Manipulation and control of droplets on surfaces in a homogeneous electric field

A method to manipulate and control droplets on a surface is presented. The method is based on inducing electric dipoles inside the droplets using a homogeneous external electric field. It is shown that the repulsive dipole force efficiently suppresses the coalescence of droplets moving on a liquid-infused surface (LIS). Using a combination of experiments, numerical computations and semi-analytical models, the dependence of the repulsion force on the droplet volumes, the distance between the droplets and the electric field strength is revealed. The method allows to suppress coalescence in complex multi-droplet flows and is real-time adaptive. When the electric field strength exceeds a critical value, tip streaming from the droplets sets in. Based on that, it becomes possible to withdraw minute samples from an array of droplets in a parallel process.

Heated Assembly and Transfer of Van der Waals Heterostructures with Common Nail Polish

Recent advances in the manipulation and control of layered, two-dimensional materials has given way to the construction of heterostructures with new functionality and unprecedented electronic properties. In this study, we present a simple technique to assemble and transfer van der Waals heterostructures using common nail polish. Commercially available nail polish acts as a resilient sticky polymer, allowing for the fabrication of complex multi-material stacks without noticeable fatigue. Directly comparing four commercially available brands of nail polish, we find that one stands out in terms of stability and stacking characteristics. Using this method, we fabricate two top-gated devices and report their electrical properties. Our technique reduces the complexity in assembling van der Waals heterostructures based on the proven van der Waals pick up method.

Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review

Deep learning has provided new ways of manipulating, processing and analyzing data. It sometimes may achieve results comparable to, or surpassing human expert performance, and has become a source of inspiration in the era of artificial intelligence. Another subfield of machine learning named reinforcement learning, tries to find an optimal behavior strategy through interactions with the environment. Combining deep learning and reinforcement learning permits resolving critical issues relative to the dimensionality and scalability of data in tasks with sparse reward signals, such as robotic manipulation and control tasks, that neither method permits resolving when applied on its own. In this paper, we present recent significant progress of deep reinforcement learning algorithms, which try to tackle the problems for the application in the domain of robotic manipulation control, such as sample efficiency and generalization. Despite these continuous improvements, currently, the challenges of learning robust and versatile manipulation skills for robots with deep reinforcement learning are still far from being resolved for real-world applications.

Manipulation and Control of Molecular Beams: The Development of the Stark-Decelerator

State-selective manipulation of beams of atoms and molecules with electric and magnetic fields has been crucial for the success of the field of molecular beams. Originally, this manipulation only involved the transverse motion. In this Chapter, the development of the Stark-decelerator, that allows to also manipulate and control the longitudinal motion of molecules in a beam, is presented.

Dystopian World of Ray Bradbury's Fahrenheit 451

Ray Bradbury explores in his dystopian novel Fahrenheit 451 (henceforth F451), the destructive side of technology and totalitarianism, which can deny individuals of their basic rights. This article gives a critical, contextual analysis of F451(1953) by Ray Bradbury. It investigates the dystopian elements to show how an authoritarian government projected in the novel that blocks mind and awareness. The protagonist of the novel is Guy Montag who takes a key role in revealing the tyrannical system and the potential consequences of disobedience. This article examines the manipulation and control of the state and its ill use of technology and its banning of books to shackle knowledge and mind. However, this article aims to show the effect of autobiographical elements, McCarthyism's censorship and the fear of communism during the postwar era and their effects on writing the novel. It also shows how in this dystopian world, an oppressive government is not successful in controlling all citizens. There are opposing characters whose consciousness is awakened and they are successful to show the failure of the system although they are becoming lonely outsiders by that system. The literature review has paved the way by providing the theoretical basis for the analysis of the novel. Thus, this short study sheds the light on how the totalitarian state affects Montag’s change, but it is demonstrating the dystopian world of the novel.

LexOPS: An R package and user interface for the controlled generation of word stimuli

LexOPS is an R package and user interface designed to facilitate the generation of word stimuli for use in research. Notably, the tool permits the generation of suitably controlled word lists for any user-specified factorial design and can be adapted for use with any language. It features an intuitive graphical user interface, including the visualization of both the distributions within and relationships among variables of interest. An inbuilt database of English words is also provided, including a range of lexical variables commonly used in psycholinguistic research. This article introduces LexOPS, outlining the features of the package and detailing the sources of the inbuilt dataset. We also report a validation analysis, showing that, in comparison to stimuli of existing studies, stimuli optimized with LexOPS generally demonstrate greater constraint and consistency in variable manipulation and control. Current instructions for installing and using LexOPS are available at https://JackEdTaylor.github.io/LexOPSdocs/.

Insights in Magnetodynamics from a Simple Two-Level Model

With single-molecule magnets research on the rise as a result of recent advantages in the field, like remarkable high blocking temperatures up to 60 Kelvin [Nature, 548, 439, 2017], gigantic coercivity up to 80 Tesla [Nat Commun., 10, 571, 2019], magnetization stability in the thin films, further applications are seriously in the scope. The possible venue here is to develop a theory of magnetic moment manipulation and control at the microscopic level. Theory of optimal control in quantum dynamics in complex systems is well-developed. For example, the uses of density matrix techniques have been well summarized already in the early ‘60s by Fano, Haar, and many others. Thus, in many respects, the task is to reframe that research into the language of the problem at hand, and into familiar terms for the community. Recently, it was already proven the Redfield reduced density matrix techniques are applicable for slow-relaxing single-molecule magnets [Nat Commun., 8, 14620, 2017]. In our recent contribution[PCCP,20, 11656, 2018], we have outlined the use of Lindblad dynamics in combination with a few axioms in the rationalization of the relaxation behavior of single-molecule magnets. In this report we put this approach in the context of the magentodynamics theory, showing the close connection to the Landau-Lifshitz-Gilbert model and presenting further elaboration for the proposed method.

Insights in Magnetodynamics from a Simple Two-Level Model

With single-molecule magnets research on the rise as a result of recent advantages in the field, like remarkable high blocking temperatures up to 60 Kelvin [Nature, 548, 439, 2017], gigantic coercivity up to 80 Tesla [Nat Commun., 10, 571, 2019], magnetization stability in the thin films, further applications are seriously in the scope. The possible venue here is to develop a theory of magnetic moment manipulation and control at the microscopic level. Theory of optimal control in quantum dynamics in complex systems is well-developed. For example, the uses of density matrix techniques have been well summarized already in the early ‘60s by Fano, Haar, and many others. Thus, in many respects, the task is to reframe that research into the language of the problem at hand, and into familiar terms for the community. Recently, it was already proven the Redfield reduced density matrix techniques are applicable for slow-relaxing single-molecule magnets [Nat Commun., 8, 14620, 2017]. In our recent contribution[PCCP,20, 11656, 2018], we have outlined the use of Lindblad dynamics in combination with a few axioms in the rationalization of the relaxation behavior of single-molecule magnets. In this report we put this approach in the context of the magentodynamics theory, showing the close connection to the Landau-Lifshitz-Gilbert model and presenting further elaboration for the proposed method.