Week 1 HW: Final Project Ideas

Biomanufacturing Report: Algal Nanocellulose for Sustainable Packaging

1. Target product and motivation

Target product: Cellulose nanocrystals (CNC/NCC) extracted from cultured microalgal biomass, intended as a reinforcing and barrier additive for compostable food-packaging film — replacing the plastic film currently used for single-use wraps, takeout containers, and produce bags.

Motivation: Single-use plastic packaging is one of the most visible and least-recycled categories of plastic waste, and most biodegradable alternatives currently rely on plant-derived cellulose (wood pulp) or petroleum-derived bioplastics, both of which carry significant land-use or fossil-carbon costs. Nanocellulose is attractive here because even small amounts (typically a few percent by weight) meaningfully improve the mechanical strength and gas-barrier properties of biodegradable films, making thinner, less material-intensive packaging viable. Sourcing that nanocellulose from cultured microalgae rather than trees or bacteria is interesting for two structural reasons: microalgae fix atmospheric CO₂ directly as autotrophs (no separate sugar feedstock is required, unlike bacterial cellulose production), and they can be cultivated on non-arable land without competing with food or timber production (unlike wood pulp). The intended audience is packaging manufacturers and consumers looking for a genuinely lower-footprint alternative to plastic film, at a scale relevant to a single institution (see Part 4) as a proof of concept before wider adoption.

2. Proposed living system

Proposed chassis: Chlorella sorokiniana, a unicellular green microalga, cultivated autotrophically in a liquid photobioreactor.

High-level process:

• Inputs: atmospheric CO₂ (as carbon source), light (as energy source), a simple inorganic nutrient medium (nitrogen, phosphorus, trace metals), and water.
• Biological process: the algae grow photoautotrophically, fixing CO₂ into biomass via photosynthesis. Cellulose is synthesized as a structural component of the algal cell wall, embedded alongside other polysaccharides and glycoproteins.
• Downstream (non-living) process: biomass is harvested by centrifugation, dried, then chemically treated (H₂O₂ bleaching to remove pigments, followed by H₂SO₄ hydrolysis) to isolate the crystalline cellulose fraction and remove the amorphous cell-wall material around it.
• Output: a purified cellulose nanocrystal (NCC) pellet, blended at a low weight percentage into a compostable packaging film formulation (e.g., a PLA or starch-based film matrix).

A few reasonable assumptions underlie this proposal: that the cellulose content and crystallinity achievable from C. sorokiniana (demonstrated at small scale) will hold reasonably well at larger cultivation volumes; that the extraction chemistry doesn’t need fundamental redesign to scale (only parallelization/automation, discussed below); and that a ~5% NCC loading in a film matrix is sufficient to achieve the target mechanical/barrier properties, consistent with typical CNC-reinforced film loadings reported in the packaging literature.

3. Automation approach

Primary focus: Automated liquid handling for extraction-condition optimization

The clearest, most immediately actionable automation opportunity is at the chemical extraction and hydrolysis step, using a desktop liquid-handling robot such as an Opentrons OT-2.

In the reference process, the hydrolysis step (H₂O₂ bleaching followed by H₂SO₄ treatment) was run as a single 60-minute protocol, manually pipetted, with the underlying study explicitly noting this gave “intermediate” results — larger, more amorphous particles form at shorter hydrolysis times, and smaller, more crystalline particles form at longer times, but the true yield-maximizing condition was never mapped. This is exactly the kind of multi-parameter optimization problem liquid-handling automation is built for:

• What gets automated: the OT-2 would dispense biomass, H₂O₂, and H₂SO₄ in a systematic grid across a 96-well plate — varying hydrolysis time, acid concentration, and temperature (via a plate heater/shaker module) — then automatically pull aliquots at fixed intervals for the downstream cellulose quantification assay (enzymatic hydrolysis + DNS colorimetric glucose assay, which is itself plate-reader compatible).
• Why this step specifically: it directly targets the single limitation the source study called out as unresolved and most likely to be limiting overall NCC yield. Instead of interpolating between two other groups’ published protocols (30-minute vs. 90-minute treatments), a single overnight automated run could generate a full time × concentration × temperature response surface and identify the actual optimum for this specific biomass.
• Why this technology tier: an Opentrons-class robot (a few thousand dollars) matches the philosophy of the underlying process — a low-cost, decentralized, non-industrial system — rather than requiring a large-scale Cloud Lab contract, which would be disproportionate to the scale of the biology being optimized at this stage.

Additional automation targets

• Culturing (automated photobioreactor control): the current culturing setup runs on a fixed light schedule and constant aeration rate with no feedback. A simple microcontroller-based system (e.g., Raspberry Pi/Arduino) driving LED intensity and CO₂/air dosing in response to real-time optical-density readings could push biomass yield closer to the higher outputs reported elsewhere in the literature for the same species, rather than following a static protocol.
• Screening (parallel strain/condition testing): a liquid-handling robot paired with a multi-well plate photobioreactor array could screen multiple algal strains or nutrient conditions in parallel for cellulose content specifically (not just biomass), since cellulose content varies widely by species and condition — a higher-cellulose strain could improve output more than optimizing extraction on a mediocre one.
• Sampling/monitoring (contamination detection): because low-cost, non-sterilizable cultivation vessels carry real contamination risk, automated in-line sensing (turbidity, pH, dissolved O₂, or periodic automated imaging) could catch contamination early enough to safely enable higher-yielding heterotrophic or mixotrophic feeding — a yield gain the source researchers identified but declined to pursue specifically because of this risk.

4. Scale and timeline estimate

(a) How much?

Scale definition: enough NCC to replace conventional plastic cling film for a mid-sized university campus (population ≈ 30,000 students and staff) for one year.

Assumptions (stated explicitly, since good sourced numbers for “film use per person” don’t really exist):

• Average film/wrap use: ~50 g of packaging film per person per year (a rough estimate for food-service wrap/bag use in a campus dining context)
• NCC loading in the film: 5% by weight (a typical CNC reinforcement loading level)
• Cellulose content of dry algal biomass: 10% (midpoint of the 9.00–10.23% measured for C. sorokiniana)
• Fraction of extracted cellulose that ends up as the NCC (vs. the coarser MCC) fraction: ~30% (an assumption — the source study reports the extracted material is “predominantly MCC with a smaller fraction of NCC,” but doesn’t give an exact split)

Calculation:

• Total film needed: 30,000 people × 50 g/person = 1,500,000 g = 1.5 tonnes of film/year
• NCC needed: 1.5 tonnes × 5% = 75 kg NCC/year
• Dry biomass needed: 75 kg NCC ÷ (10% cellulose × 30% NCC fraction) = 75 kg ÷ 0.03 = 2,500 kg (2.5 tonnes) of dry algal biomass/year

(b) How long?

Prototype scale (matching the source study’s PET-bottle bioreactors):

• Biomass concentration achieved: 1.23 g/L
• Culture volume needed: 2,500,000 g ÷ 1.23 g/L ≈ 2,032,500 L (~2,033 m³)
• Bioreactor unit size: 0.9 L working volume per PET bottle
• Number of bottles needed if run as a single batch: ~2.26 million bottles

This number is obviously impractical at the individual-bottle scale — which is itself a useful finding: it demonstrates quantitatively why yield improvement (via automation-driven optimization) matters more than simply scaling out identical low-cost units. Even with an automated modular rack running, say, 10,000 bottles in parallel (30-day growth cycle per batch), roughly 227 sequential batch cycles ≈ 6,800 days (~18.6 years) would be required — clearly impractical.

Manufacturing scale (industrial photobioreactor productivity): published productivities for optimized microalgal photobioreactors/high-rate ponds reach roughly 70 tonnes dry biomass per hectare per year. At that productivity:

• Land area needed for 2.5 tonnes/year: 2.5 t ÷ 70 t/ha/yr ≈ 0.036 hectares (~360 m², roughly the footprint of a basketball court)
• Time to produce 2.5 tonnes at that areal rate, if run continuously: (2.5/70) × 365 days ≈ 13 days of full-area production per year

Takeaway: the gap between these two numbers (18+ years vs. ~13 days) represents the central engineering problem of this proposal. Moving from validated lab-scale biology to a real photobioreactor system — plus the yield/purity improvements automation is meant to unlock — is what closes that gap, not simply building more PET bottles.

5. Open technical unknowns

1. What fraction of extracted cellulose actually becomes usable NCC (vs. coarser MCC), and how much this changes with the optimized hydrolysis conditions proposed in Part 3. This assumption (30%) was not measured in the source study and materially changes the entire Part 4 calculation — it would need to be experimentally determined via the same automated hydrolysis-optimization screen proposed above.

2. Whether cellulose content and crystallinity hold up when moving from small PET-bottle cultures to large photobioreactor or open-pond systems. Light penetration, mixing, and CO₂ transfer all change substantially at scale, and cell-wall composition can shift with growth conditions — this is an open question that would need to be tested at an intermediate pilot scale before committing to the 360 m² system in Part 4.

3. The true environmental/energy cost of the extraction chemistry (H₂O₂, concentrated H₂SO₄, autoclaving) at scale, and how it compares on a full life-cycle basis to bacterial cellulose or wood-pulp cellulose extraction. The “cleaner carbon” argument for algae rests on the cultivation stage, but the downstream chemical processing burden is not yet well quantified against the alternatives — a proper life-cycle assessment across all three routes (energy in, water use, chemical inputs, land use) is missing from the literature and would be needed to make the environmental case rigorously rather than qualitatively.

References

1. Reyna-Martínez, G.R., López-Chuken, U.J., Beltrán-Rocha, J.C., Avalos-Alanís, F.G., Gómez-Loredo, A.E., Chávez-Guerrero, L., & Silva-Mendoza, J. (2026). Production of microcellulose and crystalline nanocellulose from the microalga Chlorella sorokiniana. Journal of Applied Phycology, 38, 1241–1247. https://doi.org/10.1007/s10811-026-03828-6

2. Uzyol, H.K., & Saçan, M.T. (2017). Bacterial cellulose production by Komagataeibacter hansenii using algae-based glucose. Environmental Science and Pollution Research, 24(12), 11154–11162. https://doi.org/10.1007/s11356-016-7049-7

3. Zhu, C. et al. (2025). The potential microalgae-based strategy for attaining carbon neutrality and mitigating climate change: a critical review. Frontiers in Marine Science. https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2025.1644390/full

4. Demirbas, A. (2017). Microalgae: a potential plant for energy production. Tandfonline. https://www.tandfonline.com/doi/full/10.1080/24749508.2017.1332853

Final Project