One potential benefit of vegetated building rooftops, called ecoroofs or green roofs, is reductions in outdoor air pollution levels. However, there is little empirical data on real roofs that would enable evaluation of air quality impacts of ecoroofs. We developed and tested a low-cost dynamic flux chamber for characterizing ozone (O3) deposition on the vegetation and substrate typically used for ecoroofs. Ozone flux measurements were determined in the lab using ecoroof substrate; the next phase of testing uses ecoroof vegetation called sedums. To measure flux, a 6.59 L acrylic chamber is injected with ozone to elevate chamber O3 levels. Ambient air is drawn through the chamber by a vacuum pump. The decay of O3 levels are measured by an ozone monitor. Separate tests are conducted using an inert tracer gas, CO2, to measure the chamber air exchange rate. Preliminary results show the chamber had an air exchange rate of 0.17 ± 0.023 min-1. Minimization of errors between O3 measurements and mass balance models yielded deposition velocities (vd) for both the acrylic chamber and substrate, which were 0.16 m/hour and 5.66 m/hour respectively. Future experiments will characterize substrate and vegetation across a range of temperature, moisture content, and lighting conditions. These results will constrain models of rooftop pollutant dynamics, enabling estimates of impacts of rooftop vegetation on both urban and indoor air quality.

Flow is a mental state achieved by a person performing a task when there is a balance between skill and challenges, thereby evoking focused attention, full involvement, and enjoyment. For education applications, achieving a flow state may accelerate learning, retention and improve learning outcomes. Most current methods for assessing the extent of flow state use a self-reported questionnaire only when participants finish a learning activity. Alternatively, using objective real-time measurement such as electrophysiological techniques to assess the flow state, especially during a learning period, affords the possibility of timely adjustment of challenges to keep up with learners’ growing abilities. Such an adaptive approach may provide a more improved way to enter and sustain flow in learning activities. Previous studies also indicate that gamification is a proven way to induce the flow state, and virtual reality (VR) activities provide learners more immersive experience. The purpose of this preliminary study is to investigate an adaptive approach for assessing flow state during VR learning activities with electrophysiological measurement. This study used a NeuroSky EEG headset with a supervised machine learning algorithm to identify the features of attention, meditation, and eye blinks with flow state while performing VR learning activities. To evaluate the effects of the proposed approach, data collection was through an experiment with 10 UW students by assessing their flow state while playing VR educational games. The first version model trained by the three types of indicators is capable of determining if a learner performing VR learning activities enters the flow state. In turn, the result of this preliminary study serves as a metric for the follow-on research addressing the development of adaptive learning strategies to help each learner enter into a flow state and improve learning outcomes with the sustained flow state.

Wheat Take-All Disease (TAD) is caused by the effect of the soil-based fungus Gaeumannomyces graminis var. tritici on wheat crops. We as Pierce College Biology students in conjunction with other local institutions sequenced part of a strain of Pseudomonas fluorescens, L5.1-96 (P.f. L5.1-96), because of its known trait to supercolonize soil. Sequencing was initially achieved at Pierce College by linear sequencing reaction before being completed by Sanger Sequencing at Washington State University. Resulting data was then interpreted using FinchTV, and the NIH BLAST and tBLAST programs. P.f. L5.1-96 produces 2,4-diacetylphloroglucinol (DAPG) which is a key component in Take-All Decline, the natural suppression of the fungus after several generations, in soils. Using Escherichia coli bacteria to clone 1.7kb long plasmids of the P.f. L5.1-96 strain, the plasmids were amplified and purified in order to discover genes relevant to the empirical objective to better understand this bacteria. Our DNA insert, the portion of data analyzed from FinchTV by cross reference with BLAST, aligned with several important enzymes related to antibiotic resistance and toxin metabolism, both of which could be key to supercolonization of soil. In addition, a phylogenetic relationship has been established using BLAST between P. brassicacearum, P. chlororaphis, and our strain of Pseudomonas fluorescens L5.1-96. The findings of the research could provide greater insight into what constitutes an effective biological control agent against TAD in Washington, and possibly other affected areas of the world.

Large data centers, such as those built by Google, Amazon, and other information technology leaders consume about 1.3% of the world’s energy, of which about 40% is used on electronics cooling [1, 2]. This amounts to 245 TWh per year, which, with the average US price of 12 cents per kWh, amounts to about $29.4 billion dollars spent per year on cooling high heat semiconductors [3, 4]. The work presented here proposes an innovative way to improve this cooling process. The proposed concept features a levitating inner rotor using fluid bearings that result in no physical contact between solid parts, eliminating friction. For the first time, precision-manufactured plastic parts are utilized to achieve both a low cost and a high reliability. The micropump is expected to last in operation for over one million hours Mean Time to Failure. This work emphasizes model-based design verification and optimization to ensure adequate performance for different form factors – so that a drop-in replacement of an air fan passive heat sink can be quickly developed for every microelectronics product. Twenty-four designs and prototypes were used in evaluation of two key criteria in order to optimize the pump’s design. Three separate herringbone geometries, square, beveled-step, and circular, of herringbone grooves were prototyped based on experimentation of optimum groove parameters. These findings helped determine the optimal layer height of 100 micron for use in the micropump design. Finally, the application of a sensorless, brushless DC motor reduces overall cost of the pump and increases efficiency due to the removal of friction.

Prior research has shown that virtual reality (VR) has great promise as a science and engineering teaching tool at the primary and secondary school levels. Unfortunately there is little VR educational content for schools since the education marketplace is poorly funded. Our objective is to solve this problem by teaching middle school students how to build their own immersive 3D virtual worlds that can used as teaching aids for other students and schools. To investigate this approach we are working with Robert Eagle Staff Middle School in an after-school engineering club teaching world building tools and processes to 6th graders. We have organized the students into four teams to create VR games that teach STEM concepts including scale, gravity, light, and momentum. University of Washington engineering students are assigned to mentor these teams while serving as role models to the middle school students.The middle school students not only learn world building techniques but also understanding of these STEM concepts well enough to teach others. To create the VR games, we are instructing the students how to use Unity3D as a game engine. The virtual worlds will operate in real time on the HTC Vive VR headsets with high-end Intel-powered computers. In addition to the world building efforts student learn how to set up, configure and operate the technology within the VR workspace at the school. Our final product will be both the educational content designed by the students but also a prototype of the way to do it. We are documenting our findings in scholarly reports and a documentary film that can be used to inform schools across the nation of how to use virtual reality as a teaching tool and to build a repository of virtual worlds that can be exchanged across schools.

Polymer based fullerenes are used as photovoltaics in solar panels. Fullerene C60 molecules have icosahedral based structures resembling geodesic domes. Fullerenes have convex polyhedral shapes which obey Euler’s topological rules. Their novel structures involve Golden ratios. Here we use vector calculus methods to calculate bond lengths and bond angles and provide estimates for the volume and surface area of the molecule. The calculated average bond length (1.4320 Å), edge length (2.4252 Å), bond angle (116o) are in good agreement with reported experiments. The estimated fullerene molecularvolume is 788 Å3 and surface area is 426 Å2. To understand the critical effect of dimensionality on volume, we have studied the volume of a hypersphere in n-dimensions. The project provides hands on exploration of real world problems and data visualization.

Upper- and lower-limb orthotic devices are prescribed for individuals who have partially lost motor control, such as stroke survivors or those with cerebral palsy, to assist with the stability and function of a limb. Unlike prostheses, devices available for those missing part of a limb, there are few current solutions available for upper-limb orthoses. As a result, options for users can be clunky, expensive, and hard to customize. The goal of this research was to further develop a 3D-printed elbow-driven orthosis that is inexpensive, adjustable, and helps users with impaired dexterity perform two-handed daily tasks. In comparison to traditional devices, which can cost hundreds of dollars, this orthosis can be assembled for approximately $30 predominantly because of the use of 3D printed parts. Originally designed for an individual whose seizure reducing brain surgery limited use of her left hand, this orthosis takes advantage of existing elbow range of motion to operate a clamp near the user’s palm by using a cable extending from the elbow to the hand. Cable tension activates the clamp near the palm in two distinct ways, depending on chosen part placements; the cable can either voluntarily open the clamp, or voluntarily close the clamp with elbow flexion. To compare clamp activation methods, we conducted a study that evaluated muscle activity and time to complete activities of daily living using the adjustable orthosis. These results will help inform which device setting, voluntary opening or voluntary closing, is easiest to control for common tasks and inform future device improvements. Participants involved in this study included individuals with impaired and unimpaired hand function. Through a continuous cycle of prototyping, feedback, and device modifications, we have created a customizable, affordable, 3D printed upper-limb orthosis that will be open-sourced to promote further innovation to support individuals with limited hand function.

In scientific research labs, in general, experiments are generally treated as a black box: a prepared sample goes in, something happens, and one gets results that are then obtained via elaborate characterization steps. Several important dependent or correlated parameters are either discarded or ignored because of a lack of coherent dependency analyses that require critical thinking, linking, and pattern recognition. In this research we are working to stop treating experiments and computational simulations as black boxes, and create a cohesive platform where materials used, processes and parameters utilized and results achieved can be brought together as separate but related sets of databases. In the next step, the relationships between all the different parameters can then be connected, analyzed and visualized. Machine learning and AI techniques can then be used to predict results using these databases, thereby reducing experiment time, and taking away the traditional ‘trial and error’ method of experimentation. The research involves creation of a software interface, with numerous image and signal processing tools and applications running on libraries made customizable to research fields, types of experiments, etc. Assorted variety of services such as parallelization, compression, data analysis, and visualization, caching (among others) are also provided. We are improving the accuracy of time series data analysis and using fingerprinting to depict all parameters for improved predictability, flexibility and accuracy. When fully developed, we anticipate that the program will enable experimental and computational researchers to extensively use, customize and apply data analytics, machine learning and AI even in niche research in the hard sciences at the intersection of biology and genetics, materials science (physics, chemistry) and engineering, and computational modeling and informatics, enabling faster and accurate cross disciplinary innovation in technology and medicine. The research is supported by NSF-DMREF (DMR-1629071) program at GEMSEC-MSE, as part of National Materials Genome Initiative.

This project aims to influence the next generation of flying robots by first studying how moths use multi-sensory information to increase their agility. These different types of multi-sensory information include visual- and touch-based feedback, which are influenced by forces such as those from flapping wings and changes in body posture (which affect a moth’s inertial distribution). To visualize and analyze moth flight in a controlled environment, the goal is to implement a virtual environment, in which projected video will simulate a changing environment and provide a haptic-type virtual reality interface for the moths. Varying the dynamics of the moth’s motion (for example, angle of rotation and speed of movement) in this manner will enable an analysis of how the moths respond to inertial and aerodynamic forces. The first engineering challenge is to design and build a system to electronically control and monitor the motion of the moth while having a minimal affect on a moth’s inertia and natural flight patterns. This requires the design to have low mass, inertia and friction. After this, cameras and sensors will be used to record data that will contribute to a more realistic understanding of how the principles of animal flight can be used in robotics.