OLI’s latest release (v12.5) isn’t just an update – it’s a comprehensive infusion of new chemical data that strengthens simulation fidelity across the board. In this blog, we dive into the major industry verticals and explore what new chemistry has been added, why it matters to real operations, where competitors fall short, and how OLI’s modeling edge provides a decisive advantage. Whether you’re in oil & gas, refining, CCUS, power, critical materials, geothermal, or nuclear sectors, there’s something here for you.
Upstream Oil & Gas
New Chemistry Added: OLI v12.5 introduces improved coverage for upstream gas and condensate systems, including interactions of common production chemicals and gases. Notably, the databanks now better represent MEG (Monoethylene Glycol) in natural gas dehydration contexts and its interactions with light gases like H₂, CO, and Ar. Additionally, the update refines thermodynamics for mixed acid gas systems, which helps in modeling scenarios like high CO₂/H₂S content with various impurities.
Why It Matters: In upstream operations, preventing hydrate formation and corrosion is a constant battle. MEG is used to inhibit hydrates in gas pipelines, but its efficacy depends on complex chemistry with the gas mixture. With v12.5’s data, engineers can accurately simulate MEG regeneration loops and gas dehydration units, ensuring enough MEG is injected to prevent hydrates without overdoing it. The inclusion of H₂/CO/Ar interactions means simulations of high-pressures gases (e.g., from hydrogen-rich fields or gas injection EOR projects) are more on-point. Overall, this leads to safer flow assurance strategies and optimized chemical usage – hydrate blockages can be avoided (preventing costly downtime), and facilities can size/regenerate glycol systems more efficiently.
OLI’s Differentiation: Most general simulators handle hydrocarbons well but falter with electrolyte systems like MEG-water-salt or acid gas chemistry. They might not rigorously account for salt precipitation in MEG reclaimers or the exact vapor-liquid equilibria of multi-component acid gases. OLI’s specialization in electrolyte thermodynamics gives it a leg up – competitors often oversimplify or exclude the detailed ion chemistry. For instance, predicting when salt will drop out in a MEG system (a major operating issue) requires OLI’s electrolyte models; competitors likely can’t do this with the same accuracy, leaving a blind spot for users.
OLI’s Advantage: By delivering precise predictions for complex mixtures (hydrates, salts, acids), OLI v12.5 enables upstream operators to fine-tune their production chemistry like never before. One tangible advantage is asset integrity: with better corrosion modeling for high-CO₂/H₂S using the new alloy data (e.g., S13Cr, S17Cr steels common in wells), companies can choose optimal materials and corrosion inhibitor programs. Competitors often lack these alloy-specific corrosion models, so they can’t provide the same guidance – an area where OLI users will save money by avoiding over-conservatism or worse, unexpected failures. In short, OLI v12.5 acts as a high-fidelity virtual flow assurance lab for upstream producers, something no other tool in the market currently offers with the same depth.
Downstream Oil & Gas
New Chemistry Added: Refiners see several important additions. Key among them is the inclusion of Thiosulphuric Acid (H₂S₂O₃) in the database. OLI v12.5 also adds data for Calcium Malate, an organic salt that has been known to precipitate in some refining processes. Furthermore, the update brings in additional hydrocarbon components that were previously missing in the MSE framework – for example, 1,2- and 1,3-Butadiene, 1,2,4-Trimethylbenzene, and 1-Octene. This help round out the light ends and intermediate streams coverage in complex refinery simulations.
Why It Matters: Refining is all about managing a very diverse chemical soup, from crude oil constituents to treatment chemicals to process byproducts. The addition of thiosulphuric acid is significant for the crude distillation units, sour water strippers and sulfur recovery units – this species can lead to unexpected corrosion or catalyst deactivation if not accounted for. Now refiners can simulate its formation and behavior, leading to better strategies to neutralize or flush it out, thereby improving corrosion mitigation in those units. Calcium malate’s inclusion targets cooling water and wash water systems where organic acids can lead to scale deposits; having it in the model means refiners can predict and prevent such fouling, ensuring heat exchangers and effluent systems remain clean. The new hydrocarbons like butadiene and trimethylbenzene enable more accurate property predictions in units like distillation columns or gasoline blenders, especially when processing certain feeds or petrochemical streams. It all boils down to refiners being able to optimize processes (and troubleshoot issues) with greater confidence, from avoiding unexpected downtime due to fouling to squeezing a bit more efficiency in fractionation because the model matches reality better.
OLI’s Differentiation: Many refinery modeling packages focus on hydrocarbon pseudo components and might not include detailed electrolyte or uncommon species effects. For example, a generic process simulator may not consider thiosulfate chemistry at all, or it might lump all organic acids in one neutral “acid number” without specificity. Thus, competitor users might be blind to a developing thiosulfate corrosion issue or unable to explain a certain deposit. OLI’s competitor advantage is its comprehensive electrolyte database – it doesn’t hand-wave away things that are present at ppm levels but cause major headaches. Competition often requires custom inputs or doesn’t support these niche species at all, forcing engineers to run separate manual calculations or experiments.
OLI’s Advantage: With v12.5, OLI solidifies itself as the refiner’s secret weapon for tackling “off-design” chemistry problems. Case in point: a refinery using high TAN (acidic) crude oils can simulate neutralization and fouling control steps now that malates and other organic salts are in the toolkit. The ability to quantify such effects might allow that refinery to process a discounted crude that others avoid – directly improving profit margins. Also, consider environmental compliance: OLI can model complex wastewater neutralization chemistry post-refining, ensuring contaminants are properly treated; competing tools typically stop at the process battery limit. OLI’s end-to-end chemistry approach means users can trace issues to their root causes. For instance, if a strange solid forms on a stripper reboiler tube, an OLI simulation might reveal it is calcium malate precipitating – information that can save weeks of investigative downtime. In summary, OLI v12.5 offers refiners a competitive edge by providing insight into both the ordinary and the extraordinary chemistry of their processes, enabling proactive measures that competitors’ tools wouldn’t even suggest.
Carbon Capture, Utilization, Transportation and Storage
New Chemistry Added: CCUS applications get a significant boost through OLI v12.5’s enhanced data on CO₂ mixtures and carbonates. The update includes comprehensive modeling of CO₂ with common impurities such as CO, N₂, H₂, O₂, Ar, and light hydrocarbons (C1–C6) in the presence of water and acids. This means you can accurately simulate a Transport CO₂ stream that isn’t pure – a real-world scenario for flue gas capture where oxygen or nitrogen might slip through. Importantly, magnesium carbonate systems have been expanded, including both stable and metastable phases of hydrated magnesium carbonates. This is directly relevant to CO₂ mineralization efforts (turning CO₂ into solid rock forms). Additionally, v12.5 covers the chemistry of using magnesium oxide and other magnesium minerals to capture CO₂, which is a novel route some startups are exploring for direct air capture or flue gas treatment.
Why It Matters: For CCUTS to be effective and economical, the chemistry of capture and storage must be well-understood. The presence of impurities in captured CO₂ affects everything from corrosion in pipelines to the efficiency of injection into wells. With OLI’s new data, project engineers can ensure CO₂ transport integrity by simulating these multi-component mixes – e.g., determining if adding a bit of O₂ in the CO₂ will form corrosive nitric or sulfuric acids in pipelines. This guides purification requirements and inhibitor dosing, directly impacting project safety and cost. On the utilization side, the magnesium carbonate addition is a game-changer for those looking to permanently sequester CO₂ via mineralization. You can now model how CO₂ reacts with brucite or olivine (magnesium-containing minerals) to form magnesite or hydro magnesite, etc., predicting how fast and complete those reactions might be. That informs reactor designs and throughput for CO₂-to-solid processes. Essentially, OLI v12.5 equips CCUTS developers to design and optimize capture units, pipelines, and storage schemes with a much higher degree of certainty. It’s about avoiding nasty surprises (like a pipeline blockage from unexpected solid formation, or an amine unit degrading because of unforeseen contaminants) and maximizing CO₂ converted or stored with novel methods.
OLI’s Differentiation: Traditional process simulators might handle pure CO₂ and maybe a simplified amine chemistry, but they’re not built for the plethora of scenarios CCUTS entails. Many do not have a database for things like CO₂ reacting with solid minerals or forming multiple carbonate phases – that’s very specific and requires an electrolyte model like OLI’s. Competitors also typically simplify acid gas systems (assuming ideal or using average properties), whereas OLI’s model will rigorously handle electrolyte formation (carbonic acid, etc.) and phase splits. Additionally, competing tools often lack robust corrosion prediction for dense phase CO₂ streams with impurities. They might not tell you if 100 ppm SO₂ in your CO₂ will make sulfurous acid and corrode a carbon steel line – but OLI will, thanks to its coupled chemistry-corrosion approach.
OLI’s Advantage: OLI v12.5 gives CCUS practitioners the confidence to push boundaries. For example, a team developing direct air capture with a novel sorbent can simulate the entire sorbent regeneration chemistry, including minor byproducts, because the data is there. If a competitor’s tool can’t model the precipitation of a certain carbonate scale in the contactor, they’d have to rely on empirical testing alone (time-consuming and expensive). OLI’s advantage is in de-risking scale-up: by simulating scenarios digitally (like what happens if the captured CO₂ from a cement plant has 3% oxygen – will my pipeline corrode or my injector well clog with carbonate?), operators can mitigate issues from the start. This can save multi-millions by preventing failure of a CO₂ transport line or by extending the life of an amine solvent through proper specs. With climate-related projects under intense scrutiny for reliability and safety, having OLI’s robust predictions is an edge in winning stakeholder trust and even insurance underwriting. Simply put, OLI v12.5 is the “intel inside” that CCUTS projects need to run smoothly and cost-effectively, outpacing those who rely on less specialized tools.
Powe Generation and Geothermal
New Chemistry Added: In the power generation sphere (especially for plants dealing with steam cycles, emissions control, or geothermal fluids), OLI v12.5 delivers important enhancements. A headline addition is Antimony Sulfide (Sb₂S₃) solubility and speciation data in water and brines. Antimony issues often arise in geothermal brine handling and even in some coal boiler systems (traces of Sb from feedwater treatments). The database also now includes various mercury salts – such as mercurous and mercuric formate, glycolate, oxalate, and nitrates – which relate to flue gas desulfurization (FGD) wastewater and geothermal brine contaminants. These allow modeling of mercury partitioning between water, solids, and maybe vapor. Additionally, although not explicitly “new species,” the overall improvements in mixed-solvent electrolyte calculations mean better accuracy for power plant chemistry like borate hydrolysis in nuclear or silica scaling in high-temperature systems (many of these improvements stem from MSE framework refinements and expanded species).
Why It Matters: Geothermal Power: Antimony sulfide scaling is a notorious problem in geothermal operations – it can plate out in pipes and reinjection wells, drastically reducing efficiency and requiring expensive cleaning. With OLI’s new Sb₂S₃ data, geothermal engineers can predict when and where antimony might precipitate in their process: for example, as the brine cools in a heat exchanger or as it flashes to steam. By simulating different conditions, they might find that maintaining a slightly higher pH or adding a chemical inhibitor keeps Sb in solution, thus preventing scale. This directly translates to higher plant uptime and less maintenance cost. Thermal Power & FGD: Mercury is a toxic element that coal-fired power plants must manage, especially in wastewater from FGD units. The mercury salt data in v12.5 means plants can model how mercury forms complexes (like Hg glycolate) in scrubber solutions or how it might be removed via precipitation. This knowledge helps in designing treatment systems that ensure compliance with strict mercury discharge limits. Essentially, power plants can avoid regulatory penalties and environmental harm by optimizing their mercury removal with accurate modeling. Additionally, any power plant using amines for CO₂ capture, will benefit from the CO₂ impurity data we discussed earlier – ensuring, for example, that oxygen in flue gas doesn’t create corrosive acids that the amine unit can’t handle.
OLI’s Differentiation: Traditional power plant chemistry tools (like those used for boiler water chemistry) often rely on empirical tables and simpler models. They usually don’t incorporate species like antimony or mercury in a predictive way – engineers might rely on field experience or separate lab tests. For geothermal, many simulators treat brine as just NaCl water with maybe silica; few have the breadth to include antimony or other heavy metals. Thus, competing modeling packages might simply not flag a potential Sb₂S₃ problem at all. Mercury modeling is similarly niche – general simulators don’t have a built-in understanding of mercury complexation in different solutions; at best, users would input partition coefficients from literature. OLI’s competitor advantage comes from its comprehensive, rigorous thermodynamic model: it can handle multi-component electrolytes with trace contaminants reliably, where others throw up their hands or require custom coding.
OLI’s Advantage: The advantage for power and geothermal operators using OLI v12.5 is predictive control. They can simulate “what-if” scenarios that others cannot. For example, a geothermal operator can test how a slight change in brine temperature or adding a different scale inhibitor impacts antimony precipitation – all in the digital model, which is far cheaper and faster than experimenting on the plant. This can guide operational setpoints that avoid scale entirely. Competitors’ users might only react after the scale forms. Over years, that difference is huge: avoiding just one unplanned shutdown to acid-clean a clogged geothermal reinjection line can save millions and preserve plant output. In the broader power context, OLI’s data helps utilities inch closer to zero-emission water discharge by understanding complex contaminant chemistry (like those mercury salts). They can tailor water treatment chemicals to precipitate out the bad actors without overspending on reagents. This fine-tuning capability is something only OLI’s high-fidelity model affords. Moreover, as the power industry moves toward more integrated systems (think plants co-capturing CO₂, co-producing valuable minerals from brine, etc.), OLI’s unified approach to chemistry will enable innovative revenue streams (e.g., extracting lithium from geothermal brine while producing power). Competitors’ tools compartmentalize problems (one tool for power cycle, another for chemistry) and miss such synergistic opportunities. OLI users, however, can pursue them with confidence.
Critical Materials (Metals & Battery Recycling)
New Chemistry Added: The critical materials sector – encompassing battery metal mining, refining, and recycling – is a big winner in v12.5. The OLI database now contains extensive new data for cobalt and nickel solvent extraction systems, including updated equilibria for extraction of cobalt/nickel by organophosphorus and amide extractants. We also see cadmium species added (like Cadmium Telluride and Cadmium Sulfide) which are crucial for solar panel recycling and processing. For rare earth elements (REEs), v12.5 introduces data on rare earth complexation with EDTA and extraction with specialized reagents such as TODGA (tetraoctyl diglycolamide). On top of that, lithium processing gets a boost: there’s a revision of alkaline systems containing lithium and calcium, improving simulations for lithium brine refining (e.g., predicting scaling or yields in evaporation). In short, a broad swath of new components from the periodic table – Co, Ni, Cd, Nd, etc. – and their interactions are now accurately represented.
Why It Matters: As electric vehicles, renewable energy, and electronics drive demand for critical minerals, efficient extraction and recycling processes are paramount. OLI v12.5 equips engineers in this space with the ability to model and optimize complex hydrometallurgical flowsheets that were previously very challenging to get right. For example, in a battery recycling plant, separating cobalt and nickel from a leachate via solvent extraction is a key step. With OLI’s new data, one can simulate the exact pH at which cobalt preferentially transfers to the organic phase versus nickel, using real extractants like D2EHPA or TODGA, rather than approximations. This leads to higher purity products and minimal losses, which directly improves profitability (these metals are high value). For rare earth separation, which traditionally involves many stages and is more of an art than science, having EDTA complexation data means we can predict how to wash out impurities or recover REEs from wastewater streams more effectively. Lithium producers can use the improved lithium-calcium model to avoid complications like unwanted gypsum or carbonate precipitation during evaporation – ensuring maximum lithium recovery from brines. Ultimately, these chemistry additions mean critical material companies can achieve higher yields, better product purities, and lower reagent consumption, because they’re optimizing with a precise digital twin of their process chemistry.
OLI’s Differentiation: Competitors in this niche are few; often, companies resort to lab experiments or simplistic models. Generic chemical process simulators usually don’t have robust databases for rare earths or specialized organics. They might allow a user to input equilibrium constants if known, but that requires data the user often doesn’t have (and getting it experimentally is time-consuming). For example, very few, if any, off-the-shelf simulators have TODGA extraction equilibria for neodymium built-in – OLI does. Likewise, EDTA chelation of rare earths is a complex speciation problem that OLI’s electrolyte engine can handle, whereas competitors might not even allow defining such a multi-dentate ligand easily. In lithium brine chemistry, competitors often fail once you have more than just sodium-chloride present; they might not capture borates or the Mg/Li competition properly. OLI’s models are specifically designed for multi-electrolyte systems, so it shines where others give up or oversimplify (e.g., treating “total hardness” instead of specific Ca/Mg interactions with Li – a nuance OLI covers).
OLI’s Advantage: OLI v12.5 gives critical material projects a critical edge: the ability to design processes right the first time and adapt quickly. For instance, if a recycling company can simulate a new extraction reagent in OLI and discover it yields 5% better recovery of cobalt, they can implement it before their competitors even understand what’s happening. Time to market in battery recycling is vital as gigafactories are ramping up – OLI users can more rapidly iterate process improvements digitally. Also, waste reduction is huge here: these metals are expensive, and environmental rules are strict. OLI’s accurate predictions help minimize waste by pinpointing optimal conditions, meaning more metal in product and less in effluent. Competing firms without such tools may have to run more pilot trials or operate more conservatively (leaving more metal in waste to avoid co-extraction issues, for example). That’s essentially leaving money on the table. Additionally, OLI’s tool can handle integrated process steps (e.g., leaching -> solvent extraction -> precipitation -> crystallization) all in one model, giving holistic optimization. Others might treat each step in isolation, missing interactions (like an impurity that slips through leaching might affect extraction – OLI will catch that, others might not). The bottom line is OLI v12.5 lets critical material producers achieve higher efficiency and react quickly to material or feed changes, which is a decisive competitive advantage in markets where feed compositions (like recycled batteries) can vary widely. It turns chemical complexity into an asset – something you can master and capitalize on – rather than a risk.
Nuclear Water & Industrial Water Treatment
New Chemistry Added: In the realm of nuclear waste processing and advanced water treatment, OLI v12.5 has expanded its database to include species and data that are crucial for handling trace contaminants. Noteworthy additions are Rubidium and Cesium sulfate systems. These alkali metals are common problematic fission products in nuclear waste leachates and were previously tricky to model when they co-exist with other electrolytes. OLI also incorporated a range of mercury compounds (as mentioned earlier) that are relevant not only to power but also to waste streams from various industries. Specifically, organic mercury species like Dimethylmercury and Methylmercury Hydroxide/Nitrate have been added – these are highly toxic forms of mercury that can appear in certain waste treatments (or even in natural waters via bioprocesses). Additionally, OLI’s general improvements help with modeling extremely caustic or acidic solutions often encountered in nuclear waste (such as tank wastes containing 10-15 Molar NaOH with odd mixtures of radionuclides – while not a single “new species”, the breadth of data ensures all relevant ions are considered).
Why It Matters: Nuclear Waste: When treating or vitrifying nuclear waste, understanding the behavior of minor components like Cs⁺, Rb⁺ is important for predicting things like saltcake formation, ion exchange efficiency, or glass formulation constraints. Cesium, for example, is often captured on special filters or incorporated into glass – knowing its thermodynamic activity helps engineers set the right conditions for maximum removal. With OLI v12.5, nuclear engineers can simulate these highly alkaline, saline solutions and see, for instance, at what point will cesium start precipitating with sulfate, or how adding certain reagents might sequester it. That translates to improved safety and compliance, ensuring radioactive cesium is immobilized and won’t leach later. Water Treatment: Mercury and other heavy metals in industrial wastewater are a top environmental concern. OLI’s inclusion of various mercury species means that water treatment specialists can model the fate of mercury through a treatment train – whether it stays dissolved, forms a solid, or volatilizes. This is crucial for designing treatment steps like precipitation (do we lime-soften and get mercury out as HgO or Hg(OH)₂? Will it form a complex we need a different approach for?). By simulating these, plants can guarantee that their effluents meet regulations before actual implementation. For instance, knowing methylmercury might form under certain redox conditions could prompt an operator to adjust aeration or chemical feeds to prevent that, since methylmercury is especially nasty. Ultimately, these data empower industries (from nuclear sites to chemical plants) to handle toxic trace components with a science-backed approach, improving environmental performance and reducing liability.
OLI’s Differentiation: Nuclear waste simulations are often done with bespoke codes or very simple assumptions because commercial simulators aren’t well-suited for such extreme chemistries (high ionic strength, exotic species). Competitors do not have a comprehensive nuclear chemistry set – they might handle common ions but not the weird mix a Hanford tank has, for example. OLI’s decades of electrolyte research make it uniquely positioned here. Regarding mercury, most water treatment models (if any) are basic or ignore organo-mercury species. They might allow a generic “heavy metal” removal efficiency input, but they won’t calculate speciation. That’s a big gap, because something like dimethylmercury will not be removed by the same process as ionic mercury – you need to model it to know that. So, competitors often just assume all mercury = Hg²⁺ for simplicity, which could lead to under designing a treatment system. OLI doesn’t take such shortcuts.
OLI’s Advantage: In these sensitive fields, accuracy and credibility are everything. OLI v12.5 provides an advantage by allowing practitioners to demonstrate – to regulators, stakeholders, or the public – that they have a rigorous understanding of their process chemistry. For example, a nuclear waste cleanup team can use OLI to prove that adding a certain sulfate source will preferentially precipitate 99% of cesium as a solid (perhaps as Cs₂SO₄) before sending waste to vitrification, thereby reducing Cs volatility. That level of detail can make or break regulatory approval for a treatment plan. Competitors simply can’t generate such evidence because their tools won’t model it. Similarly, a city wastewater authority dealing with mercury in industrial pretreatment can model worst-case scenarios with OLI: e.g., if a factory discharges some organomercury, will our standard treatment remove it? If not, what do we tweak? OLI gives concrete answers, whereas others guess. The advantage is risk mitigation – fewer unknown unknowns. This means fewer surprises like “oops, the fish downstream have mercury, guess our system didn’t catch that form of Hg.” Avoiding such outcomes not only saves money (avoiding fines, cleanup costs) but preserves the organization’s reputation. From a competitive standpoint, engineering firms using OLI can win bids by highlighting their sophisticated modeling of contaminants (“we use OLI’s state-of-the-art chemistry engine to ensure even parts-per-billion issues are addressed”), setting them apart from competitors who offer less certainty. In summary, OLI v12.5’s new chemistry for nuclear and water applications is about doing the most challenging chemistry right – a capability that truly differentiates leaders in safety and environmental stewardship from the rest of the pack.
Conclusion
Across all these verticals, a pattern emerges: OLI v12.5’s expanded chemistry databank gives companies the knowledge and confidence to push boundaries and excel in their operations. By covering the edge cases and the newly important cases (from energy transition to resource recycling), OLI ensures that no critical chemical insight is missing when decisions are made.
Competitors often force engineers to operate with broader safety margins or to conduct extensive experimentation because their tools can’t predict specific behaviors. That’s effectively a tax on innovation and efficiency. In contrast, OLI’s rigorous approach is an enabler – it frees engineers to experiment virtually, optimize finely, and implement bold ideas with lower risk.
In tangible terms, what does this mean? It means higher profitability (through higher yields, less downtime, lower reagent costs), faster time-to-market for new processes (since modeling guides development), and stronger compliance and sustainability outcomes (since environmental control can be designed proactively, not reactively). It is often said that knowledge is power – in the industrial world, chemical knowledge is competitive power, and OLI v12.5 hands that power to its users in an unprecedented scope.
Finally, it’s worth noting the broader vision: OLI’s continual investment in its chemistry model reflects a commitment to scientific leadership. By choosing OLI v12.5, companies signal to the market that they are on the cutting edge of technology, whether it’s a miner assuring a car manufacturer of responsibly maximizing battery metal recovery, or a utility guaranteeing the efficacy of its carbon capture system. This credibility can open doors – to partnerships, to funding (especially in green tech areas), and to winning contracts where technical differentiation matters.
In conclusion, each drop of new chemistry in OLI v12.5 is a drop of fuel for innovation in the respective industry it serves. Those who leverage it will find themselves ahead of the curve, able to solve problems others can’t, and turning chemical complexities into strategic advantages. In a world where success often hinges on mastering the details, OLI v12.5 ensures that no molecular detail is out of reach, empowering you to engineer a better (and more profitable) future.