Manini Banerjee

Systems Designer & Research Engineer making environmental complexity legible and actionable.

COMPUTATIONAL ECOLOGY:

BIOPOD Co.
ECOLOGY · INFRASTRUCTURE · SYSTEMS
Designing deployable ecological infrastructure for wetland restoration based on environmental research.

Ecological AI

PREDICTION · INTERFACE · DATA
A Decision-Support System for Targeted Ecosystem Restoration.

Algorithmic Morphogenesis

BIO-COMPUTATION · DATA MATERIALIZATION
inscribing real-time human neurological data (EEG) into living algal morphology using phototactic actuation

HARDWARE & INTERFACES:

Threads

EDGE ML · HARDWARE · TEXTILES
Sentient Surfaces + Edge ML on Textiles. Human-AI Symbiosis through Ubiquitous Computing.

S(kin)-orb
HAPTICS · BIOSENSING · AFFECTIVE COMP. A bio-digital interface translating electromyographic (EMG) signals into haptic feedback for remote affective communication.

Vermiform

COMPONENT · SOFT ROBOTICS · WEARABLE
Bio-mimetic architectures for wearable computing.

Chito-bot
BIOCOMPOSITES · TRANSIENT ELECTRONICS
Investigating material compliance and structural integrity in bio-composite hexapods.

STRATEGIC SYSTEMS:

PFV

MOBILITY · ECOLOGY · SYSTEMS

Autonomous Mobility as Urban Bio-Infrastructure.

Aero

SENSING · MATERIALS · DATA
Developing robotic material systems for localized air-quality sensing and pollutant sequestration through embedded environmental intelligence.

Bio - intelligence
COPMUTATION · SYSTEMS · BIOLOGY
Exploring biological computation as an alternative model for system intelligence and control.

Aero

Designing intelligent materials embedded on robotic drones that
sense air health and sequesters toxins within a location

Details: Material Science • Microscopy • User research

Client: Silk Lab @ Tufts University

Date: 2024

Mentors: Giulia Guidetti • Fiorenzo Omenetto

Team: Manini Banerjee

"Aero" is an artistic installation of drones that dynamically sequester air pollutants and act as air quality sensors.

Each drone is crafted out of silk with a material intelligence that changes color depending on the air health of a particular location, offering an accessible visualization of a systemically complex issue.

This project envisions a multidisciplinary relationship between art, technology, citizen science, and the environment, contributing to a regenerative future.

Q: What if we developed biocompatible interventions that provide ecosystem services to combat poor air health?
A: Materials with intelligence that change color depending on the air health of a particular location, offering an accessible visualization of a systemically complex issue.

Optical Microscopy, BFR, 5X | Material Cross section prior to activation

Optical Microscopy, BFR, 10X | Top View (Left), revealing changes in the surface quality of the material upon base interaction. The material morphology coagulates

Optical Microscopy, BFR, 5X | Cross Section (Right) revealing how a basic environment causes a historical imprint ~0.9mm into the material

Optical Microscopy, BFR, 10X | Top View (Left) revealing changes in the surface quality of the material upon acidic interaction. The material morphology dissolves.

Optical Microscopy, BFR, 5X | Cross Section (Right) revealing how an acidic environment causes a historical imprint ~0.9mm into the material

Optical Microscopy, BFR, 5X | Cross Sections revealing how acidic and basic fluctuating environments cause historical imprints throughout the depth of the material.

Increasing the environmental resiliency of the material by varying the material composition

Q: How can we introduce restorative, empowering, and actionable objects into communities to educate and conduct air sensing?

A: Embedding the sensing silk foam into product applications for user interaction

Multiple material morphologies, or ‘skins’, were tested for the drones. Beginning with iterations on the left that implemented nature-based motifs that alluded to natural systems.

Subsequent morphologies experimented with drone-as-organism that would fit into food webs and ecosystems.

Methodologies for replicable designs were developed and biofabricated using laser-cutting techniques.

The Drone can be flown into hard-to-reach areas to collect historical information, which can then be studied colorimetrically once retrieved.

Q: Can airborne particles and air pollution be tackled by creating a closed-loop system?

A: Tuning the material’s morphology to sequester various sizes of particulate matter

The material morphology can be adjusted through post-processing, exposure to humidity, and subsequent lyophilization.

The material was cryo-cracked and studied through SEM (scanning electron microscopy)

The testing setup features an air chamber with an insert for materials to test permeability and particulate sequestration capabilities.

PM2.5 sensors on either end of the material function as particulate counters using an infrared system. Sensor information was collected by Arduino and converted into CSV files for subsequent analysis. Fans guided the particles through the chamber while a manometer ensured a constant air flow.

Materials of various morphologies and post-processing techniques were tested using the above setup to identify the optimal material design, post-processing methodology, and laser-cut depth to implement on the drone.

In addition to numerical sensor data, cro-cracked cross-sections of the material were studied using SEM to identify and characterize the distribution of particulate matter along its depth.