Chemistry + materials¶

Weeks¶

Week 17¶

Spine: OpenStax Chemistry 2e + MIT 3.091

Reading: Atomic structure, periodic trends, bonding, molecular geometry; MIT sessions 1-12

Know: Predict bonding and molecular/solid structure from electronic structure and intermolecular forces.

Reconstruct: Regenerate Lewis/VSEPR/MO-level bonding logic and lattice-energy trends.

Do: Predict qualitative properties of candidate battery/electrolyte/coating materials from bonding and polarity.

Defend: Which properties can bonding models predict reliably and where do they become crude?

Gate: Pass: property prediction includes explicit model limits.

Source: source

Week 18¶

Spine: MIT 3.091

Reading: Electronic materials + crystalline materials, sessions 13-20

Know: Use crystal systems, Miller indices, XRD intuition, defects and band concepts to connect structure to properties.

Reconstruct: Derive Bragg condition geometrically and simple defect-concentration Boltzmann scaling.

Do: Index a toy diffraction pattern and propose how a defect/dopant would change conductivity/strength.

Defend: Why are defects often the technology rather than merely imperfections?

Gate: Pass: infer structure from measurement and predict one property consequence.

Source: source

Week 19¶

Spine: OpenStax Chemistry 2e

Reading: Ch. 12-13 kinetics/equilibrium; Ch. 16 thermodynamics

Know: Connect rate laws, activation barriers, equilibrium constants and free energy.

Reconstruct: Derive Arrhenius linearization and ΔG-K relation.

Do: Fit kinetic data, estimate activation energy, and optimize a reaction under equilibrium/throughput constraints.

Defend: Why can thermodynamically favorable reactions be technologically useless?

Gate: Pass: separate equilibrium yield from reaction rate and transport limits.

Source: source

Week 20¶

Spine: OpenStax Chemistry 2e + MIT 3.091

Reading: Electrochemistry + diffusion/kinetics; MIT sessions 23-24 and electrochemistry materials

Know: Model redox potentials, cells, transport and degradation; understand electrochemical energy storage.

Reconstruct: Derive Nernst-equation directionality and diffusion timescale/current-limitation intuition.

Do: Build a simple battery-cell model with open-circuit voltage, internal resistance, diffusion-like rate limit and degradation proxy.

Defend: Where does a battery's lost energy go?

Gate: Pass: energy, charge and transport balances all close.

Source: source

Week 21¶

Spine: MIT 3.091 + TU Delft structures/materials

Reading: Phase diagrams, polymers/composites, materials selection, processing-structure-property

Know: Use phase diagrams and material indices; connect processing/defects/microstructure to performance and manufacturability.

Reconstruct: Derive lever rule and one Ashby-style performance index for a constrained design.

Do: Select material/process for a lightweight pressure vessel or thermal structure and justify against competing classes.

Defend: When does the 'best material' cease to exist because manufacturing/repair/supply constraints dominate?

Gate: Module defense: material selection includes chemistry, structure, processing, failure and supply/scale.

Source: source

Exit gate¶

Closed-book: 150 min: bonding, crystal/defect, kinetics/equilibrium, electrochemistry, phase diagram/material selection.

Novel problem: Select reaction/material/process for a frontier device under temperature, mass, cycle-life and supply constraints.

Artifact: Battery/catalyst/material model plus materials-selection decision matrix.

Defend: Defend thermodynamic vs kinetic limits, degradation, defects, processability and scale.

Pass criterion: Pass if chemistry/structure/process/property claims are quantitatively linked.

Transfer problems¶

Try these before consulting solutions or asking for the complete answer.

1. Bonding: Rank candidate materials by likely melting point/polarity/conductivity from bonding.

2. Crystal: Index a simple cubic diffraction peak set and infer lattice spacing.

3. Defect: Estimate vacancy concentration change with temperature using Boltzmann scaling.

4. Kinetics: Fit Arrhenius data and predict lifetime at a new temperature.

5. Equilibrium: Compute reaction equilibrium response to temperature/concentration changes.

6. Electrochemistry: Compute cell voltage shift with concentration and identify sign.

7. Diffusion: Estimate dopant diffusion depth versus time/temperature.

8. Phase diagram: Use lever rule to determine phase fractions.

9. Materials index: Derive a mass-minimizing material index for a stiffness-limited beam.

10. Degradation: Create a coupled model where a material property degrades due to cycling, temperature and environment.

Textbooks¶

See the five-book resource page.