X-ray diffraction, SEM and TEM, DSC and TGA, tensile, hardness, fatigue and fracture testing, ASTM methods, polymer, ceramic and thin-film processing, and materials databases.

Materials Characterization & Processing

## Why it matters

The same polymer can be stiff or soft, clear or cloudy, tough or brittle depending on how it was made and processed. A materials scientist in plastics or composites spends much of their time linking processing conditions to structure (chain length, crystallinity, orientation, voids) and structure to properties. When a molded part cracks or warps, the cause is usually in that chain of links.

## Thermoplastics, thermosets and elastomers

- **Thermoplastics** (polyethylene, polypropylene, nylon, PET, polycarbonate) are long chains that soften on heating and can be remelted. They are processed as melts.
- **Thermosets** (epoxies, phenolics, unsaturated polyesters) cure into a crosslinked network that does not remelt. They are processed as liquids or soft resins that react in the mold.
- **Elastomers** are lightly crosslinked networks above their Tg, so they stretch and recover.

## Molecular weight

Polymers contain chains of many lengths, so we use averages:

```text
number average   Mn = sum(N_i * M_i) / sum(N_i)
weight average   Mw = sum(N_i * M_i^2) / sum(N_i * M_i)
dispersity       D  = Mw / Mn   (>= 1)
```

**Worked example.** A blend has 10 chains of 10,000 g/mol and 10 chains of 100,000 g/mol. `Mn = 55,000`; `Mw = (10 × 10^8 + 10 × 10^10) / (10 × 10^4 + 10 × 10^5) = 91,800`; `D = 1.67`. Mw is pulled toward the long chains, which dominate melt viscosity and toughness.

Higher molecular weight usually means higher toughness and strength, but also a much higher melt viscosity, which makes molding harder. Processing itself can cut chains: excessive melt temperature, long residence time, or moisture in nylon and PET (hydrolysis) lower the molecular weight and make parts brittle. That is why these resins are dried before molding.

## Crystallinity and cooling

Semicrystalline polymers (PE, PP, nylon, PET) form crystalline lamellae between amorphous regions. Crystallinity raises stiffness, strength, chemical resistance and shrinkage, and lowers clarity and toughness. It depends strongly on cooling rate:

- A **hot mold** and slow cooling give higher crystallinity (and more shrinkage).
- A **cold mold** and fast cooling give lower crystallinity; PET quenched fast enough stays amorphous and clear, which is how bottle preforms are made.

You measure the result with DSC (previous module): the melting enthalpy divided by that of a 100% crystalline polymer.

## Melt processing

- **Extrusion** pushes melt through a die continuously: pipe, film, sheet, profiles, fiber. Drawing the extrudate orients chains along the machine direction, so film is stronger in one direction.
- **Injection molding** fills a closed mold at high pressure, packs it to compensate for shrinkage, then cools it. Key settings are melt temperature, mold temperature, injection speed, pack pressure and time, and cooling time. Results to watch: **shrinkage and warpage**, **weld lines** where flow fronts meet (weaker), **sink marks** at thick sections, **residual stress** and **flow-induced orientation**.
- **Blow molding** and **thermoforming** shape a parison or sheet with air pressure or vacuum.

Design and processing interact: uniform wall thickness, generous radii and gate placement prevent many defects before any setting is changed.

## Composites

A composite combines a reinforcement (glass, carbon or aramid fibers) with a matrix (usually a polymer). Fibers carry load; the matrix transfers load, holds the fibers in place and protects them.

For continuous fibers aligned with the load, the **rule of mixtures** estimates stiffness:

```text
longitudinal  E1 = Vf * Ef + Vm * Em
transverse    1/E2 = Vf/Ef + Vm/Em   (a rough lower-bound estimate)
```

**Worked example (illustrative values).** Carbon fiber with `Ef = 230 GPa` in epoxy with `Em = 3.5 GPa` at a fiber volume fraction of 0.60: `E1 = 0.6 × 230 + 0.4 × 3.5 = 139 GPa`, but `E2` is only about 8.6 GPa. The material is very stiff along the fibers and weak across them, which is why laminates stack plies at 0, ±45 and 90 degrees.

Processing routes include hand layup, **prepreg** cured in an **autoclave** (heat plus pressure, low voids, aerospace), resin transfer molding (RTM), filament winding and pultrusion. The cure cycle (time, temperature, pressure) sets the degree of cure and Tg, and pressure squeezes out voids. A few percent of voids can cut interlaminar shear strength noticeably, so void content is a routine quality check (by density, burn-off or micro-CT).

## Common mistakes

- **Blaming the resin** for brittle parts when wet resin or overheating degraded the molecular weight.
- **Ignoring orientation**: testing bars molded in one flow direction and assuming the part behaves the same in every direction.
- **Treating composites as isotropic** and using one modulus for all directions.
- **Under-curing** a thermoset to save cycle time, which lowers Tg and strength.

## Safety and training

Polymer and composite processing involves hot melts, high pressures, moving machinery, curing agents and fine fibers and dusts. Work on these processes only after your employer's or institution's training, with the required guarding, ventilation and protective equipment.

## Recap

- Mn, Mw and dispersity describe chain length; Mw drives viscosity and toughness, and processing can degrade it.
- Cooling rate controls crystallinity, which controls stiffness, shrinkage and clarity.
- Injection molding defects come from fill, pack and cool; composites are anisotropic and sensitive to cure and voids.


Relate molecular weight, crystallinity and processing (extrusion, injection molding, curing) to polymer and composite properties.

Polymers and composites

#68 Polymer Processing | Part I | Polymers Concepts, Properties, Uses & Sustainability

The Incredible Properties of Composite Materials

## Why it matters

Ceramics, semiconductors and thin films are where processing control is most extreme. A ceramic part's strength depends on the largest pore left after sintering; a transistor depends on films a few nanometres thick being uniform across a 300 mm wafer. Materials scientists in these fields design and tune processes, then characterize the result with the tools from module 1.

## Ceramic processing

Most technical ceramics (alumina, zirconia, silicon nitride, silicon carbide) cannot be melted and cast like metals, so they are made from **powders**:

1. **Powder preparation**: particle size, purity and agglomeration control everything downstream.
2. **Forming** a "green" body: pressing, slip casting, tape casting (thin sheets for capacitors and substrates), injection molding with a binder, or additive manufacturing.
3. **Binder burnout** at low temperature.
4. **Sintering** below the melting point: atoms diffuse, necks grow between particles, pores shrink and the part densifies.

Densification means shrinkage. If a green body is 55% dense and sinters to 98%, mass is conserved, so the volume shrinks by the density ratio and each dimension by its cube root:

```text
linear shrinkage = 1 - (rho_green / rho_final)^(1/3) = 1 - (0.55 / 0.98)^(1/3) = 0.175
```

About 17.5% in every direction, which is why ceramic tooling is oversized and why uneven green density causes warping. Higher temperatures and longer times densify more but also grow grains, and large grains or residual pores lower strength. Because ceramics are brittle, strength is governed by flaws and is statistical (Weibull analysis), so a few large pores matter more than average porosity.

## Semiconductor fabrication in one page

Chips are built on single-crystal silicon wafers (grown by the Czochralski method and sliced). A process flow repeats a handful of steps hundreds of times:

- **Oxidation** grows SiO2 on silicon.
- **Deposition** adds films: dielectrics, polysilicon, metals.
- **Lithography** coats photoresist, exposes a pattern through a mask (deep-UV or EUV light), and develops it.
- **Etching** removes material where the resist is open; plasma (dry) etching gives vertical walls.
- **Doping** by ion implantation, then annealing to activate dopants and repair damage.
- **Chemical mechanical polishing (CMP)** flattens each layer.
- **Metrology** at every step: film thickness by ellipsometry, critical dimensions by SEM, defects by optical inspection.

Everything happens in cleanrooms, because a single particle can kill a die.

## Thin-film deposition

Deposition processes fall into a few families. Being able to explain one end to end is a common interview question.

### PVD: physical vapour deposition

Material is turned into vapour physically and condenses on the substrate, under vacuum.

- **Thermal or e-beam evaporation**: heat a source until it evaporates. Simple, high purity, but line-of-sight, so it coats steps poorly.
- **Sputtering**, step by step: pump the chamber to high vacuum; admit argon at low pressure; apply a voltage to the target to strike a plasma; argon ions accelerate into the target and knock atoms off; those atoms travel to the substrate and build a film. Magnets behind the target (**magnetron sputtering**) trap electrons near it and raise the rate. Adding nitrogen or oxygen (**reactive sputtering**) makes nitrides and oxides such as TiN. Power, pressure, substrate temperature and bias control density, stress and grain structure.

### CVD: chemical vapour deposition

Precursor gases react on a heated surface to form the film, for example silane (SiH4) decomposing to polysilicon. CVD coats complex shapes more evenly than PVD. Plasma-enhanced CVD (PECVD) runs at lower temperature.

### ALD: atomic layer deposition

ALD splits a CVD reaction into two self-limiting half-reactions separated by purges. For alumina from trimethylaluminium and water, each cycle adds roughly 0.1 nm, regardless of small changes in dose. **Illustrative calculation:** a 10 nm gate-dielectric layer at about 0.1 nm per cycle needs about 100 cycles. ALD gives superb thickness control and conformality inside deep trenches, at the cost of speed.

### Epitaxy

Epitaxial growth (CVD epitaxy, molecular beam epitaxy) continues the substrate's crystal lattice in the film. It is used for compound semiconductors such as GaAs and GaN in LEDs and lasers, where lattice mismatch between film and substrate creates strain and defects.

## Characterizing films

Thickness by ellipsometry, profilometry or X-ray reflectivity; phase and texture by XRD; morphology by SEM; composition by XPS or EDS; stress from wafer curvature. Film stress is a frequent cause of cracking and delamination.

## Common mistakes

- **Treating sintering shrinkage as small** and machining to final size before firing.
- **Choosing evaporation for a stepped surface** and getting gaps on sidewalls.
- **Ignoring film stress** until the coating peels.
- **Reporting average porosity** when the largest flaw controls ceramic strength.

## Safety and training

Furnaces, vacuum systems, plasmas, high voltages and toxic or pyrophoric precursor gases (silane, arsine, trimethylaluminium) are serious hazards. Cleanroom and deposition work requires your facility's training, gowning and supervision before you touch a tool.

## Recap

- Ceramics: powder, forming, burnout, sintering; densification shrinks every dimension and flaws control strength.
- Chips: oxidation, deposition, lithography, etching, doping and polishing, repeated with metrology at each step.
- PVD (evaporation, sputtering), CVD and ALD trade rate, purity, coverage and thickness control.


Follow ceramic powder processing and sintering, the main semiconductor fabrication steps, and how PVD, CVD and ALD deposit thin films.

Ceramics, semiconductors, and thin films

Sputtering: What is it and how does sputter deposition work?

Thin Film Deposition

## Why it matters

Materials development used to be mostly trial and error: make a sample, test it, adjust. Today a team can screen tens of thousands of compounds in an afternoon using open databases of computed and measured properties, then spend lab time only on the most promising few. **Materials informatics** is that combination of databases, data skills and judgement. It is increasingly part of job descriptions for materials scientists in batteries, photovoltaics, catalysts and alloys.

## The databases

- **The Materials Project** (https://materialsproject.org): computed properties (formation energy, stability, band structure, elastic constants) for over 150,000 inorganic materials, from density functional theory (DFT). Free account; web interface and a Python API (`mp-api`). Checked on 2026-10-23.
- **AFLOW** and **OQMD**: other large DFT databases with their own APIs.
- **Crystallography Open Database** and the **ICSD** (commercial): experimental crystal structures.
- **NIST** data resources and handbooks (ASM, CRC) for measured properties such as thermal and mechanical data.
- Your own **lab data**, which is often the most valuable and the least organized.

## Key fields and what they mean

- **Formation energy** (eV/atom): energy to form the compound from its elements. Negative is favourable.
- **Energy above hull** (eV/atom): how far a compound is above the most stable combination of phases at that composition. `0` means it is on the convex hull (predicted stable). Small positive values (tens of meV/atom) are often still makeable as metastable phases; large values usually are not.
- **Band gap** (eV): the energy gap between valence and conduction bands; it decides whether a material is a metal, semiconductor or insulator, and which light it absorbs.
- **Density, crystal system, space group, elastic moduli**, and an ID (such as `mp-149` for silicon) that you should record with any data you use.

## Know the limits of computed data

DFT with the common PBE functional **underestimates band gaps**, often by 30 to 50% or more. Silicon's computed PBE gap is about 0.6 eV against a measured 1.12 eV. Use computed gaps to **rank** candidates and set loose filters, then check promising ones against experimental values or higher-level calculations. Other caveats: properties are for perfect crystals at 0 K, without defects, grain boundaries or temperature effects. Data is only as good as its provenance, so record the database version and IDs.

## Querying the Materials Project API

With a free API key, a typical query in your own Python environment looks like this (it needs the network, so it does not run in the browser exercise):

```python
from mp_api.client import MPRester

with MPRester("YOUR_API_KEY") as mpr:
    docs = mpr.materials.summary.search(
        band_gap=(1.0, 2.0),
        energy_above_hull=(0, 0.0),
        fields=["material_id", "formula_pretty", "band_gap", "density"],
    )
```

Keep the key out of your code and notebooks (use an environment variable), respect the API's rate limits, and save the raw results with the date so your screening is reproducible.

## Screening with pandas

Once results are in a DataFrame, screening is filtering, sorting and grouping:

```python
mask = df["band_gap_ev"].between(1.0, 2.0) & (df["e_above_hull_ev"] <= 0.0)
shortlist = df[mask].sort_values("band_gap_ev")
df.groupby("crystal_system")["density_g_cm3"].mean()
```

You will often need to parse chemical formulas (count atoms, find which elements are present) to filter out compounds with toxic, scarce or expensive elements. A small regular expression, `([A-Z][a-z]?)(\d*)`, splits "Al2O3" into element and count pairs; libraries such as `pymatgen` do this and much more in a full Python environment.

### Worked example

Suppose you want a stable absorber for a solar-cell layer, with a band gap in the computed range 1.0 to 2.0 eV (remember the underestimate: the real gaps will be higher). From an illustrative table of fourteen records:

1. Filter `band_gap_ev` between 1.0 and 2.0 and `e_above_hull_ev <= 0`: CdS, GaN and TiO2 (rutile) pass. Fe2O3 drops out because it sits 31 meV/atom above the hull, and ZnS at 2.02 eV is just outside the range. Relax the hull limit to 0.05 eV/atom and Fe2O3 comes back as a metastable candidate.
2. Sort by gap, then add filters for cost and toxicity (cadmium is a regulatory concern).
3. Check the survivors against measured gaps and literature before any lab work.

Machine learning extends the same workflow: models trained on database entries predict properties of compounds that have not been computed yet. They inherit every bias of their training data, so validation against held-out and experimental data is essential.

## Common mistakes

- **Taking computed band gaps at face value.**
- **Treating "energy above hull = 0" as "easy to make"**: synthesis conditions, kinetics and precursors still decide.
- **Losing provenance**: no database version, no IDs, no query date.
- **Committing API keys** to shared notebooks or repositories.

## Recap

- Open databases (Materials Project, AFLOW, OQMD, COD) let you screen thousands of materials by computed properties.
- Energy above hull measures stability; computed PBE band gaps are underestimates and good for ranking only.
- Screening is filtering, sorting, grouping and formula parsing in pandas; validate before you make anything.

## Try it

Open the **Do** tab to screen an illustrative materials table with pandas and parse chemical formulas.


Query a materials database for candidates by band gap and stability, understand where computed data are reliable, and screen with pandas.

Materials informatics

2. What is Materials Informatics?

Materials Project Website Walkthrough

Relate polymer, composite, ceramic, semiconductor and thin-film processing to properties, and query materials databases.