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Showing posts from July, 2020

Python and Circuits: HSPICE Binary File Parsing

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Hi everyone, my name is Raphael Gonzalez and I am a rising sophomore with an undeclared major. This summer I’ve been working with Prof Spencer’s ACE lab on a number of projects. Among these projects has been the creation of an HSPICE post1 file parser. HSPICE is a circuit simulator, a program that predicts voltages and currents in a user-specified circuit, and it has notoriously opaque binary output file formats that are collectively referred to as “post1 formats”. This is a problem because understanding output files is important for writing automation scripts or using tools like Matlab for analyzing simulation results.  Binary file contents as rendered my computer. I’ve included the figure above to make this problem concrete. It’s a screenshot of the output when we open up a post1 output file as text. This is the computer’s best guess of what the file says (it’s not a very good guess). We can force the computer to show us binary it is trying to decipher by using a tool called a hexdum

Graphene Image Analysis

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Hello! My name is Jessica and I am a rising sophomore at Mudd. I am currently studying 2D materials with Professor Breznay. The study of 2D materials such as graphene, stanene, and hexagonal boron nitride is coming into prominence because of the potential it holds for applications in many different fields. Their unique and mostly unresearched mechanical and chemical properties are thought to stem from the weak bonds holding together tightly bonded sheets of repeated subunits consisting of single atoms or molecules. We are focusing on studying graphene because it has been the most widely researched and is the simplest of the 2D materials both to synthesize (using the scotch tape method) and in its basic structure. During the school year, we worked on refining the process of exfoliating graphene onto a silicon substrate and studying the samples under an optical microscope. The optical microscope works by shining a beam of white light into a beamsplitter through an objective, which then r

LAIR - A* Path Planning

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Hi everyone! My name is Alicia Lu, a rising sophomore working in the LAIR (Lab for Autonomous and Intelligent Robotics). This summer I have been working with my fellow classmates and Prof. Clark on developing a multi-AUV system to track sharks while simultaneously collecting marine habitat data.  My job on the path-planning team is to modify the classic A* search algorithm (often seen as an extension of the famous Dijkstra Algorithm) to include our expected functionalities: track sharks of fixed positions and cover as many new habitats as possible. I have developed two versions of path planning algorithms that can complete the listed tasks.  This post shows the simulation results from the algorithm that aims to explore as many new habitats as possible while trying to maximize time spent in each habitat. The longer time spent in a habitat implies longer trajectory length within a habitat. Figure 1 below illustrates a trajectory that starts at (-215.63, -5.89) and has a length of 71 node

Molecular Diffusion Lab

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Hi everyone! My name is Sophia Lauf (J) and I work with fellow students Naina Kaimal (J), Sam Marquez (J), G Missaka (S), and Hunter Whaples (S) at the Molecular Diffusion Laboratory under the guidance of Prof. Lape. We study nanoparticles suspended in polymer membranes in order to better understand and design novel materials for separating gas mixtures. We hope this research can advance all kids of separation technologies including the emerging field of Carbon Capture! Two major properties of polymer membranes are permeability , which is the product of diffusivity and solubility representing the ease of gas penetration, and selectivity, which is the ratio of permeability between two penetrants representing separation performance. The ideal separation membrane would be both highly permeable and highly selective for a given gas, meaning it allows that gas to pass very easily without allowing contaminants to pass. Unfortunately, in the poymeric membranes that the Molecular Diffusion Lab

AMISTAD Lab - Survival Advantages of Intention Perception

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Introduction Greetings! We are the Intention Perception team working directly with Professor George MontaƱez. Our team consists of Amani Maina-Kilaas, Cynthia Hom, Kevin Ginta, and Cindy Lay. Our research aims to show that there exist scenarios in which the ability of an agent to perceive intention provides a measurable survival advantage. We show this by developing and running simulations to explore scenarios where this knowledge may be especially beneficial. Experiment 1: Predators and Prey In our first experiment, we create a predator and prey scenario, in which the predators try to eat the prey, and the prey try to avoid predators and eat food. In this scenario, we give the prey three different tiers of awareness. The lowest tier is no predator awareness—the prey can only see food. The next tier is proximity awareness—they are aware of the location of nearby predators and can try to avoid them accordingly. The highest tier—the intention awareness tier—grants prey the ability to kno