Accelerated Ionic Motion in Amorphous Memristor Oxides for Nonvolatile Memories and Neuromorphic Computing

Memristive devices based on mixed ionic–electronic resistive switches have an enormous potential to replace today's transistor‐based memories and Von Neumann computing architectures thanks to their ability for nonvolatile information storage and neuromorphic computing. It still remains unclear however how ionic carriers are propagated in amorphous oxide films at high local electric fields. By using memristive model devices based on LaFeO₃ with either amorphous or epitaxial nanostructures, we engineer the structural local bonding units and increase the oxygen‐ionic diffusion coefficient by one order of magnitude for the amorphous oxide, affecting the resistive switching operation. We show that only devices based on amorphous LaFeO₃ films reveal memristive behavior due to their increased oxygen vacancy concentration. We achieved stable resistive switching with switching times down to microseconds and confirm that it is predominantly the oxygen‐ionic diffusion character and not electronic defect state changes that modulate the resistive switching device response. Ultimately, these results show that the local arrangement of structural bonding units in amorphous perovskite films at room temperature can be used to largely tune the oxygen vacancy (defect) kinetics for resistive switches (memristors) that are both theoretically challenging to predict and promising for future memory and neuromorphic computing applications.     

Lithium-Battery Anode Gains Additional Functionality for Neuromorphic Computing through Metal–Insulator Phase Separation

Specialized hardware for neural networks requires materials with tunable symmetry, retention, and speed at low power consumption. The study proposes lithium titanates, originally developed as Li-ion battery anode materials, as promising candidates for memristive-based neuromorphic computing hardware. By using ex- and in operando spectroscopy to monitor the lithium filling and emptying of structural positions during electrochemical measurements, the study also investigates the controlled formation of a metallic phase (Li₇Ti₅O₁₂) percolating through an insulating medium (Li₄Ti₅O₁₂) with no volume changes under voltage bias, thereby controlling the spatially averaged conductivity of the film device. A theoretical model to explain the observed hysteretic switching behavior based on electrochemical nonequilibrium thermodynamics is presented, in which the metal-insulator transition results from electrically driven phase separation of Li₄Ti₅O₁₂ and Li₇Ti₅O₁₂. Ability of highly lithiated phase of Li₇Ti₅O₁₂ for Deep Neural Network applications is reported, given the large retentions and symmetry, and opportunity for the low lithiated phase of Li₄Ti₅O₁₂ toward Spiking Neural Network applications, due to the shorter retention and large resistance changes. The findings pave the way for lithium oxides to enable thin-film memristive devices with adjustable symmetry and retention.     

The Chemical Evolution of the La<Subscript>0.6</Subscript>Sr<Subscript>0.4</Subscript>CoO<Subscript>3−δ</Subscript> Surface Under SOFC Operating Conditions and Its Implications for Electrochemical Oxygen Exchange Activity

Owing to its extraordinary high activity for catalysing the oxygen exchange reaction, strontium doped LaCoO₃ (LSC) is one of the most promising materials for solid oxide fuel cell (SOFC) cathodes. However, under SOFC operating conditions this material suffers from performance degradation. This loss of electrochemical activity has been extensively studied in the past and an accumulation of strontium at the LSC surface has been shown to be responsible for most of the degradation effects. The present study sheds further light onto LSC surface changes also occurring under SOFC operating conditions. In-situ near ambient pressure X-ray photoelectron spectroscopy measurements were conducted at temperatures between 400 and 790 °C. Simultaneously, electrochemical impedance measurements were performed to characterise the catalytic activity of the LSC electrode surface for O₂ reduction. This combination allowed a correlation of the loss in electro-catalytic activity with the appearance of an additional La-containing Sr-oxide species at the LSC surface. This additional Sr-oxide species preferentially covers electrochemically active Co sites at the surface, and thus very effectively decreases the oxygen exchange performance of LSC. Formation of precipitates, in contrast, was found to play a less important role for the electrochemical degradation of LSC.     

Effect of reconstruction beam polarization on the kinetics of anisotropic gratings in bacteriorhodopsin

Anisotropic gratings are recorded on bacteriorhodopsin films by two parallelly polarized beams, and the effect of the polarization orientation of the reconstructing beam on the diffraction efficiency kinetics is studied. A theoretical model for the diffraction efficiency kinetics of the anisotropic grating is developed by combining Jones-matrix and photochromic two-state theory. It is found that the polarization azimuth of the reconstructing beam produces a cosine modulation on the kinetics of the diffraction efficiency, being positive at the peak efficiency and negative for steady state. By adding auxiliary violet light during grating formation, the saturation of the grating can be restrained. As a result, the negative cosine modulation for the steady-state diffraction efficiency changes to a positive one. In addition, the steady-state diffraction efficiency is increased appreciably for all reconstructing polarization orientations.     

Ozone Differentially Affects Perception of Plant Volatiles in Western Honey Bees

Floral scents play a key role in mediating plant-pollinator interactions. Volatile organic compounds (VOCs) emitted by flowers are used by flower visitors as olfactory cues to locate flowers, both from a distance and at close range. More recently it has been demonstrated that reactive molecules such as ozone can modify or degrade VOCs, and this may impair the communication between plants and their pollinators. However, it is not known whether such reactive molecules also may affect the olfactory system of pollinators, and thus not only influence signal transmission but perception of the signal. In this study, we used electroantennographic measurements to determine the effect of increased levels of ozone on antennal responses in western honey bees (Apis mellifera L.). Linalool and 2-phenylethanol, both known to be involved in location of flowers by the bees, and (Z)-3-hexenyl acetate, a widespread green leaf volatile also detected by bees, were used. The results showed that ozone affected antennal responses to the different substances differently. Ozone decreased antennal responses to (Z)-3-hexenyl acetate, whereas responses to linalool and 2-phenylethanol were not influenced by ozone. Overall, the study does not provide evidence that pollination by honey bees is impaired by damage in the olfactory system of the bees caused by increased levels of ozone, at least when linalool and 2-phenylethanol are the attractive signals. However, the results also suggest that ozone can change the overall perception of an odor blend. This might have negative effects in pollination systems and other organismic interactions mediated by specific ratios of compounds.     

Polymer coating behavior of Rayleigh-SAW resonators with gold electrode structure for gas sensor applications

Results from systematic polymer coating experiments on surface acoustic wave (SAW) resonators and coupled resonator filters (CRF) on ST-cut quartz with a corrosion-proof electrode structure entirely made of gold (Au) are presented and compared with data from similar SAW devices using aluminium (Al) electrodes. The recently developed Au devices are intended to replace their earlier Al counterparts in sensor systems operating in highly reactive chemical gas environments. Solid parylene C and soft poly[chlorotrifluoroethylene-co-vinylidene fluoride] (PCFV) polymer films are deposited under identical conditions onto the surface of Al and Au devices. The electrical performance of the Parylene C coated devices is monitored online during film deposition. The PCVF coated devices are evaluated after film deposition. The experimental data show that the Au devices can stand up to 40% thicker solid films for the same amount of loss increase than the Al devices and retain better resonance and phase characteristics. The frequency sensitivities of Au and Al devices to parylene C deposition are nearly identical. After coating with soft PCFV sensing film, the Au devices provide up to two times higher gas sensitivity when probed with cooling agent, octane, or tetrachloroethylene.     

Using sequence variants of a QTL region improves the accuracy of genomic evaluation in French Saanen goats

The enhanced availability of sequence data in livestock provides an opportunity for more accurate predictions in routine genomic evaluations. Such evaluations would therefore no longer rely only on the linkage disequilibrium between a chip marker and the causal mutation. The objective of this study was to assess the usefulness of sequence data in Saanen goats (n = 33) to better capture a quantitative trait locus (QTL) on chromosome 19 (CHI19) and improve the accuracy of predictions for 3 milk production traits, 5 type traits, and somatic cell scores. All 1,207 50K genotypes were imputed to the sequence level. Four scenarios, each using a subset of CHI19 imputed variants, were then tested. Sequence-derived information included all CHI19 variants (529,576), all variants in the QTL region (22,269), 178 variants selected in the QTL region and added to an updated chip, or 178 randomly selected variants on CHI19. Two genomic evaluation models were applied: single-step genomic BLUP and weighted single-step genomic BLUP. All scenarios were compared with single-step genomic BLUP using 50K genotypes. Best overall results were obtained using single-step genomic BLUP on 50K genotypes completed with all variants in the QTL region of chromosome 19 (6.2% average increase in accuracy for 9 traits) with the highest accuracy gain for fat yield (17.9%), significant increases for milk (13.7%) and protein yields (12.5%), and type traits associated with CHI19. Despite its association with the QTL region of chromosome 19, the somatic cell score showed decreased accuracy in every alternative scenario. Using all CHI19 variants led to an overall decrease of 4.8% in prediction accuracy. The updated chip was efficient and improved genomic evaluations by 3.1 to 6.4% on average, depending on the scenario. Indeed, information from only a few carefully selected variants increased accuracies for traits of interest when used in a single-step genomic BLUP model. In conclusion, using QTL region variants imputed from sequence data in single-step genomic evaluations represents a promising perspective for such evaluations in dairy goats. Furthermore, using only a limited number of selected variants in QTL regions, as available on SNP chip updates, significantly increases the accuracy for QTL-associated traits without deteriorating the evaluation accuracy for other traits. The latter approach is interesting, as it avoids time-consuming imputation and data formatting processes and provides reliable genotypes.     

Global sensitivity analysis of wind turbine power output

The dynamics of wind turbine behavior are complex and a critical area of study for the wind industry. Identification of factors that cause changes in turbine performance can sometimes prove to be challenging, whereas other times, it can be intuitive. The quantification of the effect that these factors have is valuable for making improvements to both power performance and turbine health. In commercial farms, large quantities of meteorological and performance data are commonly collected to monitor daily operations. These data can also be used to analyze the relationship between each parameter in order to better understand the interactions that occur and the information contained within these signals. In this global sensitivity analysis, a neural network is used to model select wind turbine supervisory control and data acquisition system parameters for an array of turbines from a commercial wind farm that exhibit signs of wake interaction. An extended Fourier amplitude sensitivity test is then performed for 2 years of 10‐min averaged data. The study examines the primary and combined sensitivities of power output to each selected parameter for two turbines in the array. The primary sensitivities correspond to single parameter interactions, whereas combined sensitivities account for interactions between multiple parameters simultaneously. Highly influential parameters such as wind speed and rotor rotation frequency produce expected results; the extended Fourier amplitude sensitivity test method proved effective at quantifying the sensitivity of a wide range of more subtle inputs. These include blade pitch, yaw position, main bearing and ambient temperatures as well as wind speed and yaw position standard deviation. The technique holds promise for application in full‐scale wake studies where it might be used to determine the benefits of emerging power optimization strategies such as active wake management. The field of structural health monitoring can also benefit from this method. Copyright © 2013 John Wiley & Sons, Ltd.     

A first step toward genomic selection in the multi-breed French dairy goat population

The objectives of this study were to describe, using the goat SNP50 BeadChip (Illumina Inc., San Diego, CA), molecular data for the French dairy goat population and compare the effect of using genomic information on breeding value accuracy in different reference populations. Several multi-breed (Alpine and Saanen) reference population sizes, including or excluding female genotypes (from 67 males to 677 males, and 1,985 females), were used. Genomic evaluations were performed using genomic best linear unbiased predictor for milk production traits, somatic cell score, and some udder type traits. At a marker distance of 50 kb, the average r² (squared correlation coefficient) value of linkage disequilibrium was 0.14, and persistence of linkage disequilibrium as correlation of r-values among Saanen and Alpine breeds was 0.56. Genomic evaluation accuracies obtained from cross validation ranged from 36 to 53%. Biases of these estimations assessed by regression coefficients (from 0.73 to 0.98) of phenotypes on genomic breeding values were higher for traits such as protein yield than for udder type traits. Using the reference population that included all males and females, accuracies of genomic breeding values derived from prediction error variances (model accuracy) obtained for young buck candidates without phenotypes ranged from 52 to 56%. This was lower than the average pedigree-derived breeding value accuracies obtained at birth for these males from the official genetic evaluation (62%). Adding females to the reference population of 677 males improved accuracy by 5 to 9% depending on the trait considered. Gains in model accuracies of genomic breeding values ranged from 1 to 7%, lower than reported in other studies. The gains in breeding value accuracy obtained using genomic information were not as good as expected because of the limited size (at most 677 males and 1,985 females) and the structure of the reference population.