We will next perform long distance thermal navigation, at a height of 150 µm above the surface. Retract 150 µm using axis 3 of the coarse positioners. I’d recommend doing this in one or two big steps, because the coarse positioner can slide in response to small excursions. Verify that you can still see the thermal signal on the SQUID. It is Ok if it’s faint or close to the noise floor; it will increase in size, and you know which directions to start travelling. If the resistive encoders are working , then use them to move in 100 um steps, checking the SQUID signal in between movements. There is no need to ground the SQUID in between coarse positioner steps, there will be crosstalk but this is not hazardous for the nanoSQUID. If the resistive encoders are not working, click the Step+ button repeatedly until the SQUID signal increases to a maximum. This might take a few minutes or so of clicking. You can work on a software solution instead if you like , but remember that there is always a simple, safe solution available! Once the signal is at a maximum, take another scan to verify that you’re centered above the device. You should see a local maximum in the temperature in the middle of your scan region. Ground the SQUID. Ramp the current through the device down to zero. Zero and ground any gates you have applied voltages to. Ground the sample. Make sure the SQUID is grounded to the breakout box by a BNC . Hook up the second little red turbo pump to the sample chamber through a plastic clamp and o-ring, and turn it on. Slowly, over 10-20 minutes, flower harvest buckets open the valve to the sample chamber and pump it out. Make sure the sand buckets for vibration isolation are set up and the bellows aren’t touching the ground. If there are vibration issues you can often feel them on the bellows and on the table with your hand.
Repeat the setup for approaching to contact, and approach to contact. Definitely watch the first few rounds of this approach! You can even watch the whole thing- it’ll take 30-45 mintues, but if you’ve messed something up then the approach will destroy both the SQUID and the device, because you’ve carefully aligned the SQUID with the device! Once you’ve reached the surface, you will set up the SQUID circuit. Attach the preamplifier to one of the SMA connectors at the top of the insert. Attach its output to the input of the feedback box. This output goes through the ground breaker that is clamped to the table in Andrea’s lab; all of these analog electronic circuits are susceptible to noise and ringing, so I’m sure there will be different idiosyncracies in other laboratories with other electromagnetic environments. Attach the output of the feedback box to the BNC labelled FEEDBACK . This is the BNC that should get a resistor in series if you wanted to increase the transfer function. We generally use resistors between 1 kΩ and 10 kΩ for this. To start with, just using nothing is fine . Plug the preamp and feedback box into fresh batteries . Turn the preamp on. Turn the feedback OFF. Hook up the SQUID bias wires to SQUID A and SQUID B. You can tell which they are because of the chunky low pass filters on the end, but of course they are also labelled. Make sure both sides of the SQUID are grounded while hooking it up- there is a BNC T there for a grounding cap for this purpose. Hook up Output 2 of the Zurich to signal input on the feedback box. Apply 1 V to signal input. There’s a good chance you just used this same output and cable to apply avoltage to the device, so be careful not to skip this step and apply this voltage to the device itself!
You should see the SQUID array transfer function on the oscilloscope . Turn the rheostat/potentiometer on the preamp until this pattern has maximum amplitude. Turn the Offset rheostat/potentiometer on the feedback box until this passes through zero . There is a more sophisticated procedure for minimizing noise in the SQUID array; this is covered in great detail by documents Martin Huber has provided to the lab. But if you are a beginner this simple procedure will work fine. Flip the On switch on the feedback box, and watch the interference pattern vanish, replaced by a line near V = 0. Turn off the AC voltage going to signal input. You are now ready to characterize the SQUID, although you’ll need to unground it. That includes removing the BNC grounding caps from the T’s downstream of the SQUID bias filters and also flipping the BNC switch on the top of the rack. Click ‘preliminary sweep’ on the nSOT characterizer window. Sweep from 0 to 0.1. If you see a linear slope, a ton of stuff is working! The SQUID bias circuit, the SQUID array, the feedback electronics, all the cryogenics- that’s a really good sign. If you see no signal, don’t panic. Once again, there’s a lot of stuff involved in this circuit and a ton of mistakes you can make. Go back through the list and check everything, then check to make sure the SQUID bias isn’t grounded somewhere. Increase the sweep range until you see a critical current or you get above 3.3 V, which is where the feedback box will fail. If you don’t see a critical current, you have a SHOVET but not a SQUID. If you see a critical current, close the window, switch to the nSOT characterizer, and characterize the SQUID. At this point, you are at the surface and over the device with a working SQUID, and you can begin your imaging campaign, so what comes next is up to you!As wireless technology matured, Wireless Sensor Networks began to emerge as an advantageous alternative to their wired counterparts due in part to easy deployment and scalability. The 802.15.4 IEEE communication standard was developed for use specifically with low-rate wireless personal area networks with a focus on wireless sensor networks. In the early 2000s, the ZigBee alliance worked to construct the ZigBee protocols, communication protocols functioning on the 802.15.4 MAC and Physical layers. The main advantage of the ZigBee protocols over its competitor Bluetooth was ZigBees’ highly efficient sleep mode; ZigBee devices use a basic master-slave configuration suited for low frequency data transmission star topologies, and can wake from sleep and transmit a packet in around 15 miliseconds. As a result, ZigBee devices can last for long periods on a single power supply. In recent years, Digi incorporated the 802.15.4 standard and ZigBee protocols into a proprietary RF module known as the Xbee. Xbee devices have modular firmware capable of constructing various network topologies and have been utilized as end devices in wireless sensor network and monitoring applications. However, Xbee does not contain large processors for signal processing or local data analysis at the End Device. The limited processing capabilities of an Xbee device can be addressed with the implementation of additional hardware for processing support. Current WSN designs utilize an Arduino, a low-cost, round flower buckets reliable microcontroller capable of functioningas a building block for data acquisition or control systems, to augment a sensor nodes processing capabilities. In addition to the Arduino and Xbee, prototype WSN routinely incorporate a Raspberry Pi, a small inexpensive linux computer. The Raspberry Pi usually serves as a hardware platform for the ZigBee network Coordinator, and is used to direct network communication and control in wireless systems. Additionally, the Raspberry Pi can be used to handle WSN data storage by functioning as a database server . Raspberry Pi, Arduino, and Xbee based WSN posit two main questions. First, since ZigBee protocols were developed specifically for facilitating long node lifetimes, how does introducing additional processing hardware in the form of an Arduino impact overall node lifetime? And second, if one reason for the advance of WSN is its scalability, how do developers address the relatively limited storage capabilities of the IoT devices and their potential inability to successfully scale with increasing WSN traffic?Both sensors require signal processing to convert their data into human readable format. The Arduino uses the One Wire and Dallas Temperature libraries to read temperature values from the DS18B20 sensor, and the softSerial and TinyGPS libraries to parse GPS data from the PMB-648 GPS module. The Arduino runs a single loop that manages reading temperature and GPS sensor data, and communicating data via Xbee to the ZigBee network Coordinator. Both the Xbee and Arduino have sleep functions that minimize power consumption by periodically stopping unnecessary internal processes when those processes are notneeded.
The sleep functions were implemented inside the Arduino main code loop to halt superfluous processes while the node was neither gathering nor transmitting data. In oder to address the impact of the Arduino on End Device lifetimes, End Device average power consumption was compared for a range of transmission frequencies to generate a graphical relationship between transmission frequency and power consumption of an Arduino-Xbee End Device. The ZigBee Coordinator node consists of a Raspberry Pi series 2 B running OS Raspbian Jessie and a single Xbee Series 2 loaded with Coordinator firmware via XCTU. The Xbee Coordinator transmission and reception lines are input to the Raspberry Pi via its GPIO pins as a serial communication device. Raspberry Pi uses the Python serial and Xbee libraries to parse incoming API statements from End Devices. In order to address the limited local storage on the Raspberry Pi ZigBee Coordinator, the device is transformed into an SQLite cloud database client. The Raspberry Pi uses the Python requests library to transmit data packets as URL parameters to a cloud server. The cloud database server handles all WSN data storage, alleviating the responsibility from the Raspberry Pi. Web Application Development uses Heroku as a Platform as a Service . Heroku runs a Linux Operating System, a Puma Web Server, and an SQLite database as a framework for development. The Web Application is in charge of managing wireless sensor network data storage in the SQLite database and rendering a useful human readable User Interface for data presentation with a browser request. The Web Application uses Rails Model, View, and Controller architecture to pass incoming URL parameters to the the SQLite database via Object Relational Mapping . User Interface uses the Gmaps4Rails, a Ruby gem to superimpose Sensor and Coordinator GPS data as markers on an interactive map using the google maps API. The markers display relevant sensor data when clicked by the user, such as MAC address for sensor and Coordinator node, and temperature in degrees celsius for sensor node. A full list of the latest received data for each unique Sensor node is displayed in table format underneath the map for easy viewing.Additionally, the cloud database server is designed to be a shared database for multiple wireless sensor networks. A collaborative wireless sensor network cloud database may be useful in monitoring large scale geographically separate areas of interest such as a nationwide average temperature census or large scale environmental monitoring. Examples are given showing the cloud server functioning as a shared database.ZigBee is a global open standard for communication using the 802.15.4 protocol. Maintained by the ZigBee Alliance, transceivers communicate over ISM signal bands with intended ranges of 10-100m.ZigBee device firmware can have one of three functions which combine to form various network topologies. The three types are: ZigBee Coordinator , ZigBee Router , and ZigBee End Device . ZigBee Coordinators act as the central controller and parent node to both end devices and routers. They are in charge of network management functions such as storing security keys and network ids as well as handling network traffic. They are the most resource heavy nodes in terms of processing and local memory, and must be active for a network to exist. ZigBee Routers are capable of performing application layer tasks as well as acting as fully functional sensor nodes. Routers may function as network repeaters, extending network size by relaying information from end devices or other routers out of range of the Coordinator node. Routers are not necessary for a ZigBee network to exist, but are useful in forming sophisticated network structures or when network contains a large number of nodes.