Chemical Diversity of Metal Sulfide Minerals and Its Implications for the Origin of Life

Abstract

Prebiotic organic synthesis catalyzed by Earth-abundant metal sulfides is a key process for understanding the evolution of biochemistry from inorganic molecules, yet the catalytic functions of sulfides have remained poorly explored in the context of the origin of life. Past studies on prebiotic chemistry have mostly focused on a few types of metal sulfide catalysts, such as FeS or NiS, which form limited types of products with inferior activity and selectivity. To explore the potential of metal sulfides on catalyzing prebiotic chemical reactions, here, the chemical diversity (variations in chemical composition and phase structure) of 304 natural metal sulfide minerals in a mineralogy database was surveyed. Approaches to rationally predict the catalytic functions of metal sulfides are discussed based on advanced theories and analytical tools of electrocatalysis such as proton-coupled electron transfer, structural comparisons between enzymes and minerals, and in situ spectroscopy. To this end, we introduce a model of geoelectrochemistry driven prebiotic synthesis for chemical evolution, as it helps us to predict kinetics and selectivity of targeted prebiotic chemistry under "chemically messy conditions". We expect that combining the data-mining of mineral databases with experimental methods, theories, and machine-learning approaches developed in the field of electrocatalysis will facilitate the prediction and verification of catalytic performance under a wide range of pH and Eh conditions, and will aid in the rational screening of mineral catalysts involved in the origin of life.

Keywords: density functional theory; electrocatalysis; mineral catalysis; mineral diversity; origin of life; prebiotic chemistry; sulfide minerals.

Figure 1

Model of geoelectrochemical prebiotic synthesis for chemical evolution. In deep-sea hydrothermal vents, electrons generated from the oxidation of H₂ and H₂S in the hydrothermal fluids flow towards the seawater-rock interface through the porous, conductive metal sulfide chimney minerals. The reduction of molecules, such as CO₂, NO₃⁻, NO₂⁻, at the seawater-rock interface is catalyzed by metal sulfides to generate various types of life’s building blocks, which further undergo condensation or polymerization to bio-essential polymers.

Figure 2

Metal sulfide distribution in natural environments. The 20 most frequently observed species are ranked in order of locality counts. The chemical composition of each species is shown.

Figure 3

(a) Distribution and chemical diversity (chemical composition, Fe/S valence states, and crystal symmetry) of Fe single-metal sulfides. (b) Relative abundances and locality distribution of Fe²⁺-, Fe³⁺-, and Fe²⁺ plus Fe³⁺-sulfides. Note that the valence state of arsenopyrite (Fe³⁺(AsS)³⁻) in the RRUFF mineral database is examined as (Fe²⁺(AsS)²⁻) in this review based on electric spectroscopic observations [76,77].

Figure 4

(a–c) Possible reaction pathways for the electrocatalytic reduction of CO₂ to products on transition metals and molecular catalysts (adapted from Reference [91]): (a) reaction pathways from CO₂ to CO, CH₄ (blue arrows), CH₃OH (black arrows), and HCOO⁻ (orange arrows); (b) reaction pathways from CO₂ to ethylene (gray arrows) and ethanol (green arrows); (c) reaction pathway of CO₂ insertion into a metal−H bond yielding formate (purple arrows). Species in black are adsorbates, whereas those in red are reactants or products in solution. Potentials are reported versus RHE, RDS indicates the rate-determining step, and (H⁺ + e⁻) indicates steps in which either concerted or separated proton−electron transfer takes place. (d) Limiting potentials (U_L) for elementary proton-transfer steps in the reduction of CO₂ to CH₄ (adapted from Reference [96]). Each line represents the calculated potential at which the indicated elementary reaction step is neutral with respect to free energy and as a function of the carbon monoxide affinity (E_B[CO]) of the electrocatalyst. The theoretical overpotential is defined as the potential difference between the most-negative limiting potential line and the equilibrium potential for the reduction of CO₂ to CH₄ (+0.17 V versus RHE), as highlighted in gray.

Figure 5

Framework of the methodology proposed for the rational screening of mineral catalysts using DFT calculations. (a) Select a series of minerals and extract the structure and chemical composition information from the RRUFF mineralogy database (the mineral shown here is molybdenite, MoS₂, and was obtained from the mindat website: https://www.mindat.org/search.php?name=Molybdenite; the crystal structure was created using BIOVIA Draw software); (b) Calculate the electronic structure of the bulk catalyst and surface, and obtain information of the band gap, Fermi level, conductivity, and other electronic properties. The band structure shown here was obtained from the Materials Project database for molybdenite: https://materialsproject.org/; (c) Calculate the free energy landscape for the specific reaction (here, the reaction pathway scheme assumes that only one intermediate is involved); (d) Determine the activity descriptor (binding energy of the key intermediate). Using this approach, the relative activity profile for a series of minerals can be obtained. The predicted activity profile can be verified using experimental methods to validate the optimized computational model and obtain more precise structure-activity relationships.

Figure 6

(a) Rational screening of CO adsorption energy on the second-generation core-shell alloy surfaces using the developed neural network model. (b) The parity plot shows a comparison of the CO adsorption energies on selected Cu monolayer alloys calculated by the neural network model and self-consistent density functional theory (DFT) (adapted from Reference [160]).