Analysis of the Brownian Motion by Elementary School Students

To stimulate the intellectual curiosity of elementary school students, we conducted a workshop in distance education aimed at exploring the microscopic world inside a cell. In this workshop, elementary school students motivated to learn more on the subject of science analyzed movies of the Brownian motion of micrometer-sized particles suspended in water, using an open-source software, Tracker. These students then performed two-dimensional(2D)-random walk experiments using a dice game sheet to examine the physical mechanism of Brownian motion. After the workshop, we conducted a questionnaire-based survey. Many participants answered that the contents were difficult but interesting, suggesting that our workshop was very efficient to stimulate the curiosity of motivated students.Comment: 16 pages, 10 figures, the following article has been submitted to The Physics Teache

Shaping Graphene: An Alternative Approach

With experimentation on graphene (an atomic layer of graphite) becoming more and more common it is imperative that we have the capability to shape the material beyond the random manner in which it is deposited by mechanical exfoliation. This capability would be invaluable not only for the interesting electronic and optical properties that can be obtained, but also potentially for characterizing the mechanical resonators that we have been able to fabricate here at Pomona College by suspending few-layer graphene sheets over trenches in SiO2. We propose novel methods for etching graphene that should allow us to shape the material when used in conjunction with our e-beam lithography capabilities

Crumbling Crystals: On the Dissolution Mechanism of NaCl in Water

Life on Earth depends upon the dissolution of ionic salts in water, particularly NaCl. However, an atomistic scale understanding of the process remains elusive. Simulations lend themselves conveniently to studying dissolution since they provide the spatio-temporal resolution that can be difficult to obtain experimentally. Nevertheless, the complexity of various inter- and intra-molecular interactions require careful treatment and long time scale simulations, both of which are typically hindered by computational expense. Here, we use advances in machine learning potential methodology to resolve for the first time at an ab initio level of theory the dissolution mechanism of NaCl in water. The picture that emerges is that of a steady ion-wise unwrapping of the crystal preceding its rapid disintegration, reminiscent of crumbling. The onset of crumbling can be explained by a strong increase in the ratio of the surface to volume of the crystal. Overall, dissolution is comprised of a series of highly dynamical microscopic sub-processes, resulting in an inherently stochastic mechanism. These atomistic level insights now pave the way for a general understanding of dissolution mechanisms in other crystals, and the methodology is primed for more complex systems of recent interest such as water/salt interfaces under flow and salt crystals under confinement

Mapping Structural Heterogeneity at the Nanoscale with Scanning Nano-structure Electron Microscopy (SNEM)

Here we explore the use of scanning electron diffraction coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr$_{65}$Cu$_{17.5}$Ni$_{10}$Al$_{7.5}$ bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don't require energy filters on the instrument. We spatially map different quantities of interest (QoI's), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI's. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods

Understanding Soft Errors in Uncore Components

The effects of soft errors in processor cores have been widely studied. However, little has been published about soft errors in uncore components, such as memory subsystem and I/O controllers, of a System-on-a-Chip (SoC). In this work, we study how soft errors in uncore components affect system-level behaviors. We have created a new mixed-mode simulation platform that combines simulators at two different levels of abstraction, and achieves 20,000x speedup over RTL-only simulation. Using this platform, we present the first study of the system-level impact of soft errors inside various uncore components of a large-scale, multi-core SoC using the industrial-grade, open-source OpenSPARC T2 SoC design. Our results show that soft errors in uncore components can significantly impact system-level reliability. We also demonstrate that uncore soft errors can create major challenges for traditional system-level checkpoint recovery techniques. To overcome such recovery challenges, we present a new replay recovery technique for uncore components belonging to the memory subsystem. For the L2 cache controller and the DRAM controller components of OpenSPARC T2, our new technique reduces the probability that an application run fails to produce correct results due to soft errors by more than 100x with 3.32% and 6.09% chip-level area and power impact, respectively.Comment: to be published in Proceedings of the 52nd Annual Design Automation Conferenc

Scalable Manufacturing of Superhydrophobic Micro- and Nanostructured Condensation Accelerating and Droplet Shedding Surfaces for Air Conditioning Performance Enhancement

One solution currently being explored for reducing the condensation effects of water inside the evaporator coil of an air conditioning system is the use of textured surface morphologies on the evaporator fins that may enable water droplets to both condense and shed more quickly. While multiple pattern scales and geometries have been characterized on metal substrates, including posts, pillars, post arrays, reentrant structures, micro/nano hierarchical patterns, and microchannels, there is a dearth of research associated with microdome patterns, the significance being that nature’s most famous superhydrophobic, water-shedding surface, the lotus leaf, utilizes these features. Here, aluminum surfaces have been fabricated with varying micropillar and microdome structures and a hydrothermally grown nanoporous layer of zinc oxide to create a hierarchical morphology that is reminiscent of the lotus leaf geometry. Micropillar and microdome array structures with comparable feature sizes and areal densities were fabricated, and their static and dynamic water contact angles were characterized in order to understand the influence of microstructural geometry on water-shedding performance. These hierarchical surfaces were further characterized in dynamic condensing conditions using a custom-designed wind tunnel setup to simulate an air conditioning inlet environment. Video footage was recorded, and an image analysis algorithm was developed and applied in order to compare surface performance. The entire zinc oxide nanostructure synthesis process was then scaled and applied to a full-scale cooling coil for later evaluation in a simulated building testbed. The results of all surface characterization methods and condensation tests, the wind tunnel test bed design, the image analysis algorithm development, and the scaling process are reported