Tin whisker mitigation by means of a postelectroplating electrochemical oxidation treatment

There are very few studies that have investigated directly the effect of an oxide film on tin whisker growth, since the ‘cracked oxide theory’ was proposed by Tu in 19941. The current study has investigated the effect of an electrochemically produced oxide on tin whisker growth, for both Sn-Cu electrodeposits on Cu and pure Sn electrodeposits on brass. X-ray photoelectron spectroscopy (XPS) has been used to investigate the effect of the applied electrochemical oxidation potential on the oxide film thickness. Focused ion beam (FIB) has been used to prepare cross sections from electrodeposited samples to investigate the influence of the electrochemically formed oxide film on deposit microstructure during long-term room temperature storage. The XPS studies show that the thickness of electrochemically formed oxide film is directly influenced by the applied potential and the total charge passed. Whisker growth studies show that the electrochemical oxidation treatment mitigates whisker growth for both Sn-Cu electrodeposits on Cu and pure Sn electrodeposits on brass. For Sn electrodeposits on brass, the electrochemically formed oxide greatly reduces both the formation of zinc oxide at the surface and the formation of intermetallic compounds, which results in the mitigation of tin whisker growth. For Sn-Cu electrodeposits on Cu, the electrochemically formed oxide has no apparent effect on intermetallic compound formation and acts simply as a physical barrier to hinder tin whisker growth

Learning probabilistic models of hydrogen bond stability from molecular dynamics simulation trajectories

Hydrogen bonds (H-bonds) play a key role in both the formation and stabilization of protein structures. H-bonds involving atoms from residues that are close to each other in the main-chain sequence stabilize secondary structure elements. H-bonds between atoms from distant residues stabilize a protein’s tertiary structure. However, H-bonds greatly vary in stability. They form and break while a protein deforms. For instance, the transition of a protein from a nonfunctional to a functional state may require some H-bonds to break and others to form. The intrinsic strength of an individual H-bond has been studied from an energetic viewpoint, but energy alone may not be a very good predictor. Other local interactions may reinforce (or weaken) an H-bond. This paper describes inductive learning methods to train a protein-independent probabilistic model of H-bond stability from molecular dynamics (MD) simulation trajectories. The training data describes H-bond occurrences at successive times along these trajectories by the values of attributes called predictors. A trained model is constructed in the form of a regression tree in which each non-leaf node is a Boolean test (split) on a predictor. Each occurrence of an H-bond maps to a path in this tree from the root to a leaf node. Its predicted stability is associated with the leaf node. Experimental results demonstrate that such models can predict H-bond stability quite well. In particular, their performance is roughly 20 % better than that of models based on H-bond energy alone. In addition, they can accurately identify a large fraction of the least stable H-bonds in a give

Atomic Layer Deposition (ALD) to Mitigate Tin Whisker Growth and Corrosion Issues on Printed Circuit Board Assemblies

This paper presents the results of a research program set up to evaluate atomic layer deposition (ALD) conformal coatings as a method of mitigating the growth of tin whiskers from printed circuit board assemblies. The effect of ALD coating process variables on the ability of the coating to mitigate whisker growth were evaluated. Scanning electron microscopy and optical microscopy were used to evaluate both the size and distribution of tin whiskers and the coating/whisker interactions. Results show that the ALD process can achieve significant reductions in whisker growth and thus offers considerable potential as a reworkable whisker mitigation strategy. The effect of ALD layer thickness on whisker formation was also investigated. Studies indicate that thermal exposure during ALD processing may contribute significantly to the observed whisker mitigation

An Image-Free Opto-Mechanical System for Creating Virtual Environments and Imaging Neuronal Activity in Freely Moving Caenorhabditis elegans

Non-invasive recording in untethered animals is arguably the ultimate step in the analysis of neuronal function, but such recordings remain elusive. To address this problem, we devised a system that tracks neuron-sized fluorescent targets in real time. The system can be used to create virtual environments by optogenetic activation of sensory neurons, or to image activity in identified neurons at high magnification. By recording activity in neurons of freely moving C. elegans, we tested the long-standing hypothesis that forward and reverse locomotion are generated by distinct neuronal circuits. Surprisingly, we found motor neurons that are active during both types of locomotion, suggesting a new model of locomotion control in C. elegans. These results emphasize the importance of recording neuronal activity in freely moving animals and significantly expand the potential of imaging techniques by providing a mean to stabilize fluorescent targets

Formation and Growth of Oligomers: A Monte Carlo Study of an Amyloid Tau Fragment

Small oligomers formed early in the process of amyloid fibril formation may be the major toxic species in Alzheimer's disease. We investigate the early stages of amyloid aggregation for the tau fragment AcPHF6 (Ac-VQIVYK-NH2) using an implicit solvent all-atom model and extensive Monte Carlo simulations of 12, 24, and 36 chains. A variety of small metastable aggregates form and dissolve until an aggregate of a critical size and conformation arises. However, the stable oligomers, which are β-sheet-rich and feature many hydrophobic contacts, are not always growth-ready. The simulations indicate instead that these supercritical oligomers spend a lengthy period in equilibrium in which considerable reorganization takes place accompanied by exchange of chains with the solution. Growth competence of the stable oligomers correlates with the alignment of the strands in the β-sheets. The larger aggregates seen in our simulations are all composed of two twisted β-sheets, packed against each other with hydrophobic side chains at the sheet–sheet interface. These β-sandwiches show similarities with the proposed steric zipper structure for PHF6 fibrils but have a mixed parallel/antiparallel β-strand organization as opposed to the parallel organization found in experiments on fibrils. Interestingly, we find that the fraction of parallel β-sheet structure increases with aggregate size. We speculate that the reorganization of the β-sheets into parallel ones is an important rate-limiting step in the formation of PHF6 fibrils

SIMS: A Hybrid Method for Rapid Conformational Analysis

Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (SIMS), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. SIMS can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that SIMS is applied to and demonstrate a rapid solution for each. These include the automatic determination of ﾑﾑactiveﾒﾒ residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose- Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Human Cytomegalovirus IE1 Protein Elicits a Type II Interferon-Like Host Cell Response That Depends on Activated STAT1 but Not Interferon-γ

Human cytomegalovirus (hCMV) is a highly prevalent pathogen that, upon primary infection, establishes life-long persistence in all infected individuals. Acute hCMV infections cause a variety of diseases in humans with developmental or acquired immune deficits. In addition, persistent hCMV infection may contribute to various chronic disease conditions even in immunologically normal people. The pathogenesis of hCMV disease has been frequently linked to inflammatory host immune responses triggered by virus-infected cells. Moreover, hCMV infection activates numerous host genes many of which encode pro-inflammatory proteins. However, little is known about the relative contributions of individual viral gene products to these changes in cellular transcription. We systematically analyzed the effects of the hCMV 72-kDa immediate-early 1 (IE1) protein, a major transcriptional activator and antagonist of type I interferon (IFN) signaling, on the human transcriptome. Following expression under conditions closely mimicking the situation during productive infection, IE1 elicits a global type II IFN-like host cell response. This response is dominated by the selective up-regulation of immune stimulatory genes normally controlled by IFN-γ and includes the synthesis and secretion of pro-inflammatory chemokines. IE1-mediated induction of IFN-stimulated genes strictly depends on tyrosine-phosphorylated signal transducer and activator of transcription 1 (STAT1) and correlates with the nuclear accumulation and sequence-specific binding of STAT1 to IFN-γ-responsive promoters. However, neither synthesis nor secretion of IFN-γ or other IFNs seems to be required for the IE1-dependent effects on cellular gene expression. Our results demonstrate that a single hCMV protein can trigger a pro-inflammatory host transcriptional response via an unexpected STAT1-dependent but IFN-independent mechanism and identify IE1 as a candidate determinant of hCMV pathogenicity