Project

# Title Team Members TA Documents Sponsor
47 MaterialID: Identifier for Unmarked Materials
Sachith Chandran
Shritan Bhupathiraju
Siddharth Gupta
Aniket Chatterjee
Team Members:
- Shritan Bhupathiraju (shritan2)
- Sachith Chandran (src14)
- Siddharth Gupta (sg96)

# Problem

Machine shops, makerspaces, and teaching labs keep bins of offcuts and scrap stock whose markings were cut away long ago. Many of these materials look alike: 6061 and 7075 aluminum, brass and bronze, stainless and mild steel, and several clear or white plastics. Getting them confused causes real problems. For example, 7075 is generally considered unsuitable for fusion welding while 6061 welds routinely, and alloys machine and finish differently. A wrong guess can mean scrapped parts, wasted machine time, or a structural failure.

Existing tools each cover only part of the problem:
- A magnet only separates ferrous from non-ferrous metals.
- Spark testing works only on steels and takes a trained eye.
- Handheld X-ray fluorescence analyzers cost tens of thousands of dollars.
- Eddy current conductivity meters handle metals only, and operators must look up readings in tables by hand.
- Low-cost near-infrared plastic scanners identify plastics only.

No affordable tool identifies both metals and common non-metals by measuring their physical properties. As a result, unidentified stock often gets thrown away instead of reused.

# Solution

MaterialID is a bench instrument with a flat sensing platform and a single button. The user places an unknown sample on the platform (at least 3 mm thick, with a flat face at least 50 × 50 mm) and presses the button. The instrument measures three properties of the material itself, independent of the sample's size and shape:

1. **Electrical conductivity and magnetic response,** from a multi-frequency eddy current probe under the platform. It measures at 60 kHz, plus 250 kHz for low-conductivity metals such as stainless steel.
2. **Dielectric permittivity and loss tangent** for non-conductors, from a guarded fringing-field electrode under the platform.
3. **Mechanical damping,** from a controlled solenoid tap followed by a fit to the decay of the sample's ringing. Damping is used rather than ringing pitch because pitch depends mostly on the sample's shape.

The eddy current and dielectric measurements share one digital lock-in amplifier on the microcontroller. It samples the excitation and the response at the same time, so the result doesn't depend on drift in the excitation amplitude or frequency.

A physics-based decision tree compares the measurements against a reference table that we build from our own measurements of known samples. The instrument then displays the material, the measured values, and a confidence level. If nothing in the table matches closely enough, it reports "unknown." The system uses no machine learning and needs no training data.

The target set is nine materials: 6061-T6 and 7075-T6 aluminum, C110 copper, C360 brass, 1018 steel, 304 stainless steel, soda-lime glass, acrylic (PMMA), and HDPE.

The project has five subsystems: (1) excitation and lock-in engine, (2) eddy current probe and front end, (3) dielectric sensor and front end, (4) impulse excitation and ring-down, and (5) control, user interface, and power.

# Solution Components

## Subsystem 1: Excitation and Lock-in Engine

A DDS chip generates sine excitation at 60, 100, or 250 kHz, and a current buffer drives the selected sensor. The microcontroller samples the excitation and the sensor response simultaneously on two ADCs. It computes their in-phase and quadrature components over thousands of cycles to find the sensor's complex impedance change.

- MCU: STMicroelectronics STM32G474RET6 (dual simultaneous 12-bit ADCs at 4 MS/s, CORDIC math accelerator)
- Direct digital synthesizer: Analog Devices AD9833BRMZ
- Excitation buffer: TI BUF634A
- Sensor-select analog multiplexer: TI TMUX1108

## Subsystem 2: Eddy Current Probe and Front End

A ferrite-backed probe coil sits under a 0.5 mm PTFE cover. It is wired in a bridge with an identical reference coil that faces air, and an instrumentation amplifier amplifies the imbalance between them. Conductivity (%IACS) comes from a calibrated map of how the coil's impedance shifts. Ferromagnetic materials raise the coil's inductance while non-magnetic metals lower it, which flags them. A temperature sensor at the probe allows temperature compensation. We will verify the calibration samples' true conductivity with 4-wire resistance measurements on the lab's Keysight 34461A.

- 2× ferrite pot cores (TDK B65541 series, P14×8) wound with 0.2 mm magnet wire
- Instrumentation amplifier: TI INA828
- Temperature sensor: TI TMP117 (±0.1 °C)
- 0.5 mm PTFE sheet as the platform cover

## Subsystem 3: Dielectric Sensor and Front End

An interdigitated electrode is etched into the platform PCB, with a driven guard layer beneath it so the sensor ignores objects below the platform. A transimpedance amplifier converts the electrode current to a voltage for the lock-in engine at 100 kHz. We calibrate against air, PTFE, and a glass reference to get relative permittivity and loss tangent. This subsystem runs only when the eddy current probe finds no conductor.

- Interdigitated electrode on PCB: 30 × 30 mm, 0.5 mm fingers and gaps, with rear driven guard
- Transimpedance amplifier and guard driver: TI OPA2320

## Subsystem 4: Impulse Excitation and Ring-down

A solenoid under the platform taps the sample from below through a small hole, while the sample rests on four soft silicone pads. A MOSFET delivers a timed pulse from a regulated 12 V rail, and a current-sense amplifier confirms the tap energy is the same each time. A MEMS microphone records the ringing. Firmware finds the dominant frequency, extracts the decay envelope, and computes the loss factor, which separates metals and glass (low damping) from plastics (high damping).

- 12 V push-pull solenoid: Adafruit 412
- Solenoid driver MOSFET: Infineon IRLML6344, with SS34 flyback Schottky diode
- Solenoid current sense amplifier: TI INA180
- Analog MEMS microphone: TDK InvenSense ICS-40180
- Microphone preamp and anti-alias filter: TI OPA344

## Subsystem 5: Control, User Interface, and Power

The microcontroller runs the measurement sequence with the electrical measurements first and the solenoid tap last, so switching noise can't corrupt readings. It then runs the decision tree, shows the result on an OLED, and streams raw data over USB for calibration and logging. A 12 V adapter powers the solenoid directly, a buck converter makes 5 V, and separate 3.3 V regulators feed the digital circuits and the noise-sensitive analog circuits.

- 12 V / 2 A certified external power adapter
- 5 V buck converter: TI TPS562201
- 3.3 V digital regulator: Diodes Inc. AP2112K-3.3
- 3.3 V low-noise analog regulator: TI TPS7A2033
- 0.96" SSD1306 I2C OLED display, tactile button, USB-C connector (native USB on the STM32G474)

# Criterion For Success

- Measure the electrical conductivity of non-ferromagnetic metal samples (at least 3 mm thick, flat face at least 50 × 50 mm) within ±2 %IACS over the range 2–100 %IACS, compared against 4-wire resistivity measurements of the same stock.
- For each target material, the primary property measured on three samples of different size and shape agrees within ±5% of their mean (within ±0.5 %IACS for metals below 10 %IACS). The primary property is conductivity for metals and permittivity for non-metals.
- Correctly identify the material in at least 90% of 90 trials: 9 materials × 3 samples each (at least one sample per material not used to build the reference table) × 3 placements. Each result must appear within 5 s of the button press, with no user-entered sample information.
- Repeat damping measurements within ±10% over 10 taps on the same sample, and separate the metal and glass group from the acrylic and HDPE group by a factor of at least 5 in loss factor.

Modularized Electronic Locker

Jack Davis, Joshua Nolan, Jake Pu

Modularized Electronic Locker

Featured Project

Group Member: Jianhao (Jake) Pu [jpu3], Joshua Nolan [jtnolan2], John (Jack) Davis [johnhd4]

Problem:

Students living off campus without a packaging station are affected by stolen packages all the time. As a result of privacy concerns and inconsistent deployment, public cameras in Champaign and around the world cannot always be relied upon. Therefore, it can be very difficult for victims to gather evidence for a police report. Most of the time, the value of stolen items is small and they are usually compensated by the sellers (Amazon and Apple are very understanding). However, not all deliveries are insured and many people are suffering from stolen food deliveries during the COVID-19 crisis. We need a low-cost solution that can protect deliveries from all vendors.

Solution Overview:

Our solution is similar to Amazon Hub Apartment Locker and Luxer One. Like these services, our product will securely enclose the package until the owners claim the contents inside. The owner of the contents can claim it using a phone number or a unique user identification code generated and managed by a cloud service.

The first difference we want to make from these competitors is cost. According to an article, the cost of a single locker is from $6000 - $20000. We want to minimize such costs so that we can replace the traditional mailbox. We talked to a Chinese manufacturer and got a hardware quote of $3000. We can squeeze this cost if we just design our own control module on ESP32 microcontrollers.

The second difference we want to make is modularity. We will have a sensor module, a control module, a power module and any number of storage units for hardware. We want to make standardized storage units that can be stacked into any configuration, and these storage units can be connected to a control module through a communication bus. The control module houses the hardware to open or close all of the individual lockers. A household can purchase a single locker and a control module just for one family while apartment buildings can stack them into the lockers we see at Amazon Hub. I think the hardware connection will be a challenge but it will be very effective at lowering the cost once we can massively manufacture these unit lockers.

Solution Components:

Storage Unit

Basic units that provide a locker feature. Each storage unit will have a cheap microcontroller to work as a slave on the communication bus and control its electronic lock (12V 36W). It has four connectors on top, bottom, left, and right sides for stackable configuration.

Control Unit

Should have the same dimension as one of the storage units so that it could be stacked with them. Houses ESP32 microcontroller to run control logics on all storage units and uses the built-in WiFi to upload data to a cloud server. If sensor units are detected, it should activate more security features accordingly.

Power Unit

Power from the wall or from a backup battery power supply and the associated controls to deliver power to the system. Able to sustain high current in a short time (36W for each electronic lock). It should also have protection against overvoltage and overcurrent.

Sensor Modules

Sensors such as cameras, motion sensors, and gyroscopes will parlay any scandalous activities to the control unit and will be able to capture a photo to report to authorities. Sensors will also have modularity for increased security capabilities.

Cloud Support

Runs a database that keeps user identification information and the security images. Pushes notification to end-users.

Criterion for Success:

Deliverers (Fedex, Amazon, Uber Eats, etc.) are able to open the locker using a touchscreen and a use- provided code to place their package inside. Once the package is inside of the locker, a message will be sent to the locker owner that their delivery has arrived. Locker owners are able to open the locker using a touchscreen interface. Owners are also able to change the passcode at any time for security reasons. The locker must be difficult to break into and offer theft protection after multiple incorrect password attempts.

Project Videos