PHA (polyhydroxyalkanoate) bioplastics manufacturing

PHA bioplastics manufacturing roadmap

First, this technology roadmap is given a clear and unique identifier:

• 2MPH - PHA manufacturing

This indicates that we are dealing with a “level 2” roadmap at the product level, where “level 1” would indicate a market level roadmap, and “level 3” or “level 4” would indicate an individual technology roadmap within PHA manufacturing.

Roadmap Overview

Plastic pollution. Credit: ead72 - stock.adobe.com Copyright: ©ead72 - stock.adobe.com

The problem of plastic accumulation in the natural environment is becoming a high profile problem. This is because oil-based plastics, while they are cheap and have good material properties, do not biodegrade.

One potential answer to this problem is bioplastics. The term bioplastics covers a lot of different types of materials, some of which are bio-based (i.e. generated from biological feedstocks) but not biodegradable, some of which are biodegradable but not biobased, and some that are both. One family of bioplastics that are bio-based AND biodegradable is PHAs (polyhydroxyalkanoates).

PHAs have the potential to replace oil-based plastics in terms of material properties! As one can see from the two images below, the range of properties that PHAs (blue) shows sizable overlap with the range of properties that oil-based plastics can exhibit.

One of the most exciting prospects is a variant of PHA called P(3HB). A comparison of properties with one of the most common forms of oil-based plastic, or polypropylene, is included below. In 2019 alone, a total of 16.8 billion pounds of non-biodegradable polypropylene was produced. Imagine if this amount could be shifted to a biodegradable plastic instead!

Property	P(3HB)	PP
Melting temperature (°C)	175-182	171-186
Glass-transition temperature (°C)	4	-10
Density (g/cm3)	1.25	0.92
Crystallinity (%)	65-80	65-70
Young's modulus (GPa)	3.5-4	1.7
Tensile strength (MPa)	40	38
Extension to break (%)	6-8	400
Solvent resistance	poor	good
Ultraviolet resistance	good	poor
Oxygen permeability (cm3 m-2 atm-1 d-1)	45	1700
Biodegradability	excellent	poor or non-existent
Cost ($/lb)	2.25-2.75	0.60-0.87

Sources:

• Lee, E. Y., & Choi, C. Y. (1997). Biosynthesis and biotechnological production of degradable polyhydroxyalkanoic acid. Biotechnology and Bioprocess Engineering : BBE, 2(1), 1-10. doi:http://dx.doi.org.libproxy.mit.edu/10.1007/BF02932454
• Kourmentza, C., Plácido, J., Venetsaneas, N., Burniol-Figols, A., Varrone, C., Gavala, H. N., & Reis, M. (2017). Recent Advances and Challenges towards Sustainable Polyhydroxyalkanoate (PHA) Production. Bioengineering (Basel, Switzerland), 4(2), 55. https://doi.org/10.3390/bioengineering4020055

As we can see from the table above, P(3HB) compares quite favorably to PP with regard to many mechanical properties and biodegradability. Of course, there are some properties that P(3HB) doesn't match well to - solvent resistance, extension to break, and oxygen permeability to name a few. As the science evolves, those gaps may close. The biggest barrier to increasing adoption is evidenced by the last row - the cost of P(3HB) is nearly 4x the cost of PP at present.

Unfortunately, PHAs currently are not competitive on a cost basis with oil-based plastics due to the high cost of manufacturing them. In fact, PHAs are only competitive with oil-based plastics when the price of oil is high. When the price of oil is low, PHA (and other bioplastics producers) suffer.

In this graph, we see a trend of oil prices (using Brent crude as a market) for the last several years. When the price of Brent crude fell in early 2014, the price of oil-based plastics fell in proportion. When the price of oil-based plastics fell, it led to several PHA bioplastics producers to go out of business because they could not produce PHA at a cost-competitive price with oil-based plastics. We want to break this dependence on oil prices. We propose a roadmap to reduce the cost of manufacturing PHA to parity or better with oil-based plastics.

Design Structure Matrix (DSM) Allocation

The technology hierarchy tree shows the levels of each technology and what is contained in each level of technology. We can also depict the interdependencies between the technologies as a DSM (design structure matrix). The way to interpret this DSM is the inputs are on the rows. For example, 3OPH (PHA producing engineered organisms) affects the technology selected for the 3FPH (fermentation), 3PPH (precipitation), 3SPH (sterilization), and 3XPH (separation) but is not itself affected by the technology selected for these steps.

Please note that interdependencies were only captured between levels (i.e. at level 2 or at level 3, but not crossing between level 2 and 3).

This DSM highlights how important the 3OPH and 3FPH technologies are to the overall process - they affect the rest of the process steps, but they are not affected in turn.

The level 4 technologies (4XXX) are specific variants of the level 3 technologies (3XXX) and as such are not depicted here.

Roadmap Model using OPM

We provide an Object-Process-Diagram (OPD) of the 2MPH technology in the figure below. This diagram captures the main object of the technology (PHA bioplastics manufacturing). Please draw your attention to the right side of the diagram to see current PHA bioplastics manufacturing operators. Then, please draw your attention to the bottom section of the diagram to see the different figures of merit.

High level OPM for 2MPH

An Object-Process-Language (OPL) description of this OPD is auto-generated and given below. It reflects the same content as the previous figure, but in a formal natural language.

• Engineered Organisms is physical and systemic.
• Substrate is physical and environmental.
• Purified PHA bioplastics is physical and systemic.
• Bioplastics Manufacturing Process Operator is physical and environmental.
• Reactor & Purification Equipment is physical and systemic.
• Bioplastics Engineering is informatical and environmental.
• Energy is physical and environmental.
• Bioplastics Process Designer is physical and environmental.
• CO2 is physical and systemic.
• Waste is physical and systemic.
• Biodegradability of Purified PHA bioplastics is informatical and systemic.
• CO2 intensity of PHA bioplastics Manufacturing is informatical and systemic.
• Tensile Strength of Purified PHA bioplastics is informatical and systemic.
• Young's Modulus of Purified PHA bioplastics is informatical and systemic.
• Water is physical and environmental.
• Water intensity of PHA bioplastics Manufacturing is informatical and systemic.
• Reactor & Purification Equipment Capital Cost of Reactor & Purification Equipment
• is informatical and systemic .
• Engineered Organisms Cost of Engineered Organisms is informatical and systemic.
• Cost of manufacturing of PHA bioplastics Manufacturing is informatical and systemic.
• Price per unit weight of Purified PHA bioplastics is informatical and systemic.
• Melting Point of Purified PHA bioplastics is informatical and systemic.
• Substrate Cost of Substrate is informatical and systemic.
• Water Cost of Water is informatical and systemic.
• Energy Cost of Energy is informatical and systemic.
• Air is physical and environmental.
• Elongation At Break of Purified PHA bioplastics is informatical and systemic.
• Figures Of Merit is physical and systemic.
• Kaneka Corporation is physical and environmental.
• PHB Industrial S.A. is physical and environmental.
• Shenzhen Ecomann Biotechnology Co. Ltd is physical and environmental.
• SIRIM Bioplastics is physical and environmental.
• TianAn Biologic Materials Co. Ltd is physical and environmental.
• Tianjin GreenBio Material Co. is physical and environmental.
• Purified PHA bioplastics exhibits Biodegradability, Elongation At Break, Melting Point, Price per unit weight, Tensile Strength, and Young's Modulus.
• PHA bioplastics Manufacturing exhibits CO2 intensity, Cost of manufacturing, and Water intensity.
• Reactor & Purification Equipment exhibits Reactor & Purification Equipment Capital Cost.
• Engineered Organisms exhibits Engineered Organisms Cost.
• Energy exhibits Energy Cost.
• Substrate exhibits Substrate Cost.
• Water exhibits Water Cost.
• Biodegradability, CO2 intensity, Cost of manufacturing, Elongation At Break, Melting Point, Price per unit weight, Tensile Strength, Water intensity, and Young's Modulus are Figures Of Merit.
• Kaneka Corporation, PHB Industrial S.A., SIRIM Bioplastics, Shenzhen Ecomann Biotechnology Co. Ltd, TianAn Biologic Materials Co. Ltd, and Tianjin GreenBio Material Co. are Bioplastics Manufacturing Process Operator.
• PHA bioplastics Manufacturing is physical and systemic.
• Bioplastics Manufacturing Process Operator handles PHA bioplastics Manufacturing.
• PHA bioplastics Manufacturing requires Engineered Organisms and
• Reactor & Purification Equipment.
• PHA bioplastics Manufacturing consumes Air, Energy, Substrate, and Water.
• PHA bioplastics Manufacturing yields CO2, Purified PHA bioplastics, and Waste.
• Designing / Engineering is physical and systemic.
• Bioplastics Process Designer handles Designing / Engineering.
• Designing / Engineering requires Bioplastics Engineering.
• Designing / Engineering consumes Energy.
• Designing / Engineering yields Engineered Organisms and Reactor & Purification Equipment.

We also provide a OPD of a more detailed view of the 2MPH technology, including the high level process steps that make up PHA bioplastics manufacturing.

Zoomed-in version of the PHA bioplastics manufacturing process.

An Object-Process-Language (OPL) description of this OPD is auto-generated and given below. It reflects the same content as the previous figure, but in a formal natural language.

• PHA bioplastics Manufacturing from SD zooms in SD1 into Sterilization, PHA precipitation, parallel Growing organisms and Drying and powdering, and parallel Fermentation and Cell Precipitation, as well as Electricity, Natural Gas, and Water.
• Engineered Organisms is physical and systemic.
• Engineered Organisms can be high amount or low amount.
• Substrate is physical and environmental.
• Bioplastics Manufacturing Process Operator is physical and environmental.
• Reactor & Purification Equipment is physical and systemic.
• Air is physical and environmental.
• Purified PHA bioplastics is physical and systemic.
• CO2 is physical and systemic.
• Waste is physical and systemic.
• Seed Engineered Organisms is physical and systemic.
• Nutrients is physical and systemic.
• Unrefined biomass is physical and systemic.
• Steam is physical and environmental.
• Wet PHA is physical and systemic.
• Unpurified PHA is physical and systemic.
• Electricity is physical and environmental.
• Natural Gas is physical and environmental.
• Water is physical and environmental.
• PHA bioplastics Manufacturing is physical and systemic.
• Bioplastics Manufacturing Process Operator handles PHA bioplastics Manufacturing.
• PHA bioplastics Manufacturing requires Reactor & Purification Equipment.
• PHA bioplastics Manufacturing yields CO2 and Waste.
• Growing organisms is physical and systemic.
• Growing organisms changes Engineered Organisms from low amount to high amount.
• Growing organisms requires Seed Engineered Organisms.
• Growing organisms consumes Air, Electricity, Nutrients, and Water.
• Growing organisms invokes Fermentation.
• Fermentation is physical and systemic.
• Fermentation requires Engineered Organisms at state high amount.
• Fermentation consumes Electricity and Substrate.
• Fermentation yields Unrefined biomass.
• Fermentation invokes Cell Precipitation.
• Cell Precipitation is physical and systemic.
• Cell Precipitation consumes Electricity and Unrefined biomass.
• Cell Precipitation yields Wet PHA.
• Cell Precipitation invokes Drying and powdering.
• Drying and powdering is physical and systemic.
• Drying and powdering consumes Electricity, Natural Gas, Water, and Wet PHA.
• Drying and powdering yields Unpurified PHA.
• Drying and powdering invokes PHA precipitation.
• Sterilization is physical and systemic.
• Sterilization consumes Steam.
• Sterilization invokes Growing organisms.
• PHA precipitation is physical and systemic.
• PHA precipitation consumes Electricity and Unpurified PHA.
• PHA precipitation yields Purified PHA bioplastics.
• PHA precipitation invokes Sterilization.

Figures of Merit

The table below show a list of different FOMs by which PHAs and the PHA manufacturing process can be assessed.

Grouping	Figure of Merit (FOM)	Calculation Method	Reference value for the family of PHA polymers
Cost	Cost of manufacturing [$/kg of PHA bioplastics yielded]	For a given quantity (kg) of PHA bioplastics produced, the total cost of all variable inputs required (feedstock biomass, energy, labor and utilities) to produce that quantity divided by the quantity of PHA bioplastics produced.	$5-6/kg PHA (2017, versus $1.3 to $1.9/kg for oil-based plastics)
Sustainability	Biodegradability (%)	Measure the CO2 evolved by a given quantity of PHA bioplastics and compare it to the amount of CO2 evolved by the same amounts of starch and PE (polyethylene) respectively.	68.3% for P(3HB) (2012)
Sustainability	CO2 intensity [kg CO2/kg PHA yielded]	For a given quantity (kg) of PHA produced, the total CO2 emitted during manufacturing to produce that quantity divided by the quantity of PHA produced.	1.96 kg CO2/kg PHA (2009)
Sustainability	Water intensity [kg water/kg PHA]	For a given quantity (kg) of PHA produced, the total amount of water (kg) consumed divided by the quantity of PHA produced.	150 kg H2O/kg PHA (2009)
Performance	Tensile strength [MPa]	Tensile strength of the PHA manufactured	0 - 45 MPa (2018)
Performance	Young’s modulus (GPa)	Young’s modulus of the PHA manufactured	0 - 3.5 GPa (2018)
Performance	Minimum and maximum operating temperature (degC)	Minimum and maximum operating temperature of the PHA manufactured	40 - 110 degC (2018)
Performance	Elongation at break (%)	Elongation at break of the PHA manufactured as a % of the original length of the PHA	0 - 1000% (2018)

Our research has revealed that the PHA manufacturing process itself does not affect the sustainability and performance FOMs listed above. Rather, these are properties inherent to the type of PHA formed. The family of PHA polymers is large, and each of the members have their own mechanical properties, just like the family of oil-based plastics (HDPE vs LLDPE, etc.). Therefore, the cost of manufacturing, which IS affected by the choices made when designing the PHA manufacturing process, will be the focus of this roadmap and analysis.

This first chart shows how one of the most important FOMs, the cost to manufacture PHA as reported in literature, has varied over the past 30+ years.

This graph zooms into the last 20 years of reported PHA price and compares it to the cost of PP, an oil-based plastic. The current goal is to get the cost of PHA to at or below the cost of the oil-based plastics (like PP, or polypropylene).

Alignment with Company Strategic Drivers

Number	Strategic Driver	Alignment and Targets
1	To develop a process to manufacture PHAs with desirable properties at a price point competitive with existing oil-based plastics.	This roadmap will target the design of a manufacturing process that will bring the cost per KG of P(3HB) to under $2.5/kg, which is 50% lower than the current achievable cost to produce P(3HB). This driver is currently aligned with the PHA bioplastics manufacturing technology roadmap.
2	To develop a process to manufacture PHAs that are designed to be recovered via composting (to ensure the carbon stays fixed and doesn't go into the atmosphere as CO2)	The technology roadmap will target optimizing the physical and biodegradability properties of PHAs to ensure they can be sorted and recovered at end-of-life. This driver is not currently aligned with the PHA bioplastics manufacturing technology roadmap as it is considered out of scope at this time.

The list of drivers shows that our company views PHA bioplastics as a promising industry with a lot of potential. Therefore, our company wants to develop the PHA bioplastics manufacturing process such that it yields bioplastics that are competitive with oil-based plastics on the basis of both material properties and cost. In order to do so, our technology roadmap introduces a technical model and some analysis using a governing equation for the cost of bioplastics manufacturing. The FOM target for the production cost of P(3HB), the PHA variant of interest since it is a direct competitor with PP (polypropylene), is at or below $2.5/kg in order to reach near-parity with the current market price of PP resin. This roadmap is aligned with this driver. This means that the analysis, technology targets, and R&D projects contained in our roadmap (and hopefully funded by the R&D budget) support the strategic ambition stated by driver 1.

However, the second driver, focused on managing end-of-life PHA bioplastics to ensure the carbon stays fixed, is out of scope and not currently aligned with this roadmap.

Positioning of Company vs. Competition

Strain	PHA produced	Fermentation strategy	Substrate	PHA content (%)	Productivity (g L-1 hr-1	Production cost ($/kg)
A. latus	P(3HB)	Fed-batch	Sucrose	50	3.97	8.3
A. latus	P(3HB)	Fed-batch	Sucrose	88	4.94	2.6
E. coli	P(3HB)	Fed-batch	Glucose + YE + CSL + casein hydrolysate	72.3	1.98	5.37
E. coli	P(3HB)	Fed-batch	Glucose	77	3.2	4.91
R. eutropha	P(3HB)	no data	Glucose	73.8	2.42	unavailable (commercial data)
P. cepacia	P(3HB)	no data	Xylose	60	no data	unavailable (commercial data)
A. vinelandii	P(3HB)	no data	Molasses	60	1.4	unavailable (commercial data)
Various micro-organisms	P(3HB)	no data	Lignocellulose hydrolysates	32-89	0.3-105	unavailable (commercial data)
E. coli harboring A. latus genes	P(3HB)	no data	Whey	80.2	2.57	unavailable (commercial data)
R. eutropha	P(3HB)	no data	Plant oils	62.5	0.96	unavailable (commercial data)
R. eutropha	P(3HB)	no data	Waste frying oil	36.5	0.14	unavailable (commercial data)
P. cepacia	P(3HB)	no data	Glycerol	31.4	0.6-1.5	unavailable (commercial data)
M. organophilum	P(3HB)	no data	Methanol	52	1.8-2.0	unavailable (commercial data)
P. oleovorans	P(3HB)	no data	n-Octane	32.6	0.25	unavailable (commercial data)
P. putida	P(3HB)	no data	Polystyrene oil	25.0	0.015	unavailable (commercial data)
Methylotroph spp.	P(3HB)	no data	Methane	51.0	0.031	unavailable (commercial data)

Source:

• Choi, J., Lee, S. Factors affecting the economics of polyhydroxyalkanoate production by bacterial fermentation. Appl Microbiol Biotechnol 51, 13–21 (1999). https://doi.org/10.1007/s002530051357
• Jiang, G., Hill, D. J., Kowalczuk, M., Johnston, B., Adamus, G., Irorere, V., & Radecka, I. (2016). Carbon Sources for Polyhydroxyalkanoates and an Integrated Biorefinery. International journal of molecular sciences, 17(7), 1157. https://doi.org/10.3390/ijms17071157

Competitor production cost data is typically confidential, so the data we have available is derived from research papers. The latter part of the data without prices comes from companies, even some large-scale fermenters that were not named in the paper. Although the price data isn't present, our hope is that we can build a technical model that can compare all of the above on an equal basis (assuming a constant price for glucose rather than worrying about regional or local prices, etc.).

In the section of the prices that ARE available, we begin to see some of the factors and choices that influence the price. For example, how does the choice of feedstock affect the price? The strain of bacteria? The PHA content? etc. We see that one A. latus process near the top is able to achieve near our goal of $2.5/kg P(3HB) or less. Why is this?

Technical Model

Our roadmap's primary focus is the production cost of PHA bioplastics. However, there are many variables and choices to take, so we need a technical model and some simplifying assumptions to explore the design tradespace.

As such, we need first need a governing equation for the production cost of PHA bioplastics that relates the production cost to commonly reported variables: Where:

• k_s,c, in units of $/kg carbon substrate is the cost of the carbon substrate. Since PHA is only composed of C, H, and O items, the carbon substrate is the most significant.
• Y_p/c^(theor), in units of kg PHA/kg carbon substrate, is the theoretical yield of PHA on the carbon substrate. The theoretical yield typically references the biochemical theoretical yield, which is typically lower than the purely chemical theoretical yield because it accounts for the biological reactions occurring in the production pathway.
• C_p is the PHA content (% of dry cell weight).
• Y_x/c in units of kg x/kg carbon substrate, is the yield of organism x (x can be whatever organism) on the carbon substrate. The organism is a living creature so it will consume some of the carbon substrate for its own sustenance and growth.
• k_t in units of $/hr represents the running costs, which typically include utilities such as steam, air, fuel, etc.
• Φ, in units of kg PHA-L^-1-hr^-1 is the volumetric productivity of PHA. Note that it is on a time basis.
• V_b, in units of L, is the volume of the fermenter.

This equation was adapted from Yamane T. Cultivation engineering of microbial bioplastics production, FEMS Microbiology Reviews, Volume 9, Issue 2-4, December 1992, Pages 257–264, https://doi.org/10.1111/j.1574-6968.1992.tb05846.x

Comparing the list of variables here to the table given in the "Positioning of Company vs Competition", we see that many of the variables in this equation are explicitly stated, such as volumetric productivity and PHA content. The other variables can be determined given the information provided - for example, given the name of the substrate, one can find an expected cost, and given the substrate, organism, and product, one can determine the biological pathway that will determine the theoretical yield (kg PHA/kg carbon substrate).

This process will allow us to determine which parameters to focus on to yield a total production cost of PHA bioplastics of <=$2.5/kg.

First, just by exploring the equation above, we can determine normalized sensitivities to four of the most prominent variables. The design vector used to generate this chart was as follows:

• Strain Alcaligenes latus or “x”
• PHA formed P(3HB)
• Substrate sucrose, with a cost of $0.290/kg
• PHA content of resulting cells is 50%, or 0.50
• Productivity 3.97 g L-1 hr-1 = 0.00397 kg L-1 hr-1
• Assume theoretical yield 0.5 kg P(3HB)/kg sucrose, assume Y_(x/c) is 0.5 kg x/kg sucrose
• Assume running costs and fermenter volume are fixed at $0.49/hr and 100 L respectively. For the purposes of comparison, we will assume the running costs and fermenter volumes are constant across the different possibilities.
• At 100,000 tonnes/year production capacity, Choi 1999 simulated a production cost of $8.3/kg P(3HB) for this particular design vector.

Normalized sensitivities of PHA cost to a 1% increase for 4 factors in a tornado chart

Here are two examples of how to read the above:

• For a 1% positive change in the substrate cost, the cost of production increases by $0.142/kg (P3HB).
• For a 1% positive change in the theoretical PHA yield on carbon substrate, the cost of production reduces by $0.244/kg (P3HB).

These normalized sensitivities help us determine what to focus on as we map out a roadmap to achieving cost-competitive PHA bioplastics.

In fact, we can even build a sample morphological matrix. Please note that the options in this morphological matrix are NOT exhaustive of all of the possibilities. The options are there only to give the reader an idea of what goes in each category.

Morphological matrix for a PHA manufacturing process

AD1, the choice of organism, impacts:

• PHA cell content
• PHA productivity
• theoretical yield of PHA on the carbon substrate

AD2, the choice of substrate, impacts:

• cost of the carbon substrate
• theoretical yield of PHA on the carbon substrate

AD3, the choice of PHA product, impacts:

• PHA cell content
• PHA productivity
• theoretical yield of PHA on the carbon substrate
• {biodegradability of the PHA and all of the mechanical properties (elasticity, Young’s modulus, etc.)}

AD4, fermentation strategy, impacts:

• PHA cell content
• PHA productivity

Key Publications, Presentations and Patents

Key publications: Our first stop was [Choi, J., Lee, S. Factors affecting the economics of polyhydroxyalkanoate production by bacterial fermentation. Appl Microbiol Biotechnol 51, 13–21 (1999). https://doi.org/10.1007/s002530051357]. This paper covers a lot of ground directly relevant to our work:

• Introduction to the factors that affect PHA production's overall economics: PHA productivity, PHA content, the yield of PHA on a carbon source, the price of raw materials, and the recovery method employed.
• Tables correlating different design choices (such as bacterial strain, PHA type produced, fermentation strategy, and substrate) with the factors listed above and the overall cost of production ($/kg).
• A textual and graphical description(using 3D charts) of the sensitivity analysis of the factors listed above to the ultimate PHA type production cost.

This paper is an excellent introduction to our subject. However, although there is a lot of quantitative data, much of the discussion revolves around qualitative descriptions (such as "the carbon source cost contributes significantly to the overall production cost of PHA" without a numerical value to the significance.

Most importantly, this paper points out that the largest determinants of PHA production costs are mainly associated with the fermentation step, with only one factor related to downstream processing costs (recovery method employed). This tells us to focus on upstream processing (fermentation) costs.

Our search for a quantitative model to evaluate sensitivities led us to [Yamane T.Cultivation engineering of microbial bioplastics production, FEMS Microbiology Reviews, Volume 9, Issue 2-4, December 1992, Pages 257–264, https://doi.org/10.1111/j.1574-6968.1992.tb05846.x]. This paper covers:

• A formula for the cost of PHA production as a function of the most common reported values mentioned in the paper above. This formula was a critical find and is covered in depth in the technical model section of our roadmap.
• Quantitative definitions and key simplifying assumptions for each of the terms in the formula.

This paper introduces a formula for the overall yield of PHB compared to the theoretical yield of PHB that wasn't fully derived. Therefore, we consulted the author's previous work, [Yamane T. Yield of poly-D(-)-3-hydroxybutyrate from various carbon sources: a theoretical study. Biotechnol Bioeng. 1993 Jan 5;41(1):165-70. doi: 10.1002/bit.260410122.], which provided a detailed definition of the formula introduced in the previous paper.

Key patents:

• Liu et al. (2020). US Patent No. 10,807,893 B2. Sacramento, CA: US Patent and Trademark Office. This patent was issued on October 20, 2020). It details a method for producing PHAs during wastewater treatment. The most important takeaway from this process is the claim that PHA can be produced using an activated sludge process with a higher PHA content (>10% cell weight basis) than conventional technologies (2.5% cell weight basis). As we learned from the previous papers, PHA content is an important factor for economical PHA production. However, it is difficult to achieve high PHA content with a cheap carbon source. Typically, one must use expensive carbon sources to achieve high PHA content, which negatively impacts PHA production costs. This patent is interesting because it claims a breakthrough in using a cheap source of feed (wastewater, a liability) to achieve a higher PHA content than before, suggesting that there may not be such a tradeoff between carbon source cost and PHA content.
• Tsai et al. (2020). US Patent No. 10,745,723 B2. Nantou County (TW): US Patent and Trademark Office. This patent was issued on August 18, 2020. It is similar in scope and tone to the Liu et al. patent above, which may indicate where the attention in this field is currently (PHAs from activated sludge, boosting PHA content). It details a method of increasing the PHA content of waste sludge using a specific sequence of processing steps. Just like the previous patent, the aim is to reduce the cost of PHA production. This patent again illustrates the importance of PHA content. However, unlike the Liu et al. patent above, this one does not make any claims for how much this different process can raise the waste sludge's PHA content versus a control.
• Nomura et al. (2020). US Patent No. 10,745,722 B2. Syracuse, NY: US Patent and Trademark Office. This patent was also issued on August 18, 2020, with the support of the NSF. It details a specifically engineered strain of Escherichia Coli that can be controlled to produce different poly-R-3-hydroxyalkanoate polymers. Control is important because it allows the manufacturer to "dial-in" the material properties desired from the PHA produced. Here we see how important the organisms used to produce PHA are and how they can be customized. These organisms catalyze PHA production and are much more complex compared to analogous inorganic catalysts. Poly-3-hydroxybutyrate (P3HB) is in the family of PHAs and is perhaps the most exciting of the different PHA variants because it can be a direct competitor to polypropylene, one of the major oil-derived plastics in use today. (A head-to-head comparison is detailed on our roadmap). This invention proposes an engineered E. coli that can deliver a higher yield of P3HB range biopolymers with the right composition. As detailed in the key papers, the yield is an important factor of PHA (or P3HB) production cost, and this is important for our roadmap.

Financial Model

The figure below describes a financial model for a project to manufacture PHA at a commercial scale. There are a few key elements depicted here:

1. R&D costs - This entails the cost of engineering an organism that will produce the variant of PHA desired and engineering the process around that organism that will produce the desired PHA at the cost desired. The R&D costs are fairly small at about $400k/year, based on discussions with startups in the PHA bioplastics space.
2. Revenue - This is the projected revenue from selling PHA on the market. The revenue is a function of not only the price per kg of PHA but also the amount (kg) of PHA produced. As shown in the graphic below the financial model, the higher the premium charged to consumers for a green product like PHA bioplastics, which can be used for packaging and are biodegradable, the lower the share of consumers willing to pay for it. So if we're to access more consumers, the price we're charging for PHA needs to drop.
3. Production costs - This is the projected cost to manufacture PHA. Just like revenue, it's a function of not only the price per kg of PHA but also the amount (kg) of PHA produced. We model the price to produce each kg of PHA as reducing gradually over time as a result of R&D activities (engineering more efficient organisms and tweaking the manufacturing process to be more efficient)
4. CAPEX - This is the cost of the manufacturing facilities. We build a new facility only when the previous year's demand has exceeded the current facility's capacity, which is why the CAPEX cost comes in infrequently. It's quite a large cost - according to industry benchmarks, approximately $3,200/ton of PHA production capacity. Therefore, a 50 kiloton/year facility would cost $160 million. With this order of magnitude of CAPEX, it becomes vitally important to maximize the margin between the price each kg of PHA is sold for and the cost to manufacture each kg of PHA.
5. Misc - This was just modelled as overhead, a fixed percentage of production costs.

Financial analysis for manufacturing PHA at a commercial scale

We've estimated a NPV of approximately $12 million over 20 years, but there are several areas of interest.

Major points of interest

• We assumed that PHA would replace polypropylene (referenced earlier in the roadmap) over time. PP is a massive market - over 17 million tons are produced in the US and Canada each year. We'll be able to capture more and more of that market the closer we get to PP's price (currently about $1.2/kg PP).
• Just meeting PP spot price at parity isn't enough to recoup the large capital investment required to build the plants needed to produce PHA at a commercial scale! It's clear that we not only need to meet PP spot price but also go below it in order to turn a profit and counter the heavy capital costs (~$3,200/ton PHA) required to build a large plant.
• The only way to meet and beat PP spot price is to already start off with a highly cost-competitive PHA manufacturing process - assuming we start off selling PHA for $3/kg, we need to already be at a PHA cost to manufacture of $1.5/kg (for a margin of at least $1.5/kg) when the first factory is built! The goal is to take advantage of the high prices that a small share of consumers are willing to pay for green products to sell to those consumers at a high margin (profit) to us so we can recoup the large CAPEX expenditures required to expand our production capacity.
• We've assumed a discount rate of 20%, to reflect the risky nature of this business (disrupting oil-based plastics).

IdTechEx/McKinsey study on how much more consumers might pay for green products

This image depicts the relationship between the share of consumers willing to purchase a green product and the premium charged for that green product over an equivalent non-green product. We're using this general relationship (packaging is the closest analogy) to depict how we can access more consumers and a bigger share of the plastics market if we can sell PHAs (profitably) at a lower price.

List of R&T Projects

There are clearly many challenges ahead to producing PHAs at a commercial scale in an economically feasible manner, but as a startup company, we do not have a large team/large amount of resources to tackle multiple large opportunities at once.

We propose broad groupings to the R&T opportunities as follows:

• Making PHAs cheaper to produce (reducing the cost $/kg) - This is fairly straightforward, given the previous content.
• Building a market for PHAs - We know that the capital cost for PHA plants is high, and we also know that PHAs are a commodity, which means the margin between the price they are sold at and the cost of manufacturing them won't be very large. Therefore, the only way to make enough money to outweigh the high capital cost of PHA plants at low margins is to increase the scale at which we can manufacture PHAs - the more markets we can get into, the more consumers we can sell to!

A few R&T projects worth considering are shown in the Wheelwright and Clark model below. They are explained in the table below the graphic.

File:2MPH R&T projects.JPG

Wheelwright and Clark categorization of R&T projects for a small (startup) PHA bioplastics company

In order to select and prioritize R&D (R&T) projects we recommend using the technical and financial models developed as part of the roadmap to rank-order projects based on an objective set of criteria and analysis. The figure below illustrates how technical models are used to make technology project selections, e.g based on the previously stated 2030 target performance and Figure 8-17 (see the Chapter 8 of the text) shows the outcome if none of the three potential projects are selected.

A roadmap shows the R&T/R&D projects and demonstrators that have been (completed), are being (active) and could be (proposed) undertaken in order to progress the technology at the component or system level towards the set targets/goal set by the higher or lower-level roadmap. Please add what is essentially a Gantt Chart with milestones.

Technology Strategy Statement

A technology roadmap should conclude and be summarized by both a written statement that summarizes the technology strategy coming out of the roadmap as well as a graphic that shows the key R&D investments, targets and a vision for this technology (and associated product or service) over time. For the 2SEA roadmap the statement could read as follows and is displayed in an Arrow Chart:

Our target is to develop a new solar-powered and electrically-driven UAV as a HAPS service platform with an Entry-into-Service date of 2030. To achieve the target of an endurance of 500 days and useful payload of 10 kg we will invest in two R&D projects. The first is a flight demonstrator with a first flight by 2027 to demonstrate a full-year aloft (365 days) at an equatorial latitude with a payload of 10 kg. The second project is an accelerated development of Li-S batteries with our partner XYZ with a target lifetime performance of 500 charge-discharge cycles by 2027. This is an enabling technology to reach our 2030 technical and business targets.