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At least 469 records · Page 26

Large Photothermal Effect in Sub-40 nm h-BN Nanostructures Patterned Via High-Resolution Ion Beam

The controlled nanoscale patterning of 2D materials is a promising approach for engineering the optoelectronic, thermal, and mechanical properties of these materials to achieve novel functionalities and devices. Herein, high-resolution patterning of hexagonal boron nitride (h-BN) is demonstrated via both helium and neon ion beams and an optimal dosage range for both ions that serve as a baseline for insulating 2D materials is identified. Through this nanofabrication approach, a grating with a 35 nm pitch, individual structure sizes down to 20 nm, and additional nanostructures created by patterning crystal step edges are demonstrated. Raman spectroscopy is used to study the defects induced by the ion beam patterning and is correlated to scanning probe microscopy. Photothermal and scanning near-field optical microscopy measure the resulting near-field absorption and scattering of the nanostructures. These measurements reveal a large photothermal expansion of nanostructured h-BN that is dependent on the height to width aspect ratio of the nanostructures. This effect is attributed to the large anisotropy of the thermal expansion coefficients of h-BN and the nanostructuring implemented. Finally, the photothermal expansion should be present in other van der Waals materials with large anisotropy and can lead to applications such as nanomechanical switches driven by light.

2D materials↗

Multi-Scale Temporal Patterns in Stream Biogeochemistry Indicate Linked Permafrost and Ecological Dynamics of Boreal Catchments

Temporal patterns in stream chemistry provide integrated signals describing the hydrological and ecological state of whole catchments. However, stream chemistry integrates multi-scale signals of processes occurring in both the catchment and stream. Deconvoluting these signals could identify mechanisms of solute transport and transformation and provide a basis for monitoring ecosystem change. Here, we applied trend analysis, wavelet decomposition, multivariate autoregressive state-space modeling, and analysis of concentration-discharge relationships to assess temporal patterns in high-frequency (15 min) stream chemistry from permafrost-influenced boreal catchments in Interior Alaska at diel, storm, and seasonal time scales. We compared catchments that varied in spatial extent of permafrost to identify characteristic biogeochemical signals. Catchments with higher spatial extents of permafrost were characterized by increasing nitrate concentration through the thaw season, an abrupt increase in nitrate and fluorescent dissolved organic matter (fDOM) and declining conductivity in late summer, and flushing of nitrate and fDOM during summer rainstorms. In contrast, these patterns were absent, of lower magnitude, or reversed in catchments with lower permafrost extent. Solute dynamics revealed a positive influence of permafrost on fDOM export and the role of shallow, seasonally dynamic flowpaths in delivering solutes from high-permafrost catchments to streams. Lower spatial extent of permafrost resulted in static delivery of nitrate and limited transport of fDOM to streams. Shifts in concentration-discharge relationships and seasonal trends in stream chemistry toward less temporally dynamic patterns might therefore indicate reorganized catchment hydrology and biogeochemistry due to permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗

Peri-Net-Pro: the neural processes with quantified uncertainty for crack patterns

Abstract This paper develops a deep learning tool based on neural processes (NPs) called the Peri-Net-Pro, to predict the crack patterns in a moving disk and classifies them according to the classification modes with quantified uncertainties. In particular, image classification and regression studies are conducted by means of convolutional neural networks (CNNs) and NPs. First, the amount and quality of the data are enhanced by using peridynamics to theoretically compensate for the problems of the finite element method (FEM) in generating crack pattern images. Second, case studies are conducted with the prototype microelastic brittle (PMB), linear peridynamic solid (LPS), and viscoelastic solid (VES) models obtained by using the peridynamic theory. The case studies are performed to classify the images by using CNNs and determine the suitability of the PMB, LBS, and VES models. Finally, a regression analysis is performed on the crack pattern images with NPs to predict the crack patterns. The regression analysis results confirm that the variance decreases when the number of epochs increases by using the NPs. The training results gradually improve, and the variance ranges decrease to less than 0.035. The main finding of this study is that the NPs enable accurate predictions, even with missing or insufficient training data. The results demonstrate that if the context points are set to the 10th, 100th, 300th, and 784th, the training information is deliberately omitted for the context points of the 10th, 100th, and 300th, and the predictions are different when the context points are significantly lower. However, the comparison of the results of the 100th and 784th context points shows that the predicted results are similar because of the Gaussian processes in the NPs. Therefore, if the NPs are employed for training, the missing information of the training data can be supplemented to predict the results.

Mathematics↗

Netostat: analyzing dynamic flow patterns in high-speed networks

Understanding flow traffic patterns in networks, such as the Internet or service provider networks, is crucial to improving their design and building them robustly. However, as networks grow and become more complex, it is increasingly cumbersome and challenging to study how the many flow patterns, sizes and the continually changing source-destination pairs in the network evolve with time. Here, we present Netostat, a visualization-based network analysis tool that uses visual representation and a mathematics framework to study and capture flow patterns, using graph theoretical methods such as clustering, similarity and difference measures. Netostat generates an interactive graph of all traffic patterns in the network, to isolate key elements that can provide insights for traffic engineering. We present results for U.S. and European research networks, ESnet and GEANT, demonstrating network state changes, to identify major flow trends, potential points of failure, and bottlenecks.

97 MATHEMATICS AND COMPUTING↗

CSK hopping pattern model for visible light communication networks

This paper proposes a new channel access method for visible light communications. The transmitter uses the CSK hopping pattern mode to load data to the R, G, and B light-emitting diodes of LEDs and establishes the network access point (AP) of the LEDs for the illumination coverage area. The coordinator controls the work of each AP to ensure that it simultaneously uses different color patterns to distinguish its respective networks. When the receiver (mobile terminal) detects a particular color pattern in the illumination coverage area, it establishes a communication access network process with the AP that is transmitting the particular color pattern. The advantage of this method is that interference between adjacent APs can be avoided. In addition, due to the simplification of the access network, the proposed CSK hopping model can shorten delays in the terminal’s access network. Through modeling and simulation, it is found that this method can effectively support network power and reduce network delay. Moreover, the fairness and stability of terminals that access the network are improved to a certain extent.

42 ENGINEERING↗

Controllable diffraction pattern in semiconductor quantum well based on quantum coherence

In this paper, we study properties of diffraction of a weak probe field interacting with a symmetric semiconductor quantum well that is coherently manipulated by a standing wave. Based on the theory of quantum coherent and of light diffraction, we can obtain distribution of the diffraction spectra of the probe field. We consider the influences of Kerr nonlinear effect on the diffraction pattern, and studies show the distribution of diffraction pattern can be controlled through choosing appropriate physical parameters of system. Kerr nonlinear effect can enhance the brightness of central pattern and improve the transmission efficiency of the incident beam. A controllable diffraction pattern has potential applications in some areas, such as design of quantum diffractive optical elements, grating imaging system, precision measurement and so on.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Synchronous firing patterns of induced pluripotent stem cell-derived cortical neurons depend on the network structure consisting of excitatory and inhibitory neurons

Highlights: • Induced pluripotent stem cells yielded excitatory and inhibitory cortical neurons. • Neurons spontaneously fired and functionally matured on microelectrode arrays. • Firing patterns depended on the in vitro neuronal network structure. The balance between glutamate-mediated excitation and GABA-mediated inhibition is critical to cortical functioning. However, the contribution of network structure consisting of the both neurons to cortical functioning has not been elucidated. We aimed to evaluate the relationship between the network structure and functional activity patterns in vitro. We used mouse induced pluripotent stem cells (iPSCs) to construct three types of neuronal populations; excitatory-rich (Exc), inhibitory-rich (Inh), and control (Cont). Then, we analyzed the activity patterns of these neuronal populations using microelectrode arrays (MEAs). Inhibitory synaptic densities differed between the three types of iPSC-derived neuronal populations, and the neurons showed spontaneously synchronized bursting activity with functional maturation for one month. Moreover, different firing patterns were observed between the three populations; Exc demonstrated the highest firing rates, including frequent, long, and dominant bursts. In contrast, Inh demonstrated the lowest firing rates and the least dominant bursts. Synchronized bursts were enhanced by disinhibition via GABA{sub A} receptor blockade. The present study, using iPSC-derived neurons and MEAs, for the first time show that synchronized bursting of cortical networks in vitro depends on the network structure consisting of excitatory and inhibitory neurons.

60 APPLIED LIFE SCIENCES↗

Machine learning for interpreting coherent X-ray speckle patterns

Speckle patterns produced by coherent X-ray have a close relationship with the internal structure of materials but quantitative inversion of the relationship to determine structure from speckle patterns is challenging. Here, in this work, we investigate the link between coherent X-ray speckle patterns and sample structures using a model 2D disk system and explore the ability of machine learning to learn aspects of the relationship. Specifically, we train a deep neural network to classify the coherent X-ray speckle patterns according to the disk number density in the corresponding structure. It is demonstrated that the classification system is accurate for both non-disperse and disperse size distributions.

36 MATERIALS SCIENCE↗

Incorporating space and time into random forest models for analyzing geospatial patterns of drug-related crime incidents in a major U.S. metropolitan area

The opioid crisis has hit American cities hard, and research on spatial and temporal patterns of drug-related activities including detecting and predicting clusters of crime incidents involving particular types of drugs is useful for distinguishing hot zones where drugs are present that in turn can further provide a basis for assessing and providing related treatment services. In this study, we investigated spatiotemporal patterns of more than 52,000 reported incidents of drug-related crime at block group granularity in Chicago, IL between 2016 and 2019. We applied a space-time analysis framework and machine learning approaches to build a model using training data that identified whether certain locations and built environment and sociodemographic factors were correlated with drug-related crime incident patterns, and establish the top contributing factors that underlaid the trends. Space and time, together with multiple driving factors, were incorporated into a random forest model to analyze these changing patterns. We accommodated both spatial and temporal autocorrelation in the model learning process to assist with capturing the changes over time and tested the capabilities of the space-time random forest model by predicting drug-related activity hot zones. Overall, we focused particularly on crime incidents that involved heroin and synthetic drugs as these have been key drug types that have highly impacted cities during the opioid crisis in the U.S.

97 MATHEMATICS AND COMPUTING↗

Effect of patterned inclusions on the fracture behavior of ceramic composites

Developments in additive manufacturing have enabled the reinforcement of ceramic composites across the scales. Understanding the fracture behavior of such composites is critical for structural design and engineering. However, systematic investigations on the relationship between the patterning characteristics and the effective fracture properties have been scarce. In this work, we propose a mixed-mode phase field model to investigate the effects of elastic modulus and pattern characteristics of circular inclusions on the fracture behavior of a ceramic composite beam. The modeling results have shown that the stiff and compliant inclusions can either repel or attract the crack. The extent of repelling and attraction can be controlled by altering the pattern characteristics. In addition, utilizing the relationship between the pattern characteristics and resulting fracture path, fracture growth can be controlled with appropriate inclusion properties. The targeted enhancement in fracture toughness can also be predicted using an effective fracture model linked with the underlying fracture path computed by the proposed mixed-mode phase field model.

36 MATERIALS SCIENCE↗

Circulating levels of perfluoroalkyl substances are associated with dietary patterns – A cross sectional study in elderly Swedish men and women

Background: In our daily life, we are exposed to perfluoroalkyl substances (PFAS) with possible health implications. The main exposure route for these substances is diet but comparative studies on how dietary habits influence exposure are lacking. Objectives: To examine the relations between blood levels of PFAS and adherence to three predefined dietary patterns (a WHO recommended diet, a Mediterranean-like diet, and a Low-Carbohydrate High-Protein (LCHP) diet) in an elderly Swedish population. Methods: Dietary data from 7-day food records and serum concentrations of PFAS were obtained from a 70-year-old Swedish population (n=844), the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study. The Healthy Diet Indicator score (based on WHO recommendations), the Mediterranean Diet Score and LCHP score were used to assess adherence. Multivariate linear regression was used to assess the associations between eight major PFAS and adherence to each dietary pattern. Results: The WHO recommended diet was positively associated with perfluorohexane sulfonic acid (PFHxS). The LCHP diet was positively related to four out of eight PFAS; namely, perfluorooctane sulfonic acid (PFOS), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA) and perfluoroundecanoic acid (PFUnDA). The Mediterranean-like diet was positively associated with most PFAS; namely perfluorooctanoic acid (PFOA), perfluorooctane sulfonamide (PFOSA), PFHxS, PFNA, PFDA, and PFUnDA. Conclusions: All dietary patterns were positively associated with blood levels of PFAS. The highest body burden of PFAS was found in individuals with high adherence to a Mediterranean-like diet, whilst individuals who more closely followed the officially recommended diet displayed a lower body burden of these compounds. - Highlights: • Perfluoroalkyl substances (PFAS) quantified in blood of 70-y-old Swedish subjects. • Adherence to predefined dietary patterns was associated with circulating PFAS. • A Mediterranean-like diet was positively associated with most circulating PFAS. • A low-carbohydrate high-protein diet was positively related to some PFAS in blood. • A WHO-recommended diet was only related to higher circulating levels of PFHxS.

54 ENVIRONMENTAL SCIENCES↗

Supply sunspots and shadows: Business siting patterns and inequitable rooftop solar adoption in the United States

Entrepreneurs in certain industries tend to locate new businesses in relatively affluent areas. Preferences to site businesses in affluent areas can reduce low-income household access to certain products. Some argue that business siting patterns could explain inequitable consumption patterns, though such causal claims are often empirically weak. Here, we explore whether business siting patterns partly explain inequitable adoption of rooftop solar photovoltaics in California. We show that solar business formation drives an immediate and sustained increase in local solar adoption, including in low-income areas. However, solar business siting patterns have only weak impacts on solar adoption equity. The data show how solar businesses headquartered in low-income areas nonetheless install solar for relatively affluent customers. Customer-level adoption inequity partly offsets the potential equity gains of siting more businesses in low-income areas. We discuss how the emergent nature and unique business model of rooftop solar help explain these nuanced results.

14 SOLAR ENERGY↗

Patterns of Local-Regional Failure in Completely Resected Stage IIIA(N2) Non-Small Cell Lung Cancer Cases: Implications for Postoperative Radiation Therapy Clinical Target Volume Design

Purpose: To analyze patterns of local-regional failure (LRF) for completely resected stage IIIA(N2) non-small cell lung cancer (NSCLC) patients treated in our hospital and to propose a clinical target volume (CTV) for postoperative radiation therapy (PORT) in these patients. Methods and Materials: From 2005 to 2011, consecutive patients with pT1-3N2 NSCLC who underwent complete resection in our hospital but who did not receive PORT were identified. The patterns of first LRF were assessed and evaluated as to whether these areas would be encompassed by our proposed PORT CTV. Results: With a median follow-up of 24 months, 173 of 250 patients (69.2%) experienced disease recurrence. Of the 54 patients with LRF as the first event, 48 (89%) had recurrence within the proposed PORT CTV, and 6 (11%) had failures occurring both within and outside the proposed CTV (all of which occurred in patients with right-lung cancer). Ninety-three percent of failure sites (104 of 112) would have been contained within the proposed PORT CTV. For left-sided lung cancer, the most common lymph node station failure site was 4R, followed by 7, 4L, 6, 10L, and 5. For right-sided lung cancer, the most common site was station 2R, followed by 10R, 4R, and 7. Conclusions: LRF following complete surgery was an important and potentially preventable pattern of failure in stage IIIA(N2) patients. Ipsilateral superior mediastinal recurrences dominated for right-sided tumors, whereas left-sided tumors frequently involved the bilateral superior mediastinum. Most of the LRF sites would have been covered by the proposed PORT CTV. A prospective investigation of patterns of failure after PORT (following our proposed CTV delineation guideline) is presently underway and will be reported in a separate analysis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Influence of turbulence intensity on vortex pattern for a rigid cylinder with turbulence stimulation in flow induced oscillations

The effect of ambient turbulence intensity on the flow induced oscillations of rigid circular cylinders with symmetric and asymmetric local turbulence stimulation is studied. Cylinders oscillate in one degree of freedom transversely to a steady uniform flow. Two-dimensional unsteady Reynolds-Average Navier-Stokes equations with the Spalart-Allmaras turbulence model are used to solve the problem numerically. Three freestream turbulence intensity values (0.2%, 1%, 5%) are used to study the influence of turbulence intensity on vortex pattern. Simulation results are compared with experimental data measured in the Marine Renewable Energy Laboratory of the University of Michigan in the range of 30,000 ≤ Re ≤ 110,000. The amplitude ratio, lift coefficient, vortex modes, and the interactions between vortices and cylinders are observed and discussed. In conclusion, major conclusions are: (a) Vortex patterns strongly depend on the freestream ambient turbulence intensity. (b) Low turbulence intensity can generate multi-vortex patterns at high Re. (c) High turbulence intensity results in fewer separations of a shed vortex into multiple vortices inducing emergence of elongated vortex patterns.

42 ENGINEERING↗

Extracting Grain Orientations from EBSD Patterns of Polycrystalline Materials Using Convolutional Neural Networks

Abstract We present a deep learning approach to the indexing of electron backscatter diffraction (EBSD) patterns. We design and implement a deep convolutional neural network architecture to predict crystal orientation from the EBSD patterns. We design a differentiable approximation to the disorientation function between the predicted crystal orientation and the ground truth; the deep learning model optimizes for the mean disorientation error between the predicted crystal orientation and the ground truth using stochastic gradient descent. The deep learning model is trained using 374,852 EBSD patterns of polycrystalline nickel from simulation and evaluated using 1,000 experimental EBSD patterns of polycrystalline nickel. The deep learning model results in a mean disorientation error of 0.548° compared to 0.652° using dictionary based indexing.

Materials Science↗

Sharp Morphological Transitions from Nanoscale Mixed-Anchoring Patterns in Confined Nematic Liquid Crystals

Liquid crystals are known to be particularly sensitive to orientational cues provided at surfaces or interfaces. In this work, we explore theoretically, computationally, and experimentally the behavior of liquid crystals on isolated nanoscale patterns with controlled anchoring characteristics at small length scales. The orientation of the liquid crystal is controlled through the use of chemically patterned polymer brushes that are tethered to a surface. This system can be engineered with remarkable precision, and the central question addressed here is whether a characteristic length scale exists at which information encoded on a surface is no longer registered by a liquid crystal. To do so, we adopt a tensorial description of the free energy of the hybrid liquidcrystal surface system, and we investigate its morphology in a systematic manner. For long and narrow surface stripes, it is found that the liquid crystal follows the instructions provided by the pattern down to 100 nm widths. This is accomplished through the creation of line defects that travel along the sides of the stripes. We show that a "sharp" morphological transition occurs from a uniform undistorted alignment to a dual uniform/splay-bend morphology. The theoretical and numerical predictions advanced here are confirmed by experimental observations. Our combined analysis suggests that nanoscale patterns can be used to manipulate the orientation of liquid crystals at a fraction of the energetic cost that is involved in traditional liquid crystal-based devices. Here, the insights presented in this work have the potential to provide a new fabrication platform to assemble low power bistable devices, which could be reconfigured upon application of small external fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Printing-assisted surface modifications of patterned ultrafiltration membranes

Understanding and restricting microbial surface attachment will enhance wastewater treatment with membranes. We report a maskless lithographic patterning technique for the generation of patterned polymer coatings on ultrafiltration membranes. Polyethylene glycol, zwitterionic, or negatively charged hydrophilic polymer compositions in parallel- or perpendicular-striped patterns with respect to feed flow were evaluated using wastewater. Membrane fouling was dependent on the orientation and chemical composition of the coatings. Modifications reduced alpha diversity in the attached microbial community (Shannon indices decreased from 2.63 to 1.89) which nevertheless increased with filtration time. Sphingomonas species, which condition membrane surfaces and facilitate cellular adhesion, were depleted in all modified membranes. Microbial community structure was significantly different between control, different patterns, and different chemistries. Lastly, this study broadens the tools for surface modification of membranes with polymer coatings and for understanding and optimization of antifouling surfaces.

36 MATERIALS SCIENCE↗

Selective-Area Remote Epitaxy of ZnO Microrods Using Multilayer–Monolayer-Patterned Graphene for Transferable and Flexible Device Fabrications

Here, selective-area remote epitaxy (SA-REpi) is demonstrated for fabricating mechanically releasable position-controlled ZnO microrod (MR) arrays from donor wafers in an arrayed form. Intaglio-patterned graphene, consisting of basal single-layer graphene (SLG) overlayered with multilayer graphene (MLG) patterned with perforated holes, is transferred onto a GaN/Al 2 O 3 wafer on which the hydrothermal synthesis is performed for growing ZnO MRs. The basal SLG area exposed through the MLG pattern yields ZnO MRs, whereas the MLG plateau inhibits the growth. The noncovalent remote epitaxial heterointerface enables the release of the MR overlayer in the arrayed form, and the original source wafer is refurbished for reproducibly repeating the SA-REpi. Density-functional theory calculations suggest that localized surface charge density is induced on the surface of SLG by the underlying GaN across ultrathin SLG, which possibly provides a driving force for precursor adatoms and the following remote epitaxy of ZnO. In contrast, the induction of the charge density redistribution does not clearly occur through MLG; so, that keeps the surface of MLG nearly charge-neutral. The diameter and spacing of ZnO MRs are controlled in a designed way by changing the pattern geometries. High-resolution scanning transmission electron microscopy reveals the remote heteroepitaxial relationship at an atomic level. The remote epitaxy is expected to provide an ideal platform to transfer the addressable spatial arrays of nano- or micro-architecture semiconductor components to arbitrary target surfaces directly after the growth without the assembly procedures.

36 MATERIALS SCIENCE↗