Hysteresis, force oscillations and non-equilibrium effects in the adhesion of spherical nanoparticles to atomically smooth surfaces

Molecular dynamics simulations are used to examine hysteretic effects and distinctions between equilibrium and non-equilibrium aspects of particle adsorption on the walls of nano-sized fluidfilled channels. The force on the particle and the system's Helmholtz free energy are found to depend on the particle's history as well as on its radial position and the wetting properties of the fluid, even when the particle's motion occurs on time scales much longer than the spontaneous adsorption time. The hysteresis is associated with changes in the fluid density in the gap between the particle and the wall, and these structural rearrangements persist over surprisingly long times. The force and free energy exhibit large oscillations with distance when the lattice of the structured nanoparticle is held in register with that of the tube wall, but not if the particle is allowed to rotate freely. Adsorbed particles are trapped in free energy minima in equilibrium, but if the particle is forced along the channel the resulting stick-slip motion alters the fluid structure and allows the particle to desorb

Thermal generation of spin current in epitaxial CoFe2O4 thin films

The longitudinal spin Seebeck effect (LSSE) has been investigated in high-quality epitaxial CoFe2O4 (CFO) thin films. The thermally excited spin currents in the CFO films are electrically detected in adjacent Pt layers due to the inverse spin Hall effect (ISHE). The LSSE signal exhibits a linear increase with increasing temperature gradient, yielding a LSSE coefficient of ~100 nV/K at room temperature. The temperature dependence of the LSSE is investigated from room temperature down to 30 K, showing a significant reduction at low temperatures, revealing that the total amount of thermally generated magnons decreases. Furthermore, we demonstrate that the spin Seebeck effect is an effective tool to study the magnetic anisotropy induced by epitaxial strain, especially in ultrathin films with low magnetic moments.Comment: 17 pages, 4 figure

Safe Exploration for Optimization with Gaussian Processes

We consider sequential decision problems under uncertainty, where we seek to optimize an unknown function from noisy samples. This requires balancing exploration (learning about the objective) and exploitation (localizing the maximum), a problem well-studied in the multi-armed bandit literature. In many applications, however, we require that the sampled function values exceed some prespecified "safety" threshold, a requirement that existing algorithms fail to meet. Examples include medical applications where patient comfort must be guaranteed, recommender systems aiming to avoid user dissatisfaction, and robotic control, where one seeks to avoid controls causing physical harm to the platform. We tackle this novel, yet rich, set of problems under the assumption that the unknown function satisfies regularity conditions expressed via a Gaussian process prior. We develop an efficient algorithm called SafeOpt, and theoretically guarantee its convergence to a natural notion of optimum reachable under safety constraints. We evaluate SafeOpt on synthetic data, as well as two real applications: movie recommendation, and therapeutic spinal cord stimulation

Structure of multicorrelation sequences with integer part polynomial iterates along primes

Let $T$ be a measure preserving $\mathbb{Z}^\ell$-action on the probability space $(X,{\mathcal B},\mu),$ $q_1,\dots,q_m:{\mathbb R}\to{\mathbb R}^\ell$ vector polynomials, and $f_0,\dots,f_m\in L^\infty(X)$. For any $\epsilon > 0$ and multicorrelation sequences of the form $\displaystyle\alpha(n)=\int_Xf_0\cdot T^{ \lfloor q_1(n) \rfloor }f_1\cdots T^{ \lfloor q_m(n) \rfloor }f_m\;d\mu$ we show that there exists a nilsequence $\psi$ for which $\displaystyle\lim_{N - M \to \infty} \frac{1}{N-M} \sum_{n=M}^{N-1} |\alpha(n) - \psi(n)| \leq \epsilon$ and $\displaystyle\lim_{N \to \infty} \frac{1}{\pi(N)} \sum_{p \in {\mathbb P}\cap[1,N]} |\alpha(p) - \psi(p)| \leq \epsilon.$ This result simultaneously generalizes previous results of Frantzikinakis [2] and the authors [11,13].Comment: 7 page

N′-Cyclo­dodecyl­idene­pyridine-4-carbohydrazide

The title compound, C18H27N3O, is a derivative of the anti­tuberculosis drug isoniazid (systematic name: pyridine-4-carbohydrazidei). The crystal structure consists of repeating C(4) chains along the b axis, formed by N—H⋯O hydrogen bonds with adjacent amide functional groups that are related by a b-glide plane. The cyclo­dodecyl ring has the same approximately ‘square’ conformation, as seen in the parent hydro­carbon cyclo­dodecane

Influence of thickness and interface on the low-temperature enhancement of the spin Seebeck effect in YIG films

The temperature dependent longitudinal spin Seebeck effect (LSSE) in heavy metal (HM)/Y3Fe5O12 (YIG) hybrid structures is investigated as a function of YIG film thickness, magnetic field strength, and different HM detection material. The LSSE signal shows a large enhancement with reducing the temperature, leading to a pronounced peak at low temperatures. We find the LSSE peak temperature strongly depends on the film thickness as well as on the magnetic field. Our result can be well explained in the framework of magnon-driven LSSE by taking into account the temperature dependent effective propagation length of thermally excited magnons in bulk. We further demonstrate that the LSSE peak is significantly shifted by changing the interface coupling to an adjacent detection layer, revealing a more complex behavior beyond the currently discussed bulk effect. By direct microscopic imaging of the interface, we correlate the observed temperature dependence with the interface structure between the YIG and the adjacent metal layer. Our results highlight the role of interface effects on the temperature dependent LSSE in HM/YIG system, suggesting that the temperature dependent spin current transparency strikingly relies on the interface conditions

Parallelizing Exploration-Exploitation Tradeoffs in Gaussian Process Bandit Optimization

How can we take advantage of opportunities for experimental parallelization in exploration-exploitation tradeoffs? In many experimental scenarios, it is often desirable to execute experiments simultaneously or in batches, rather than only performing one at a time. Additionally, observations may be both noisy and expensive. We introduce Gaussian Process Batch Upper Confidence Bound (GP-BUCB), an upper confidence bound-based algorithm, which models the reward function as a sample from a Gaussian process and which can select batches of experiments to run in parallel. We prove a general regret bound for GP-BUCB, as well as the surprising result that for some common kernels, the asymptotic average regret can be made independent of the batch size. The GP-BUCB algorithm is also applicable in the related case of a delay between initiation of an experiment and observation of its results, for which the same regret bounds hold. We also introduce Gaussian Process Adaptive Upper Confidence Bound (GP-AUCB), a variant of GP-BUCB which can exploit parallelism in an adaptive manner. We evaluate GP-BUCB and GP-AUCB on several simulated and real data sets. These experiments show that GP-BUCB and GP-AUCB are competitive with state-of-the-art heuristics