS oncogene in gDNA. The technique enabled the determination of mutant allelic specific imbalance (MASI) in several cancer cell-lines and the precise quantification of a mutated KRAS gene in the presence of a 200,000-fold excess of unmutated KRAS genes. The sensitivity is only limited by the number of droplets analyzed. Furthermore, by one-to-one fusion of drops containing gDNA with any one of seven different types of droplets, each containing a TaqMan(®) probe specific for a different KRAS mutation, or wild-type KRAS, and an optical code, it was possible to screen the six common mutations in KRAS codon 12 in parallel in a single experiment.

Robust synchronization (phase locking) of power plants and consumers centrally underlies the stable operation of electric power grids. Despite current attempts to control large-scale networks, even their uncontrolled collective dynamics is not fully understood. Here we analyze conditions enabling self-organized synchronization in oscillator networks that serve as coarse-scale models for power grids, focusing on decentralizing power sources. Intriguingly, we find that whereas more decentralized grids become more sensitive to dynamical perturbations, they simultaneously become more robust to topological failures. Decentralizing power sources may thus facilitate the onset of synchronization in modern power grids.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTPhotoemission from Liquid Aqueous SolutionsBernd Winter and Manfred FaubelView Author Information Max-Born-Institut für Nichtlineare Optik und Kurzzeitspektroskopie, Max-Born-Strasse 2A, D-12489 Berlin, Germany Max-Planck-Institut für Dynamik und Selbstorganisation, Bunsenstrasse 10, D-37073 Göttingen, Germany Cite this: Chem. Rev. 2006, 106, 4, 1176–1211Publication Date (Web):March 8, 2006Publication History Received9 August 2005Published online8 March 2006Published inissue 1 April 2006https://pubs.acs.org/doi/10.1021/cr040381phttps://doi.org/10.1021/cr040381presearch-articleACS PublicationsCopyright © 2006 American Chemical SocietyRequest reuse permissionsArticle Views4900Altmetric-Citations443LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Anions,Electrical energy,Liquids,Solution chemistry,Water Get e-Alerts

3,41Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany, 2Institute for Mathematical Optimization, Faculty of Mathematics, Otto-von-Guericke University Magdeburg, Magdeburg, Germany, 3Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum Mu¨nchen—German Research Center forEnvironmental Health, Neuherberg, Germany, 4Max Planck Institute for Dynamics and Self-Organization, Go¨ttingen, Germany