Techno-Economic Analysis
What Does It Take to Scale?
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A technology can work exceptionally well in a laboratory and still fail to become a commercially viable product. Techno-economic analysis (TEA) is a tool used to determine whether a technology can make the transition from research to commercial deployment. TEA combines engineering, economic, and financial information to estimate how much a technology would cost to build and operate, how much revenue or value it could generate, and whether it can compete with existing alternatives [1].
Figure 1: Colorful depiction of the key steps of techno-economic analysis [1]
TEA is particularly important during scale-up because the economics of a technology can change dramatically as production increases. Laboratory experiments often use expensive materials, specialized equipment, and small quantities of chemicals. These conditions may be reasonable for demonstrating that a technology works, but they do not necessarily represent the economics of operating a large industrial facility. TEA allows researchers to model those larger-scale conditions and identify potential economic barriers before investing in expensive pilot or commercial facilities [1][2][3].
Estimating Costs
A TEA begins by defining the proposed process and its material and energy flows. Researchers estimate how much feedstock, electricity, water, catalysts, solvents, and other inputs are required to produce a certain quantity of the final product. They then estimate the equipment needed to operate the process, including reactors, separation systems, pumps, heat exchangers, storage tanks, and other infrastructure.
These expenses are generally divided into two major categories: capital expenditure (CAPEX) and operating expenditure (OPEX). CAPEX represents the upfront cost of constructing a facility, including equipment, buildings, installation, and other infrastructure. OPEX represents the ongoing costs of running the facility, such as electricity, raw materials, labor, maintenance, waste treatment, and utilities [4][5][6].
By combining these costs with the expected production rate, researchers can estimate metrics such as the cost of production. For example, a company developing a new hydrogen-production process could calculate the cost of producing one kilogram of hydrogen at different plant sizes and compare it with conventional hydrogen-production technologies [4][5].
Finding Economic Bottlenecks
One of the most useful functions of TEA is identifying which parts of a process contribute most to its cost. A technology may appear inexpensive overall while one particular component creates a major economic barrier.
For example, in carbon capture, electricity or heat requirements can represent a significant portion of operating costs [7]. In battery recycling, transportation, chemical consumption, or waste treatment could become major expenses [8]. Identifying these bottlenecks allows researchers to direct development toward the changes that could have the greatest economic impact.
This can also change how researchers approach technical optimization. Improving a material's performance is not necessarily valuable if that improvement has little effect on the overall cost. TEA helps connect individual engineering decisions to their broader economic consequences [7][8].
Lithium-Ion Battery Recycling
Lithium-ion battery recycling demonstrates how techno-economic analysis can reveal the economic bottlenecks that determine whether a process can succeed commercially.
In a 2024 study, “A techno-economic assessment of two recycling processes for black mass from end-of-life lithium-ion batteries,” published in Applied Energy, researchers from RWTH Aachen University compared the economics of pyrometallurgical and hydrometallurgical recycling processes for the black mass produced from end-of-life lithium-ion batteries. The pyrometallurgical process is traditional heat-based recycling while the hydrometallurgic process uses a chemical-based recycling method.
The analysis found that material and energy prices were among the most important factors affecting profitability, while the changing composition of battery chemistries also significantly influenced the value of recovered materials. The researchers also found that the hydrometallurgical process was more robust under changing economic conditions, while both processes could become more profitable as the amount of material processed increased [9].
This illustrates how TEA can identify specific economic bottlenecks—in this case, input costs, energy consumption, recovered-material prices, and battery chemistry [9].
Figure 2: Flow charts of a pyrometallurgical process, traditional heat-based recycling, (left) compared to a hydrometallurgic one, chemical-based recycling method, that extracts lithium first (right) [9]
Scaling Up Economically
The economics of a technology often change as its production capacity increases. Larger facilities can benefit from economies of scale, in which equipment and infrastructure costs increase more slowly than production capacity. For example, doubling the size of a facility does not necessarily require doubling every construction expense [10].
However, larger systems can also introduce new costs and engineering challenges. Equipment may become more complex, transportation distances may increase, and maintaining consistent operating conditions can become more difficult. A process that is inexpensive at laboratory scale may therefore encounter unexpected costs when expanded to thousands or millions of units of production [10][11].
See Manufacturing at Scale article under Scale-Up Overviews for further information
TEA allows researchers to model these changes and determine whether increasing the scale of a facility actually improves its economics.
Hydrogen Electrolyzers
Hydrogen electrolyzers provide a clear example of how scale can change the economics of an emerging technology. Electrolyzers require expensive components and supporting equipment, including compressors, gas storage, transformers, and other balance-of-plant systems.
Figure 3: Diagram of a general flow cell that produces hydrogen gas [13]
Research on large alkaline electrolyzer installations by the DOE's H2NEW program found that scaling these components could reduce capital costs by roughly 25–60%, depending on the system design. However, simply making an electrolyzer larger does not automatically produce these savings because many modern systems are built from modular, prepackaged units. DOE's H2NEW program therefore evaluates not only electrolyzer performance but also manufacturing methods, catalyst loading, balance-of-plant design, electricity costs, and system utilization [11][12].
Sensitivity and Uncertainty
Emerging technologies often lack reliable data about future equipment costs, material prices, catalyst lifetimes, degradation, maintenance, and large-scale performance. Instead of treating uncertain values as fixed numbers, TEAs can use sensitivity analysis to determine how strongly different assumptions affect the final result [14][15].
For example, a model might calculate how the cost of a technology changes under different electricity prices, production rates, equipment costs, catalyst lifetimes, or raw-material prices. If a small change in one variable dramatically changes the cost of the final product, that variable represents an important economic uncertainty [14].
This information can help researchers prioritize future experiments. Rather than collecting data on every possible parameter equally, they can focus on the variables that have the greatest influence on commercial viability.
“Because of the amount of assumptions used and the variability of certain costs over time , TEA can’t precisely tell us how much a technology will cost at scale and how that cost will change with deployment but it can provide us with valuable insights on the expected ranges of these values” [6].
Uncertainty in Carbon Capture Costs
Carbon capture demonstrates why techno-economic analyses must account for uncertainty in their underlying data. A 2017 study, “Unravelling uncertainty and variability in early stage techno-economic assessments of carbon capture technologies,” in the International Journal of Greenhouse Gas Control compared techno-economic assessments of the same post-combustion carbon-capture technology using advanced amine solvents.
Even after van der Spek et al. attempted to standardize the assumptions between studies, estimated equipment costs differed by 66% and total capital costs differed by 65%. The researchers identified differences in equipment sizing and equipment-cost estimates as major sources of variation. Sensitivity analysis also showed that the efficiency penalty caused by capturing and compressing CO₂ was one of the most important factors affecting the cost of electricity.
These results demonstrate why TEA cannot simply produce one fixed cost estimate: uncertain inputs can substantially change the predicted economics of a technology. By identifying which variables have the greatest influence on the final result, researchers can focus future experiments and engineering improvements on collecting better data and reducing the most important uncertainties.
Connecting Economics and Environmental Impact
TEA can also be combined with life-cycle assessment (LCA) to evaluate both the economic and environmental performance of a technology. While TEA focuses primarily on costs and financial viability, LCA examines environmental impacts across a technology's life cycle, including raw-material extraction, manufacturing, operation, transportation, and disposal [16][17].
Using both approaches can reveal tradeoffs that would otherwise be overlooked. A process could be cheaper than an existing technology but require substantially more energy or raw materials. Conversely, a technology could provide major environmental benefits while remaining too expensive for widespread adoption. Combining TEA and LCA helps researchers search for solutions that are both economically and environmentally sustainable [16].
Why TEA Matters
The quality of a TEA ultimately depends on the quality of its assumptions. Early-stage technologies often have limited information about how they will perform over years of continuous operation. Researchers may therefore rely on laboratory measurements, engineering models, comparable industrial processes, and projected improvements.
As a technology progresses from laboratory research to pilot plants and eventually commercial facilities, these assumptions can be replaced with increasingly reliable data. A TEA performed early in development can therefore be updated repeatedly as new information becomes available.
TEA provides a roadmap for what must improve for a technology to become commercially viable. By connecting technical performance with economic consequences, TEA helps researchers identify the most important barriers before large amounts of capital are invested. A laboratory breakthrough becomes much more meaningful when its developers understand not only whether it works, but whether it can eventually work at a cost that the real world can support.
References
Sustainability Science | TEA. (2016). In Sus Science. https://www.sustainabilitysci.com/technoeconomicanalysis
Qureshi, T.I. Understanding the scaling up of future innovations with techno-economic analysis. Nat. Rev. Clean Technol. 1, 232 (2025). https://doi.org/10.1038/s44359-025-00046-0
Technoeconomic Analysis of Chemical and Electrochemical Technologies. (2023). In Argonne National Laboratory. https://www.anl.gov/cse/electrochemical-chemical-TEA
Ranjitha Ranganath. (2024). Capital vs Operating Costs: Key Differences Explained. In Efficient CapEx Procurement for Faster Project Deliveries | ProQsmart. https://proqsmart.com/blog/capital-vs-operating-costs/
Ross, S. (2021). What Smart Business Owners Should Know About CAPEX and OPEX. In Investopedia. https://www.investopedia.com/ask/answers/112814/whats-difference-between-capital-expenditures-capex-and-operational-expenditures-opex.asp
Techno-Economic Assessment. (2021). Upenn.Edu. https://ceclab.seas.upenn.edu/page/tea?utm_source=chatgpt.com
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Das, P., Hewage, K., Kotagodahetti, R., Wanniarachchi, T., & Sadiq, R. (2026). Lithium-ion battery recycling: a critical review of techno-economical and socio-environmental impacts. Separation and Purification Technology, 135847. https://doi.org/10.1016/j.seppur.2025.135847
Woeste, R., Drude, E.-S., Dzeneta Vrucak, Klöckner, K., Rombach, E., Letmathe, P., & Friedrich, B. (2024). A techno-economic assessment of two recycling processes for black mass from end-of-life lithium-ion batteries. Applied Energy, 361, 122921–122921. https://doi.org/10.1016/j.apenergy.2024.122921
Morgan, E. R., Manwell, J. F., & McGowan, J. G. (2013). Opportunities for economies of scale with alkaline electrolyzers. International Journal of Hydrogen Energy, 38(36), 15903–15909. https://doi.org/10.1016/j.ijhydene.2013.08.116
Research | Hydrogen from Next-generation Electrolyzers of Water (H2NEW). (2026). Energy.Gov. https://h2new.energy.gov/research#lte
Home | Hydrogen from Next-generation Electrolyzers of Water (H2NEW). (2026). Energy.Gov. https://h2new.energy.gov/
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Strunge, T., Renforth, P., & Van der Spek, M. (2023). Uncertainty quantification in the techno-economic analysis of emission reduction technologies: a tutorial case study on CO2 mineralization. Frontiers in Energy Research, 11. https://doi.org/10.3389/fenrg.2023.1182969
van der Spek, M., Sanchez Fernandez, E., Eldrup, N. H., Skagestad, R., Ramirez, A., & Faaij, A. (2017). Unravelling uncertainty and variability in early stage techno-economic assessments of carbon capture technologies. International Journal of Greenhouse Gas Control, 56, 221–236. https://doi.org/10.1016/j.ijggc.2016.11.021
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