Scientists should be familiar with the financial language of industry in order to discover entry points for better and cleaner technologies. We are thrilled to announce an open-source techno-economic analysis (TEA) resource<\/strong> specifically built around copper extraction from chalcopyrite heap leaches, and developed in collaboration with the team at Conductor Labs<\/a>. As part of our Orecast project – intended to help biomining innovators determine if their technologies have a viable path to market – this Excel-based tool is designed to put scientists in the \u201cCommand Center\u201d of a mine: illustrating how value is created, and showing what biology can do to move the needle on costs and revenues.<\/p>\n\n\n\n
In this post, we\u2019ll highlight:<\/strong><\/p>\n\n\n\n <\/p>\n\n\n\n If you\u2019d like to skip all the talk and go directly to the model, we welcome you to do so. Please find the relevant resources below:<\/strong><\/p>\n\n\n\n Copper is a cornerstone metal for modern electronics, energy infrastructure, and construction. Demand for this metal is projected to increase by 70% by 2050<\/a>. However, conventional copper extraction can be energy-intensive and environmentally challenging. The process of biomining – using microbes to assist with metal recovery – shows promise, but scientists often struggle to demonstrate economic feasibility to industrial stakeholders.<\/p>\n\n\n\n Chalcopyrite (a copper-iron sulfide) is a copper ore that makes up about 70% of the world\u2019s copper reserves<\/a> and already sees some bio-based industrial extraction. Extraction of copper from chalcopyrite poses challenges like \u201cpassivation,\u201d where mineral surfaces become less reactive over time, reducing overall recovery. By focusing on chalcopyrite, we\u2019re looking at a widely relevant case where biology is already part of the conversation – and where there\u2019s plenty of room for further innovation.<\/p>\n\n\n\n Our Excel spreadsheet acts like a digital twin<\/a> for a copper heap-leaching operation. Think of it as the cockpit that shows you all the dials and knobs controlling production. With this model, you can experiment with how scientific breakthroughs translate into the metrics a mine manager or investor cares about, and ultimately drive your own decisions around R&D and commercialization. Think of the model as an illustrative reference of what types of data, decision-making, and analysis is involved when navigating the path to commercial deployment for an early-stage technology.<\/p>\n\n\n\n A key starting point in developing a new technology is understanding where it fits within an existing process flow. Thus, this model starts with a Process Flow Diagram.<\/p>\n\n\n\n In this process, we\u2019ve mapped:<\/p>\n\n\n\n The spreadsheet visually mirrors this flow so you can see how changing one step (e.g., different acid concentration) ripples through the rest. We\u2019ve made the model highly customizable and agnostic to the specific biotechnology, so that researchers working in a variety of systems or with differing technologies can utilize this model as a starting point.<\/p>\n\n\n\n We see a lot of numbers in this financial model, but which ones are the most important? Sensitivity analysis is a way in which we can see which variables have the biggest impact, such as decreasing an input cost or increasing an output price.<\/p>\n\n\n\n The spreadsheet includes a Tornado Chart, which ranks variables by their impact on costs or profitability if you tweak them up or down. This is a powerful way to see, for instance, how a 10% change in sulfuric acid price can make or break your operation \u2014 or how speeding up the leach cycle yields faster returns on capital. If you\u2019re a biologist hoping to pitch a better microbe that reduces acid usage or accelerates reaction rates, the Tornado Chart pinpoints why (and how much) that matters.<\/p>\n\n\n\n This TEA indicates that there are three primary levers where biomining holds great potential in chalcopyrite heap leaching:<\/p>\n\n\n\n For academic scientists, it can be easy to get bogged down in how your engineered proteins or microbial communities work. But in the Command Center, the core question is: Are we reducing costs or increasing production speed (or both)? That is what determines if an idea moves forward in a commercial mine.<\/p>\n\n\n\n Orecast exists to help biotechnologists forecast the economic potential of their best ideas and communicate those ideas with potential funders and the mining industry.<\/em><\/p><\/blockquote><\/figure>\n\n\n\n Our hope is that this TEA, and the Orecast project in general, empowers biotechnologists to engage directly with mining\u2019s economic realities. By putting yourself in the Command Center, you\u2019ll see exactly how (and why) innovations can sink or swim on industrial scales.<\/p>\n\n\n\n Cleaner mining starts with shared goals and shared numbers. With this TEA, scientists, funders, and mining decision makers can all speak the same economic language.<\/p>\n\n\n\n If you have questions, feedback, or are interested in work like this \u2013 we invite you to reach out to us at jayme@homeworld.bio<\/a> and jesse@conductor-labs.com<\/a> <\/p>\n\n\n\n\n
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\n\n\n\nWhy Focus on Copper and Chalcopyrite?<\/h2>\n\n\n\n
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Meet the TEA: Your Command Center Dashboard<\/h2>\n\n\n\n
The Process Flow Diagram (PFD)<\/h3>\n\n\n\n
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The \u201cDashboard\u201d Sheet: Where the Numbers Come Together<\/h3>\n\n\n\n
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The Main sheet provides a high-level summary: annual tonnage, operating costs, capital costs, and revenue from copper sales. You\u2019ll see familiar (but often daunting) financial terms – like COGS (Cost of Goods Sold), CapEx (capital expenditures), and variable costs vs. fixed costs. If these terms are new to you, don\u2019t worry; our manual<\/a> is filled with definitions and references.
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From the perspective of mining economics, improving a process is only worthwhile if it reduces the dollars per tonne produced or increases the dollars per tonne sold. This model breaks out the biggest cost items, such as sulfuric acid, so that you can instantly see where a small scientific improvement might save millions of dollars annually at scale.
<\/li>\n<\/ul>\n\n\n\nTornado Charts and Sensitivity Analysis<\/h3>\n\n\n\n
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Above: sensitivity testing and a tornado chart for chalcopyrite heap leaching, as also seen in the Orecast model.<\/em><\/figcaption><\/figure>\n\n\n\nThree Big Opportunities for Biotech Innovation<\/h2>\n\n\n\n
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Sulfuric acid is expensive, particularly when it is deployed at a heap leach scale. Even a modest reduction in acid consumption can translate to massive savings. If your microbial process somehow regenerates or reduces the acid load, that directly impacts the bottom line.
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Heap leaching can be slow, on the order of months and years. Faster leaching means more metal recovered in less time, increasing throughput and allowing mines to produce more copper before adding new lifts. Time really is money in heap leaching.
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<\/strong>It goes without saying that extracting more copper can raise profits. But this aspect of the model provides a vignette into how TEAs can translate science into economics; a brilliant idea to remove passivation might take months to develop and hours to fully explain, but at an economic level, it\u2019s simplified to \u201cmore copper\u201d and potentially, then, \u201cmore profit\u201d.
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\n\n\n\nHow This TEA Resource Helps You<\/h3>\n\n\n\n
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If you have an innovative biomining approach, you can use this resource to plug in your assumptions about how it might perform. It translates lab-scale data into the financial metrics that mine operators and investors consider.
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Big ideas can die quickly if you can\u2019t show economic impact. Our TEA helps you see which improvements – such as acid consumption, extraction rate, and yield – are the ones that matter. It also reveals which cost items are relatively negligible, so you don\u2019t waste time on marginal gains.
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With every assumption clearly documented, you can\u2019t hide fuzzy math. You\u2019ll learn whether your \u201cworld-changing technology\u201d is truly a game-changer or just a neat lab project.
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This TEA doubles as a crash course in mining economics, and serves as an example of what \u2018good looks like\u2019 when it comes to projecting your economics at early stages. You won\u2019t need an MBA or to be a TEA expert to get started, but you’ll need to take time making the model your own. Our goal is to help get you started with a structure, industry-standard color-coding and formatting, and a detailed step-by-step manual, so you can gain the fluency required to confidently discuss feasibility with industry stakeholders.<\/li>\n<\/ul>\n\n\n\nHow to use this TEA Resource<\/h2>\n\n\n\n
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Above: the Orecast manual for the Chalcopyrite TEA.<\/em><\/figcaption><\/figure>\n\n\n\n\n
Access our open-source TEA workbook<\/a> and make a copy to play around in. Unfortunately, the Excel \u201cData Tables\u201d used to run the sensitivity analysis & tornado chart are only available in Excel, so beware that if you convert it into Google Sheets, there will be a loss in functionality.
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We\u2019ve written a thorough walkthrough and guide, which includes some examples that help users become familiar with the model. We recommend skim-reading the manual before trying to adapt this model for your own use!
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Head to the Dashboard sheet and check out the Tornado Chart. Use the sensitivity testing to understand how small changes in acid cost or leach rates shift profitability.
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We strongly encourage you to thoroughly understand how the model works and the applicability of the assumptions before taking the outputs at face value. This is more than a disclaimer\u2014we want climate biotech founders and ecosystem participants to develop robust mental models around TEA. As part of that, we remind users that we left the \u201cBioleach\u201d sheet as open-ended as possible, so if you already have lab data showing how your idea can shift a lever like leach rate or the total yield, input those assumptions to see the potential economic payoff.
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Use the Validation tab to compare your bottom-up assumptions with top-down industry benchmarks. For instance, equipment costs vary greatly from location to location – ensure the numbers the model is pulling make sense for you, and if something looks off, refine your inputs until the results make sense.<\/li>\n<\/ol>\n\n\n\nConclusion<\/h2>\n\n\n\n
Learn more about<\/h2>\n\n\n\n
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