Mehnaj Jimy

Chemical & Molecular Engineering

Stony Brook UniversityB.E. expected May 2028

Undergraduate Researcher · Lee Research Group

I study precursor uptake in polymers using ALD/VPI and in-situ QCM. My independent projects cover semiconductor process monitoring and reactor modeling.

Seeking Summer 2027 engineering internships.

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Research

ALD Growth on Polymer Materials

I design and run ALD experiments on polymer films, particularly polyurethane, to study precursor uptake and retention. My work includes preparing films, collecting QCM, FTIR, and XRD measurements, and using Python to compare samples.

Research overview
ALD instrument with sample vials and tools on top; background edited
ALD system used in my research · edited photo

Selected engineering work

ColdPlateTwin: Water-Cooled Testbed Design

Active independent project · Preliminary CAD and synthetic simulations

I’m designing a water-cooled testbed with interchangeable flow inserts. I use CAD and Python to examine heat balance and pressure losses before physical testing.

Case study GitHub
Oblique view of the preliminary ColdPlateTwin CAD assembly
Preliminary CAD · not built hardware

Physics-Based ALD Reactor Model

Active independent project

My Python model follows precursor delivery and surface reactions through an ALD cycle. I compare well-mixed and spatial versions to see where their predictions differ along the reactor.

Working note
Well-mixed and spatial ALD surface completionSaved synthetic model output at the end of the A pulse. The well-mixed prediction is 97.8 percent throughout the reactor. The spatial prediction falls from approximately 100 percent near the inlet to 91.1 percent at the outlet. The vertical scale spans 90 to 100 percent.Surface completion (%)90100Well-mixed97.8%Spatial · 91.1%InletOutletWell-mixed and spatial ALD surface completionSaved synthetic model output at the end of the A pulse. The well-mixed prediction is 97.8 percent throughout the reactor. The spatial prediction falls from approximately 100 percent near the inlet to 91.1 percent at the outlet. The vertical scale spans 90 to 100 percent.Surface completion (%)90100Well-mixed97.8%Spatial · 91.1%InletOutlet
Synthetic model output · not experimental data

PVD Process Monitoring & Virtual Metrology

Independent project · Public Infineon datasets

I used Infineon’s public AlCu and WTi manufacturing data to screen process excursions and predict 17 released metrology targets.

I repeated the held-out test with identical target profiles kept together to check how much the split affected the scores.

Ordinary-split aggregate R²: AlCu 0.622 · WTi 0.604

Case study GitHub
Two questions from recorded process dataRecorded AlCu and WTi process data branches into statistical monitoring to review runs, and virtual metrology to predict 17 targets.Recordedprocess dataAlCu / WTiWhich runs need review?Statistical monitoringCan the targetsbe predicted?17-target virtual metrologyTwo questions from recorded process dataRecorded AlCu and WTi process data has two separate uses: statistical monitoring to review runs and virtual metrology to predict 17 targets.Recorded process dataAlCu / WTiWhich runs need review?Statistical monitoringCan the targets be predicted?17-target virtual metrology

Batch Reactor Simulator

I solve batch reaction kinetics in Python to follow concentration and conversion over time. Each case is checked against its analytical solution, so the numerical error is visible alongside the result.

Project note GitHub