Characterizing the weak organic acids used in low solids fluxes

The elimination of chlorofluorocarbons (CFCs) and other chlorinated cleaning solvents due to their long-term environmental impact has lead electronic assemblers to examine soldering fluxes that reduce or eliminate the need for post-solder cleaning. Today, low solids fluxes are replacing more traditional rosin-based and water-soluble fluxes because many of them can be used in a no-clean process. Most low solids fluxes use weak organic acids as active ingredient. It has been reported that some of these weak organic acids leave behind residues that are corrosive to copper. Surface Insulation Resistance (SIR) measurements of flux-processed comb patterns have been the main test method used to determine the corrosivity of flux residues. This test has been performed with test samples exposed to accelerated temperature and humidity conditions of 85°C and 85%RH and a 50 V bias. Recent data on some weak organic acids suggests that they slowly disappear at this temperature and a lower test temperature of 65°C has been introduced into the new Bellco Standard. In Europe, this test is normally performed at 40°C and 93% RH. This paper reports on the application of SIR tests to study the corrosive behavior of three carboxylic acids (succinic, glutaric, and adipic acids) that are commonly used as the active ingredients in soldering fluxes. Coupons treated with equi-molar solutions of the acids were either exposed to reflow-soldering conditions or wave soldered face-up to create partially heated residues. Both tests were run under two different accelerating conditions, 85°C/85%RH for 7 days or 40°C/93%RH for 20 days. This latter condition is being considered for inclusion in an IPC standard. At the end of the test period, both corrosion and SIR test samples were examined under a microscope and any residues or dendritic growth were documented. SEM and EDX characterization was also performed to determine the residue and dendrite composition.     

Temporal sequence detection with spiking neurons: towards recognizing robot language instructions

We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a new model of an integrate-and-fire neuron with active dendrites and dynamic synapses (ADDS) and its synaptic plasticity rule. The neuron employs the dynamics of the synapses and the active properties of the dendrites as an adaptive mechanism for maximizing its response to a specific spatio-temporal distribution of incoming action potentials. The learning algorithm follows recent biological evidence on synaptic plasticity. It goes beyond the current computational approaches which are based only on the relative timing between single pre- and post-synaptic spikes and implements a functional dependence based on the state of the dendritic and somatic membrane potentials around the pre- and post-synaptic action potentials. The learning algorithm is demonstrated to effectively train the neuron towards a selective response determined by the spatio-temporal pattern of the onsets of input spike trains. The model is used in the implementation of a part of a robotic system for natural language instructions. We test the model with a robot whose goal is to recognize and execute language instructions. The research in this article demonstrates the potential of spiking neurons for processing spatio-temporal patterns and the experiments present spiking neural networks as a paradigm which can be applied for modelling sequence detectors at word level for robot instructions.     

Hydrodynamic modeling of traffic jams in intracellular transport in axons

Irregularities in intracellular traffic in axons caused by mutations of molecular motors may lead to “traffic jams”, which often result in swelling of axons causing such neurodegenerative diseases as Alzheimer's disease and Down syndrome. Hence, it is of particular interest to mathematically model the formation of traffic jams in axons. This paper adopts the hydrodynamic continuity equations for intracellular transport of organelles as developed by Smith and Simmons [D.A. Smith, R.M. Simmons, Models of motor-assisted transport of intracellular particles, Biophysical Journal 80 (2001) 45–68.] whereas the Kerner and Konhäuser [B.S. Kerner, P. Konhäuser, Cluster effect in initially homogeneous traffic flow, Physical Review E 48 (1993), R2335–R2338.] model for traffic jams in highway traffic is applied to predict the velocity field. It is observed that combination of the two sets of equations can comprehensively predict the traffic jams in axons without the need to any additional assumption or modification.     

铝合金中孪生枝晶的研究进展

羽状晶是铸造组织中与柱状晶、等轴晶并列的第三类组织,在凝固理论研究和工业应用中有重要价值。近年来研究表明孪生枝晶是羽状晶最基本的微观组织特征。综述了孪生枝晶尖端形貌、增殖机制、与常规枝晶的竞争生长规律以及羽状晶力学性能等方面的研究进展,讨论了不同因素对孪生枝晶形成和生长的影响,总结了研究中尚未解决的问题。     

Hierarchical novel NiCo2O4/BiVO4 hybrid heterostructure as an advanced anode material for rechargeable lithium ion battery

Hybrid metal oxide heterostructures have been considered as ideal and potential anode materials for lithium ion batteries (LIBs) due to their better electrochemical performances, such as reversible capacity, structural stability and electronic conductivity. Herein, we have demonstrated synthesis of NiCo₂O₄/BiVO₄ heterostructures by simple hydrothermal strategy to construct hybrid xNiCo₂O₄/(1–x)BiVO₄ heterostructures with four selected compositions, that is, x = 10%, 20%, 30% and 40%. XRD shows the phases of NiCo₂O₄ and BiVO₄ and FE-SEM data revealed strong interface coupling between NiCo₂O₄ nanowires and BiVO₄ dendrites. Upon testing for electrochemical properties, the optimized composition of 30%NiCo₂O₄-70% BiVO₄ showed higher reversible capacity of 408.6 mAh/g at a constant current rate of 0.5 A/g after 1000 cycles with columbic efficiency around 99% suggesting potential electrode material for high-performance LIBs. The higher capacity is mainly attributed to the large surface area which can provide more channels and locations for fast Li ion intercalation/de-intercalation into electrode materials. Additionally, improved Li ion storage capacity with superior rate capability of BN-30 electrode could be attributed to its lower charge-transfer resistance. The dendritic and nanowire heterostructure novel system with good stable capacity for LIBs is hitherto unattempted.     

Tailoring Sodium Anodes for Stable Sodium–Oxygen Batteries

Sodium–oxygen batteries based on abundant sodium resource have caused increasing interest due to their high energy density and low cost. However, the reactive sodium anode always induces unpredictable side reactions especially in oxygen atmosphere and battery short circuit due to the uncontrolled formation of dendrites. Here, an accessible method to grow a durable protective passivation film on the surface of sodium anodes is reported. The sodium fluoride‐rich film efficiently suppresses O₂ crossover and electrolyte decay related side reactions on sodium anodes. Significantly, no dendrites form during long‐term stripping/plating cycles. Benefiting from these superiorities, sodium–oxygen batteries achieve impressive improvement of discharge–charge ability and reliable safety. These results enrich the approaches for stabilizing sodium anodes and allow researchers to focus on the investigations on the air cathode and the overall chemistry of sodium–oxygen batteries.     

Dendrites in Zn-Based Batteries

Aqueous Zn batteries that provide a synergistic integration of absolute safety and high energy density have been considered as highly promising energy-storage systems for powering electronics. Despite the rapid progress made in developing high-performance cathodes and electrolytes, the underestimated but non-negligible dendrites of Zn anode have been observed to shorten battery lifespan. Herein, this dendrite issue in Zn anodes, with regard to fundamentals, protection strategies, characterization techniques, and theoretical simulations, is systematically discussed. An overall comparison between the Zn dendrite and its Li and Al counterparts, to highlight their differences in both origin and topology, is given. Subsequently, in-depth clarifications of the specific influence factors of Zn dendrites, including the accumulation effect and the cathode loading mass (a distinct factor for laboratory studies and practical applications) are presented. Recent advances in Zn dendrite protection are then comprehensively summarized and categorized to generate an overview of respective superiorities and limitations of various strategies. Accordingly, theoretical computations and advanced characterization approaches are introduced as mechanism guidelines and measurement criteria for dendrite suppression, respectively. The concluding section emphasizes future challenges in addressing the Zn dendrite issue and potential approaches to further promoting the lifespan of Zn batteries.     

Novel Ag-Cu substrates for surface-enhanced Raman scattering

Ag dendrites were deposited on rough Cu plate by a simple galvanic displacement process between Ag ion and Cu under room temperature. Surface-enhanced Raman scattering (SERS) performances have been studied using Rhodamine 6G (R6G) probe molecules on this kind of Ag-Cu substrates. The high SERS enhancements are attributed to the highly branched Ag dendritic nanostructures and Ag nanoparticles formed on the trunks, branches, and even leaves.     

Modeling of retrograde nanoparticle transport in axons and dendrites

This paper presents a pioneering modeling study on nanoparticle internalization and transport in neurons. The model developed in this paper is based on recent experimental results that indicate that after entering a neurite by endocytosis, nanoparticles are transported toward the neuron soma in endocytic vesicles by retrograde molecular-motor-driven transport. Experimental results also indicate that nanoparticles enter axons at axon terminals while in dendrites they enter through the entire plasma membrane. The model equations developed in this paper are based on these experimental observations. The analytical solution of these equations is obtained; the solution predicts the distribution of the concentration of nanoparticles associated with free nanoparticle-loaded vesicles (NLVs) (not transported on microtubules (MTs)) as well as the distribution of the concentration of nanoparticles associated with NLVs transported on MTs by dynein motors. The fluxes of nanoparticles by diffusion and motor-driven transport as well as the total (combined) flux of nanoparticles are also predicted.