Sergi Molins

Predicting the number of newly formed crystals and their spatial distribution on surfaces or within pore spaces matters across many fields, from structural biology to coupled fluid flow and reactive transport in porous media to atmospheric physics. Nucleation occurs at molecular and nanoscopic scales, yet classical nucleation theory (CNT) provides an averaged, macroscopic description, and a growing body of experimental observations is inconsistent with CNT predictions. Probabilistic nucleation models have been developed to predict mineral formation in reactive porous geochemical systems and to generate uncertainty estimates, for example, of how mineral growth affects fluid flow. However, the probability density functions of nucleation rates or induction times that underlie these models remain poorly constrained and are not grounded in the intrinsic nanoscopic physicochemical mechanisms underlying the observed macroscopic behavior. This perspective reviews recent advances in mineral nucleation research, focusing on modeling in coupled reactive transport systems, and examines how the large uncertainties reported for macroscopic nucleation rates may be linked to the extent and spatial distribution of surface sites with contrasting reactivity, such as kinks, steps, and terraces. Building on this, we propose a framework that integrates site-specific nucleation probabilities and explicitly accounts for polymorph selection to enable deterministic prediction of macroscopic nucleation rates from intrinsic surface properties. While the resulting parameter space is extensive, recent advances in machine learning, combined with high-throughput experimentation and simulation, suggest that such predictive, multiscale models are now within reach.

Watersheds function as biogeochemical reactors that control solute export and critical zone processes, including the chemical weathering of silicate minerals. Silicate weathering influences atmospheric carbon dioxide on geologic timescales and shapes water chemistry on shorter timescales, but the controls on mineral weathering rates are difficult to predict a priori because of the complex physical and biogeochemical processes involved. Moreover, anthropogenic forcings including acid deposition mean that modern observations of these processes may reflect substantial disequilibrium. Reactive transport models are a promising tool to understand how complex interactions between critical zone processes shape the hydrogeochemistry of watersheds. In this study, we use a watershed reactive transport model to explore the processes governing solute generation and export at the Hubbard Brook Experiment Forest (New Hampshire, USA), with an emphasis on silicate mineral weathering and the chemostasis of geogenic solutes. Coupling integrated hydrology with a biogeochemical reaction network in a spatially explicit model, we find the low pH and ionic strength of groundwaters means that chemical weathering occurs in far-from-equilibrium conditions, and low exposed surface areas of minerals maintain the dilute waters in the watershed. While chemical weathering rates are primarily influenced by temperature and thus greatest during summer months, our model reveals hydrologic connectivity of soils to the stream decreases over these warm periods. Built-up solutes in soil can subsequently flush during wetter periods, leading to the chemostatic behavior of geogenic solutes. Our results also show that strong acids from acid deposition drive >80% of silicate dissolution, significantly reducing carbon sequestration efficiency.

The weathering of sedimentary rocks in high‐elevation catchments influences freshwater quality and the global carbon cycle. While individual biogeochemical mechanisms involved in this process are relatively well understood, quantifying their contributions to solute export and carbon fluxes under natural, transient conditions remains challenging. Here, we implement a numerical multidimensional and multiphase model to simulate coupled hydrological and biogeochemical processes in a shale‐underlain, snow‐dominated hillslope in the Rocky Mountains, Colorado. The model captures the dynamic interplay between soil respiration, mineral weathering, and climate‐driven hydrological forcing, reproducing observed soil CO ₂ dynamics, groundwater chemistry, and subsurface flow. Our results reveal that seasonal snowmelt enhances carbonate weathering by promoting the infiltration of CO ₂ ‐rich water to depth, while pyrite oxidation is primarily sensitive to low water saturation that facilitates O ₂ diffusion through the regolith. Topography modulates the spatial distribution of shale weathering, as steeper slopes enhance lateral drainage, favoring the delivery of reactants to greater depths. While shale weathering at our site acts as a transient carbon sink, with silicates and carbonates buffering acidity and promoting atmospheric CO ₂ consumption (1% of soil‐derived CO ₂ ), the exported dissolved inorganic carbon is predominantly geogenic (∼73%). Consequently, when accounting for long‐term marine carbonate precipitation. The current weathering regime represents a net source of carbon to the atmosphere. The oxidation of pyrite and petrogenic organic carbon together release approximately 0.9 mol·m ⁻² ·yr ⁻¹ of CO ₂ . Our findings highlight the role of topography, hydroclimate, and the coupling between acid‐base reactions in shaping the carbon balance and the solute exports in mountainous critical zones.

Alquimia v1.0 is a generic interface to geochemical solvers that facilitates development of multiphysics simulators by enabling code coupling, prototyping and benchmarking. The interface enforces the function arguments and their types for setting up, solving, serving up output data and carrying out other common auxiliary tasks while providing a set of structures for data transfer between the multiphysics code driving the simulation and the geochemical solver. Alquimia relies on a single-cell approach that permits operator splitting coupling and parallel computation. We describe the implementation in Alquimia of two widely used open-source codes that perform geochemical calculations: PFLOTRAN and CrunchFlow. We then exemplify its use for the implementation and simulation of reactive transport in porous media by two open-source flow and transport simulators: Amanzi and ParFlow. We also demonstrate its use for the simulation of coupled processes in novel multiphysics applications including the effect of multiphase flow on reaction rates at the pore scale with OpenFOAM, the role of complex biogeochemical processes in land surface models such as the E3SM Land Model (ELM) and the impact of surface–subsurface hydrological interactions on hydrogeochemical export from watersheds with the Advanced Terrestrial Simulator (ATS). These applications make it apparent that the availability of a well-defined yet flexible interface has the potential to improve the software development workflow, freeing up resources to focus on advances in process models and mechanistic understanding of coupled problems.

We present Alquimia v1.0, a generic interface to geochemical solvers that facilitates development of multiphysics simulators by enabling code coupling, prototyping and benchmarking. The interface enforces a call signature for setting up, solving, serving up output data, and other common auxiliary tasks, while providing a set of structures for data transfer between the multiphysics code driving the simulation and the geochemical solver. Alquimia relies on a single-cell approach that permits operator splitting coupling and parallel computation. We describe the implementation in Alquimia of two widely-used open-source codes that perform geochemical calculations, PFLOTRAN and CrunchFlow. We then exemplify its use for the implementation and simulation of reactive transport in porous media by two open-source flow and transport simulators, Amanzi and Parflow. We also demonstrate its use for the simulation of coupled processes in novel multiphysics applications including the effect of multiphase flow on reaction rates at the pore scale with openFOAM, the role of complex biogeochemical processes in land surface models such as the E3SM Land Model (ELM), and the impact of surface-subsurface hydrological interactions on hydrogeochemical export from watersheds with the Advanced Terrestrial Simulator (ATS). These applications make it apparent that the availability of a well-defined yet flexible interface has the potential to improve the software development workflow, freeing up resources to focus on advances in process models and mechanistic understanding of coupled problems.

Geochemically driven alterations of fractures in multi‐mineral media can create altered layers (ALs) at the fracture‐matrix interface. Spatial variations in the AL significantly influence mass transfer across the interface, and the hydraulic and mechanical properties of the fractured medium. A real‐rock based microfluidic experiment reported spatial variations in AL thickness despite the initially smooth fracture surface, suggesting potential effects of matrix heterogeneity on AL development. However, the respective contribution of structural and mineralogical characteristics is still poorly understood. Using the microfluidic experimental data and a micro‐continuum reactive transport model, we systematically evaluated how micro‐porosity and initial mineral texture impact AL development and thus the overall reactive transport behaviors. Our simulation results confirmed that the extent of AL spatial variations, mainly controlled by mineralogical texture, influences the evolution of reaction and permeability in different ways. Accounting for spatial heterogeneity in mineral distribution produces “channeling” structures in ALs and lower overall reaction (by up to 35.6%), but larger permeability increase (by up to 9.8%). The characteristic length of the reactive mineral cluster was observed to dominate the internal texture of ALs. Whereas the presence of micro‐porosity can enhance mineral accessibility via improving connectivity for flow and transport, and lead to both higher bulk reaction, that is, thicker ALs, and permeability enhancement. Considerations of surface roughness with characteristic length on the same order of magnitude as mineral texture did not change the overall development of AL, which further highlights the importance of accounting for rock matrix properties in predicting long‐term evolution of fractured media. The resulting spatial variations of ALs and their impacts on bulk properties, however, are expected to be further complicated by the coupling of chemical and mechanical processes, and may trigger matrix disaggregation, erosion and other mechanisms of fractured media alteration.

Models have historically represented fractured porous media with continuum descriptions that characterize the media using bulk parameters. The impact of small-scale features is not captured in these models, although they may be controlling the performance of subsurface applications. Pore-scale models can simulate processes in small-scale features by representing the pore space geometry explicitly but are computationally expensive for large domains. The alternative multiscale approach entails the combination of pore-scale and continuum-scale descriptions in a single framework. We use Chombo-Crunch, a computational capability that discretizes complex geometries with an adaptive, embedded boundary method to contrast these two approaches. Chombo-Crunch takes advantage of recent computational performance and memory bandwidth improvements resulting from the emergence of exascale computing resources. These combined improvements enable the efficient simulation of reactive transport in fractured media with a high degree of fidelity and the ability to capture the control small-scale processes exert on the overall medium evolution.

Redox processes, aqueous and solid‐phase chemistry, and pH dynamics are key drivers of subsurface biogeochemical cycling and methanogenesis in terrestrial and wetland ecosystems but are typically not included in terrestrial carbon cycle models. These omissions may introduce errors when simulating systems where redox interactions and pH fluctuations are important, such as wetlands where saturation of soils can produce anoxic conditions and coastal systems where sulfate inputs from seawater can influence biogeochemistry. Integrating cycling of redox‐sensitive elements could therefore allow models to better represent key elements of carbon cycling and greenhouse gas production. We describe a model framework that couples the Energy Exascale Earth System Model (E3SM) Land Model (ELM) with PFLOTRAN biogeochemistry, allowing geochemical processes and redox interactions to be integrated with land surface model simulations. We implemented a reaction network including aerobic decomposition, fermentation, sulfate reduction, sulfide oxidation, methanogenesis, and methanotrophy as well as pH dynamics along with iron oxide and iron sulfide mineral precipitation and dissolution. We simulated biogeochemical cycling in tidal wetlands subject to either saltwater or freshwater inputs driven by tidal hydrological dynamics. In simulations with saltwater tidal inputs, sulfate reduction led to accumulation of sulfide, higher dissolved inorganic carbon concentrations, lower dissolved organic carbon concentrations, and lower methane emissions than simulations with freshwater tidal inputs. Model simulations compared well with measured porewater concentrations and surface gas emissions from coastal wetlands in the Northeastern United States. These results demonstrate how simulating geochemical reaction networks can improve land surface model simulations of subsurface biogeochemistry and carbon cycling.