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At least 235 records · Page 13

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics and Structure of Molten Neodymium Titanate

Binary rare earth titanates can be vitrified using levitation melt quenching, and their glasses are promising for optical applications. To better understand their thermophysical properties and dynamics, we have used molecular dynamics (MD) and empirical potential structure refinement (EPSR) to simulate molten neodymium titanate, 83TiO 2 –17Nd 2 O 3 . The models are compared with high-energy synchrotron X-ray diffraction of the melt structure over 1060–1960 K and thermophysical property measurements of electrostatically levitated droplets over 1500–2200 K. As temperature increases, the network periodicity increases and the correlation length decreases, both in monotonic trends that suggest continuous structural evolution through the melt and supercooled liquid regimes. At 1900 K, the mean Ti–O and Nd–O coordination numbers are 5.8(5) and 6.7(5), compared to the glass, 5.72(6) and 7.70(26). The equilibrium melting point is measured as 1860(20) K, over 100 K higher than previous estimates. Viscosity data from MD are in good agreement with experimental measurements. The dynamic propensity of Nd is similar to that of the network-forming Ti, suggesting that Nd does not participate as a conventional modifier. The viscosity of this fragile liquid is likely controlled by the breaking of cation–oxygen bonds and rearrangements of Ti–O polyhedra.

molecular dynamics↗

Illuminating the mechanistic impacts of an Fe-quaterpyridine functionalized crystalline poly(triazine imide) semiconductor for photocatalytic CO 2 reduction

The strategy of incorporating earth-abundant catalytic centers into light-absorbing architectures is desirable from the viewpoint of low cost, low toxicity, and versatility for activating small molecules to produce solar-based fuels. Herein, we show that an Fe-quaterpyridine molecular catalyst can be anchored to a light-absorbing, crystalline, carbon nitride (PTI), to yield a molecular-catalyst/material hybrid, Fe-qpy-PTI, capable of facilitating CO 2 reduction to CO selectively (up to ∼97–98%) in aqueous solution under low-intensity light irradiation. This hybrid material leverages the ability of the Fe-qpy catalyst to bind CO 2 upon a one-electron reduction, as achieved by transfer of excited electrons from the carbon-nitride semiconductor. At a low incident power density of only 50 mW cm −2 , the catalytic activity of the hybrid material was measured across a range of catalyst loadings from 0.1–3.8 wt%, yielding CO rates of up to 596 μmol g −1 h −1 for a 3.8 wt% loading during a 3 h experiment. Over the course of 8 h, the hybrid material attained a CO evolution rate of 608 μmol g −1 h −1 and 305 turnovers for a TOF of ∼38 h −1 and an apparent quantum yield of 2.6%. Higher light intensities provided an initial increase in activity but negatively impacted photocatalytic rates with time, with an AQY of 0.6% at 150 mW cm −2 and 0.4% at 250 mW cm −2 . Transient absorption spectroscopy results showed electron survival probabilities consistent with the trends in observed product rates. Computational modeling was also used to evaluate and understand the mechanistic pathway of the high product selectivity for CO versus H 2 . These results thus help unveil key factors for leveraging the mechanistic understanding of molecular catalysts for CO 2 reduction for pairing with light absorbing semiconductors and establishing optimal conditions to attain maximal rates in aqueous solution.

McGuigan, Scott [Baylor University, Waco, TX (Unit↗

Unravelling Microstructure Selection in an Additively Manufactured Eutectic High‐Entropy Alloy

High-entropy alloys (HEAs) are promising candidates for advanced structural applications due to their excellent mechanical properties. Additive manufacturing (AM), with its rapid solidification conditions, enables the creation of unique nonequilibrium microstructures. To fully leverage the synergy between AM and HEAs, understanding how processing affects structure and properties is essential. Here, how solidification rate influences microstructure evolution and phase transformation pathway in laser additively manufactured AlCrFe2Ni2 eutectic HEAs is investigated. By increasing the laser scan speed and hence the solidification rate, distinct solidification modes evolving from coupled eutectic to anomalous eutectic and eventually to single-phase solidification are revealed. These transitions result in distinct microstructures and a wide range of mechanical properties. Thermodynamic modeling and molecular dynamics simulations reveal that low cooling rates allow for sufficient atomic diffusion and phase separation, facilitating coupled eutectic growth. In contrast, rapid cooling suppresses diffusion and destabilizes the solid–liquid interface, promoting anomalous or single-phase solidification. This integrated experimental and computational approach provides a multiscale understanding of solidification mechanisms in HEAs and underscores how kinetic effects can over-ride thermodynamic predictions under nonequilibrium conditions. Furthermore, these results demonstrate that AM can serve as a powerful tool to design HEAs with tailored microstructures and properties.

36 MATERIALS SCIENCE↗

Fused-ring isomerism modulates molecular packing and device performance in non-halogenated organic solar cells

Subtle changes in molecular backbone geometry impact intermolecular interactions and performance of organic solar cells. Here, three isomeric small-molecule acceptors (NaO1, NaO2, and NaO3) are investigated to reveal how different fused-ring configurations control molecular packing, electronic coupling, and film formation. Structural and spectroscopic analyses show that the linearly fused NaO1 forms a compact three-dimensional packing network with large and balanced electronic couplings (>24 meV) across multiple directions, while the more curved analogues exhibit excessive crystallization and phase segregation. In-situ optical measurements demonstrate that NaO1 promotes fast and continuous structural evolution during film formation, resulting in smooth morphology and homogeneous phase distribution. These structural and dynamic advantages facilitate efficient charge generation and transport, accompanied by reduced non-radiative energy loss, ultimately achieving an efficiency of 20.07% for non-halogenated ternary devices. Our findings highlight how fused-ring isomerism decisively governs structure–packing–performance relationships in organic solar cells.

36 MATERIALS SCIENCE↗

Ancient co-option of LTR retrotransposons as yeast centromeres

Centromeres ensure accurate chromosome segregation, yet their DNA evolves rapidly across eukaryotes leaving the origins of new centromere architectures unclear. The brewer’s yeast Saccharomyces cerevisiae exemplifies this long-standing puzzle. Its centromeres shifted ancestrally from large, repeat-rich, epigenetically specified forms to the compact, genetically defined ‘point’ centromeres. How this transition occurred has remained unresolved6. Here we identify evolutionarily related ‘proto-point’ centromeres that provide a resolution to the evolutionary origins of point centromeres. Proto-point centromeres contain a single centromeric nucleosome positioned over an AT-rich core, accompanied by relaxed organization and sequence variability of flanking cis-elements. In two species, these proto-point centromeres lie within retrotransposon-derived repeat clusters, linking ancestral repeat-rich centromeres to genetically encoded ones. Comparative and phylogenetic analyses indicate that proto-point and point centromeres evolved in an ancestor with retrotransposon-rich centromeres. These results identify long-terminal-repeat retrotransposons, specifically Ty5 sequences, as the genetic substrate for point-centromere evolution and provide a mechanistic route by which an epigenetic centromere can become genetically specified. More broadly, they show how selfish elements can be co-opted to perform essential chromosomal functions.

Haase, Max A. B. [Max Planck Institute of Molecula↗

Probing Carbon Mineralization Mechanisms in Pore and Bulk Fluids by Harnessing Architected Calcium Silicates

The ability to synthesize materials with well-controlled pore structures gives us unprecedented control over probing fluid interactions with reactive interfaces and advancing calibrated insights into coupled chemo-morphological interactions. One of the primary challenges in developing crystalline silicate materials lies in achieving ordered pore structures. Existing approaches of producing amorphous mesoporous metal silicates via sol–gel methods and heat-treatment of these materials to produce crystalline phases cause the pore structures in the amorphous phases to collapse. To overcome this challenge, carbon coating of amorphous mesoporous calcium silicate particles is carried out to retain the pore structure, while the material is heated to produce crystalline calcium silicate with calcium sulfate inclusions. The pore diameter in these materials is about 3.9 nm, with a surface area and a pore volume of 28.75 m 2 /g and 0.092 cm 2 /g, respectively. The mechanisms of carbon mineralization are investigated by reacting architected calcium silicate with 1 M Na 2 CO 3 and monitoring the evolution in the structural phases using operando wide-angle X-ray scattering (WAXS) measurements. Formation of stable calcium carbonate polymorph or calcite and metastable calcium carbonate polymorph or vaterite in pore and bulk fluids, respectively, resulting from the reaction between Na 2 CO 3 and CaSiO 3 , are noted. The mechanisms associated with carbon mineralization are delineated using ReaxFF molecular dynamics (MD) simulations. The surface dissolution reaction is initiated by 2H + ions that replace a Ca 2+ ion in the Ca–silicate matrix. Ca 2+ ions in the solution initially react with water to form calcium hydroxide and eventually form calcium (bi)carbonate. A slow and gradual increase in the formation of sodium silicate in the solution resulting from the reactions of silicic acid or the silicon dioxide reaction with sodium hydroxide is noted. When carbon mineralization occurs in environments bearing interfacial fluids, calcite is the dominant calcium carbonate polymorph, as determined using experiments with pore fluids and molecular-scale simulations. In conclusion, these studies provide fundamental insights into the mechanisms underlying the carbon mineralization of calcium silicate informed by experiments and molecular-scale simulations.

Calcium↗

Unveiling the Role of Surface Ir-Oxo Species in O 2 Evolution at IrO 2 Electrocatalysts via Embedded Cluster Multireference Calculations

Understanding the mechanisms driving the oxygen evolution reaction (OER) on iridium oxide (IrO 2 )-based catalysts is essential to improving their performance and enabling an actual scale-up of water-splitting photoelectrochemical cells. The mechanistic pathways at IrO 2 interfaces have been extensively investigated computationally using density functional theory (DFT), which predicts a high-energy barrier for the last step of the OER of molecular oxygen detachment and release from the catalyst surface. Nevertheless, surface O 2 over- and under-binding results by standard generalized gradient approximation and hybrid density functionals, respectively, call for further analysis of this crucial step via multireference methods. Aiming at unveiling the nature of such a barrier, we hereby address the formation of O 2 from the most-stable IrO 2 (110) surface with both periodic DFT and an electrostatic embedded cluster approach at the n-electron valence-state perturbation theory. With this multireference approach, we find a value for the aforementioned energy barrier that is much closer to experimental indications than DFT ones. Here, an in-depth analysis of the involved molecular orbitals suggests that the origin of this barrier is related to the breaking of a π interaction between O 2 and Ir surface atom and to a significant additional O 2 interaction with adjacent electrophilic Ir-oxo species, which is present under experimental operating conditions. Besides shedding light on the mechanism of the OER on IrO 2 , these findings point out the importance of multireference methods for dissecting complex reactions at electrocatalytic interfaces and pave the route for further investigations with effective embedding approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Generalized Grain-Scale Model for the Non-Plasma and Plasma-Assisted Hydrogen Direct Reduction of Iron Ore

Direct Reduction of Iron ore using hydrogen (H-DRI) is a promising pathway towards efficient steelmaking and accurate predictive models are a necessity for scale-up and optimization of this technology. However, accurate models of this process remain limited because existing models oversimplify grain-scale phenomena, such as nonlinearity inside grain, self-sufficient porosity, surface reactions, and the role of plasma species. These phenomena are important for flash steelmaking and plasma-assisted H-DRI processes. To address this need, we present a phenomenological model for simulating H-DRI at the scale of a single micron-sized grain of the iron ore. We call this the Transient Reactive Grain Model (TRGM). TRGM incorporates key physical process: gas species transport, a chemical kinetics of material conversion, nanopore structural evolution and, adsorption-desorption surface kinetics at the reactive nanopore surface. The important contribution of this work is that the model provides a dependence on different reductant species, specifically hydrogen atoms versus molecules, so that role of hydrogen plasma reduction can be clarified compared to the use of pure hydrogen gas reduction. TRGM predictions agree well with experimental data for both molecular H2 reduction of Fe2O3 and plasma hydrogen reduction of Fe3O4. Results reveal species concentration gradients with a diffuse reaction zone, and enhanced hydrogen diffusion at the grain outer surface due to evolving porosity. These findings challenge common assumptions in existing models, including sharp reaction fronts, quasi-steady diffusion and kinetics, and the neglect of surface chemistry. As a generalized grain-scale model for H-DRI processes, TRGM has practical applications in flash steelmaking and in-flight reduction using both molecular and plasma hydrogen.

08 HYDROGEN↗

Risk assessment of wellbore leakage during underground hydrogen storage

The expansion of renewable energy sources would require large-scale energy storage options to overcome the intermittent nature of these sources. Underground hydrogen storage (UHS) in depleted hydrocarbon reservoirs offers a scalable and practical energy storage solution. These reservoirs are chosen for their availability and large capacity, but the unique properties of hydrogen raise concerns about potential leakage pathways, particularly through wellbores. In this study, we develop and apply, for the first time, reduced-order models (ROMs) specifically designed for efficient leakage risk prediction in UHS systems operating in depleted hydrocarbon reservoirs. Using 3,000 high-fidelity simulation scenarios, we examine the influence of 11 key parameters, including reservoir and aquifer depths, wellbore permeability and porosity, initial saturations of water, oil and gas fractions (hydrogen, light, intermediate, and heavy hydrocarbons), reservoir pressure multiplier, and the aquifer-to-reservoir volume ratio, to simulate leakage behavior over a 1,000-year timescale. We train ROMs using a two-step classification-regression approach, achieving R 2 values exceeding 99 % across all targets. These ROMs effectively capture the leakage evolution and identify critical controls of leakage, guiding the design of mitigation strategies. Results indicate that gas leakage occurs in about 27 % of scenarios as early as five years post-operation, reaching volumes of up to 106 ft3. Oil leakage is less frequent (~17 %) and typically begins decades later. Our findings also show that hydrogen often migrates first, owing to its smaller molecular size and higher buoyancy, followed by heavier hydrocarbons. Over time, these heavier components contribute significantly to the total leaked volume, reinforcing the need for targeted monitoring and remediation strategies. Our analysis highlights that deeper storage reservoirs, shallower aquifers, and low-permeability wellbores significantly reduce leakage risks. In conclusion, this work offers a robust framework for risk-informed UHS deployment, supporting energy security through reliable large-scale hydrogen storage while safeguarding environmental integrity.

08 HYDROGEN↗

Two-Dimensional Tantalum Carbo-Selenide for Hydrogen Evolution

Herein, we report the synthesis of two-dimensional Ta 2 Se 2 C (2D-Ta 2 Se 2 C) nanosheets using electrochemical lithiation in multilayer Ta 2 Se 2 C followed by sonication in deionized water. Multilayer Ta 2 Se 2 C was obtained via solid-state synthesis of Fe x Ta 2 Se 2 C followed by chemical etching of Fe. 2D-Ta 2 Se 2 C exhibited promising electrocatalytic activity for the hydrogen evolution reaction from water compared to multilayer Ta 2 Se 2 C and 2D-TaSe 2 . 2D-Ta 2 Se 2 C showed an overpotential at 10 mA·cm -2 (η 10 ) of 264 mV, a Tafel slope of 91 mV·dec -1 , and an electrochemically active surface area of 17.61 m ECSA 2 ·g catalyst -1 . The high performance could be attributed to the large surface area of single sheets which hence maximizes the number of exposed catalytic sites and increased density of vacancies, observed with transmission electron microscopy, during synthesis and processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evolution of carbapenemase activity in the class C β-lactamase ADC-1

Antibiotic resistance in bacteria poses a significant threat to public health. Among dozens of available antimicrobial agents, carbapenems are used as drugs of choice for the treatment of serious infections caused by pathogens resistant to other antibiotics. However, their usefulness has been severely compromised due to the emergence and wide spread of carbapenem-resistant clinical isolates worldwide. High-level resistance to carbapenems in bacteria is mediated by the production of β-lactamases from three molecular classes, A, B, and D, but not by class C enzymes. In this study, we selected a triple mutant of the intrinsic class C Acinetobacter-derived cephalosporinase ADC-1 (ADC-1 TM ) that confers high-level resistance to the carbapenems meropenem, ertapenem, and doripenem. Kinetic experiments demonstrated that the apparent binding affinity, along with the acylation and deacylation rates, were all improved for the mutant enzyme. X-ray crystallography, molecular docking, and molecular dynamics simulations revealed that the amino acid substitutions in ADC-1 TM produce significant changes in the enzyme active site architecture and binding mode of the carbapenem ertapenem. These changes allow for better positioning of a deacylating water for nucleophilic attack, thus explaining the significantly improved rate of ertapenem deacylation by ADC-1 TM . In this study, we showed for the first time that a class C β-lactamase can produce high-level resistance to carbapenem antibiotics, which underlines the potential for enzymes of this class to evolve such resistance and could further exacerbate the problem of antibiotic resistance in bacteria.

59 BASIC BIOLOGICAL SCIENCES↗

SUDA: A SUrface Dust Analyser for Compositional Mapping of the Galilean Moon Europa

Abstract The Surface Dust Analyser (SUDA) is a mass spectrometer onboard the Europa Clipper mission for investigating the surface composition of the Galilean moon Europa. Atmosphereless planetary moons such as the Galilean satellites are wrapped into a ballistic dust exosphere populated by tiny samples from the moon’s surface produced by impacts of fast micrometeoroids. SUDA will measure the composition of such surface ejecta during close flybys of Europa to obtain key chemical signatures for revealing the satellite’s composition such as organic molecules and salts, history, and geological evolution. Because of their ballistic orbits, detected ejecta can be traced back to the surface with a spatial resolution roughly equal to the instantaneous altitude of the spacecraft. SUDA is a Time-Of-Flight (TOF), reflectron-type impact mass spectrometer, optimized for a high mass resolution which only weakly depends on the impact location. The instrument will measure the mass, speed, charge, elemental, molecular, and isotopic composition of impacting grains. The instrument’s small size of$268 ~\mathrm {mm} \times 250 ~\mathrm {mm} \times 171$ 268 mm × 250 mm × 171 $~\mathrm {mm}$ mm , radiation-hard design, and rather large sensitive area of 220 cm 2 matches well the challenging demands of the Clipper mission.

Astronomy & Astrophysics↗

Comparison of the Arrhenius parameters between conventional hydrothermal and microwave-assisted synthesis methods for tin oxide nanoparticles

Microwave (MW) irradiation has emerged as a powerful tool for accelerating materials synthesis, yet the origins of its specific influence on reaction kinetics remain elusive. While multiple studies have attributed the observed enhancements in reaction rates under MW heating to reduced activation energies, other accounts have suggested modifications to the Arrhenius pre-exponential factor as the predominant cause. Distinguishing between these parameters in modern applications of MW processing in nanomaterials requires experimental approaches capable of resolving the dynamic and nuanced structural kinetics that govern MW-assisted chemistry. Here, we combine in-situ synchrotron X-ray total scattering with pair distribution function (PDF) analysis to track the structural evolution of SnO 2 nanoparticles synthesized via MW-assisted and conventional hydrothermal conditions. Avrami modeling and Arrhenius analysis suggest that although MW irradiation yields a higher apparent activation energy, the enhanced crystallization is better explained by a pre-exponential factor several orders of magnitude larger than that of conventional heating. These findings suggest that the MW field induces a higher frequency of successful molecular rearrangements rather than lowering the intrinsic activation barrier. The results contribute further insights clarifying the role of the applied MW field for materials design where MW-specific effects can be deliberately harnessed. Furthermore, this work presents a framework promoting the utility of in-situ PDF characterization coupled with kinetic analysis for developing more sophisticated descriptions of nanoscale transformations for MW-driven reaction kinetics.

36 MATERIALS SCIENCE↗

Integrative analysis of CAM photosynthesis reveals its impact on primary metabolism in Yucca

Crassulacean Acid Metabolism (CAM) is an adaptation that temporally separates carbon uptake at night from photosynthesis during the day. CAM has evolved repeatedly across vascular plants, as its emergence may depend on simple regulatory changes to deeply conserved metabolic pathways. Modern CAM research relies heavily on interpretation of transcriptomic data, though regulation occurs at multiple levels following transcription. Additionally, while most research to date has focused on a handful of genes and metabolites in the core CAM pathway, the co-option of conserved regulatory and functional genes is bound to have wide-ranging effects on other aspects of primary metabolism. In this study, we integrate transcriptomic, proteomic, and metabolomic data to compare primary metabolism between the CAM species Yucca aloifolia and closely related C 3 species, Y. filamentosa. We observe minimal correlation between protein abundance and mRNA expression, suggesting significant post-transcriptional regulation in CAM species. We also find evidence of shifts in gene expression and metabolite accumulation outside of the central CAM pathway, suggesting that the shift to CAM has cascading effects across primary metabolism, especially nitrogen metabolism. Our findings provide insights into the metabolic shifts associated with CAM evolution, and highlight the complexity of its regulation at multiple biological levels.

59 BASIC BIOLOGICAL SCIENCES↗

Highly Active Hydrogen Evolution Reaction (HER) Catalysts Formed by Energetic Pt n Cluster Deposition: Deposition Dynamics and the HER Mechanism

Mass-selected Pt n + (n ≤ 7) were deposited at variable energies on highly oriented pyrolytic graphite (HOPG), creating highly active hydrogen evolution reaction (HER) electrocatalysts. HER mass activities were ~2 to >10 times higher than those for the surface atoms in bulk Pt and for Pt n deposited on several other supports. Thus, high activity reflects the Pt-C structures formed by energetic Pt n -HOPG impacts, in addition to high Pt surface availability. The Pt n /HOPG electrodes were probed by X-ray photoelectron spectroscopy, low energy ion scattering, and electron microscopy. Born-Oppenheimer molecular dynamics (BOMD) was used to simulate Pt n - HOPG impacts, revealing the types of structures formed at different energies, then DFT was used to probe their most important HER pathways. For low deposition energies, the Pt n deposit onto the HOPG surface with sub-unit sticking probability, aggregating at defects. With increasing deposition energy, the sticking probability initially decreases, then rises to unity as subplantation and defect creation allow formation of strongly bonded platinum-carbon structures. Barriers for HER on these structures were found to be low and weakly dependent on Pt n size, consistent with experiment. The activities were highest for small covalently-bonded Pt-C structures created at high deposition energies. The larger aggregated structures formed at low energies were less active, but still substantially better than the bulk Pt surface monolayer. The catalysts were stable in repeated potential cycling at reducing potentials, but electrodes containing subplanted Pt became more active when scanned to oxidizing potentials, due to emergence of subplanted Pt onto the surface.

08 HYDROGEN↗

The role of manganese in CoMnO x catalysts for selective long-chain hydrocarbon production via Fischer-Tropsch synthesis

Cobalt is an efficient catalyst for Fischer–Tropsch synthesis (FTS) of hydrocarbons from syngas (CO + H 2 ) with enhanced selectivity for long-chain hydrocarbons when promoted by Manganese. However, the molecular scale origin of the enhancement remains unclear. Here we present an experimental and theoretical study using model catalysts consisting of crystalline CoMnO x nanoparticles and thin films, where Co and Mn are mixed at the sub-nm scale. Employing TEM and in-situ X-ray spectroscopies (XRD, APXPS, and XAS), we determine the catalyst’s atomic structure, chemical state, reactive species, and their evolution under FTS conditions. We show the concentration of CH x , the key intermediates, increases rapidly on CoMnO x , while no increase occurs without Mn. DFT simulations reveal that basic O sites in CoMnO x bind hydrogen atoms resulting from H 2 dissociation on Co 0 sites, making them less available to react with CH x intermediates, thus hindering chain termination reactions, which promotes the formation of long-chain hydrocarbons.

36 MATERIALS SCIENCE↗