Unveiling Competitive Adsorption in TiO2 Photocatalysis through Machine-Learning-Accelerated Molecular Dynamics, DFT, and Experimental Methods.

The efficient harnessing of solar power for water treatment via photocatalytic processes has long been constrained by the challenge of understanding and optimizing the interactions at the photocatalyst surface, particularly in the presence of nontarget cosolutes. The adsorption of these cosolutes, such as natural organic matter, onto photocatalysts can inhibit the degradation of pollutants, drastically decreasing the photocatalytic efficiency. In the present work, computational methods are employed to predict the inhibitory action of a suite of small organic molecules during TiO2 photocatalytic degradation of para-chlorobenzoic acid (pCBA). Specifically, tryptophan, coniferyl alcohol, succinic acid, gallic acid, and trimesic acid were selected as interfering agents against pCBA to observe the resulting competitive reaction kinetics via bulk and surface phase reactions according to Langmuir-Hinshelwood adsorption dynamics. Experiments revealed that trimesic and gallic acids were most competitive with pCBA, followed by succinic acid. Density functional theory (DFT) and machine learning interatomic potentials (MLIPs) were used to investigate the molecular basis of these interactions. The computational findings showed that while the type of functional group did not directly predict adsorption affinity, the spatial arrangement and electronic interactions of these groups significantly influenced adsorption dynamics and corresponding inhibitory behavior. Notably, MLIPs, derived by fine-tuning models pretrained on a vastly larger dataset, enabled the exploration of adsorption behaviors over substantially longer periods than typically possible with conventional ab initio molecular dynamics, enhancing the depth of understanding of the dynamic interaction processes. Our study thus provides a pivotal foundation for advancing photocatalytic technology in environmental applications by demonstrating the critical role of molecular-level interactions in shaping photocatalytic outcomes.

Bromine Incorporation Affects Phase Transformations and Thermal Stability of Lead Halide Perovskites.

Mixed-cation and mixed-halide lead halide perovskites show great potential for their application in photovoltaics. Many of the high-performance compositions are made of cesium, formamidinium, lead, iodine, and bromine. However, incorporating bromine in iodine-rich compositions and its effects on the thermal stability of the perovskite structure has not been thoroughly studied. In this work, we study how replacing iodine with bromine in the state-of-the-art Cs0.17FA0.83PbI3 perovskite composition leads to different dynamics in the phase transformations as a function of temperature. Through a combination of structural characterization, cathodoluminescence mapping, X-ray photoelectron spectroscopy, and first-principles calculations, we reveal that the incorporation of bromine reduces the thermodynamic phase stability of the films and shifts the products of phase transformations. Our results suggest that bromine-driven vacancy formation during high temperature exposure leads to irreversible transformations into PbI2, whereas materials with only iodine go through transformations into hexagonal polytypes, such as the 4H-FAPbI3 phase. This work sheds light on the structural impacts of adding bromine on thermodynamic phase stability and provides new insights into the importance of understanding the complexity of phase transformations and secondary phases in mixed-cation and mixed-halide systems.

2D Metal/Graphene and 2D Metal/Graphene/Metal Systems for Electrocatalytic Conversion of CO2 to Formic Acid.

Efficiently transforming CO2 into renewable energy sources is crucial for decarbonization efforts. Formic acid (HCOOH) holds great promise as a hydrogen storage compound due to its high hydrogen density, non-toxicity, and stability under ambient conditions. However, the electrochemical reduction of CO2 (CO2 RR) on conventional carbon black-supported metal catalysts faces challenges such as low stability through dissolution and agglomeration, as well as suffering from high overpotentials and the necessity to overcome the competitive hydrogen evolution reaction (HER). In this study, we modify the physical/chemical properties of metal surfaces by depositing metal monolayers on graphene (M/G) to create highly active and stable electrocatalysts. Strong covalent bonding between graphene and metal is induced by the hybridization of sp and d orbitals, especially the sharp d z 2 ${{d}_{{z}^{2}}}$ , d y z ${{d}_{yz}}$ , and d x z ${{d}_{xz}}$ orbitals of metals near the Fermi level, playing a decisive role. Moreover, charge polarization on graphene in M/G enables the deposition of another thin metallic film, forming metal/graphene/metal (M/G/M) structures. Finally, evaluating overpotentials required for CO2 reduction to HCOOH, CO, and HER, we find that Pd/G, Pt/G/Ag, and Pt/G/Au exhibit excellent activity and selectivity toward HCOOH production. Our novel 2D hybrid catalyst design methodology may offer insights into enhanced electrochemical reactions through the electronic mixing of metal and other p-block elements.

Multiscale Modeling Approach for the Aldol Addition Reaction in Multicompartment Micelle-Based Nanoreactor.

Water has emerged as a versatile solvent for organic chemistry in recent years due to its abundance, low cost, and environmental friendliness. However, one of the most important reactions, the aldol reaction, in the presence of excess water exhibits low yields and poor enantioselectivities. In this regard, we have employed a multiscale modeling approach to investigate the aldol addition reaction catalyzed by l-proline in the hydrophobic compartment of multicompartment micelle (MCM) nanoreactor consisting of amphiphilic bottlebrush copolymer, which minimizes the water content at the reactive site. Through performing dissipative particle dynamics (DPD) simulation, it is found that the "clover-like" morphology of the MCM is formed from multiblock copolymer with a sequence of ethylene oxide-based hydrophilic blocks, styrene lipophilic blocks, l-proline catalyst blocks, and a pentafluorostyrene fluorophilic block in aqueous media. We find that the vicinity of the catalyst in the clover-like MCM has a low dielectric environment, which could facilitate the aldol addition reaction. Our DFT calculations demonstrate that the asymmetric aldol addition of l-proline-catalyzed acetone and 4-nitrobenzaldehyde is energetically more favorable under the low dielectric environment in MCM compared with other commonly used solvents such as DMSO, water, and vacuum condition.

Catalysis Sans Catalyst Loss: The Origins of Prolonged Stability of Graphene-Metal-Graphene Sandwich Architecture for Oxygen Reduction Reactions.

Over the past decades, the design of active catalysts has been the subject of intense research efforts. However, there has been significantly less deliberate emphasis on rationally designing a catalyst system with a prolonged stability. A major obstacle comes from the ambiguity behind how catalyst degrades. Several degradation mechanisms are proposed in literature,   but with a lack of systematic studies, the causal relations between degradation and those proposed mechanisms remain ambiguous. Here, a systematic study of a catalyst system comprising of small particles and single atoms of Pt sandwiched between graphene layers, GR/Pt/GR, is studied to  unravel the degradation mechanism of the studied electrocatalyst for oxygen reduction reaction(ORR). Catalyst suffers from atomic dissolution under ORR harsh acidic and oxidizing operation voltages. Single atoms trapped in point defects within the top graphene layer on their way hopping through toward the surface of GR/Pt/GR architecture. Trapping mechanism renders individual Pt atoms as single atom catalyst sites catalyzing ORR for thousands of cycles before washed away in the electrolyte. The GR/Pt/GR catalysts also compare favorably to state-of-the-art commercial Pt/C catalysts and demonstrates a rational design of a hybrid nanoarchitecture with a prolonged stability for thousands of operation cycles.

Distribution and Transport of CO2 in Hyperbranched Poly(ethylenimine)-Loaded MCM-41: A Molecular Dynamics Simulation Approach.

Fossil fuel use is accelerating climate change, driving the need for efficient CO2 capture technologies. Solid adsorption-based direct air capture (DAC) of CO2 has emerged as a promising mode for CO2 removal from the atmosphere due to its potential for scalability. Sorbents based on porous supports incorporating oligomeric amines in their pore spaces are widely studied. In this study, we investigate the intermolecular interactions and adsorption of CO2 and H2O molecules in hyperbranched poly(ethylenimine) (HB-PEI) functionalized MCM-41 systems to understand the distribution and transport of CO2 and H2O molecules. Density Functional Theory (DFT) is employed to compute the binding energies of CO2 and H2O molecules with HB-PEI and MCM-41 and to develop force field parameters for molecular dynamics (MD) simulations. The MD simulations are performed to examine the distribution and transport of CO2 and H2O molecules as a function of the HB-PEI content. The study finds that an HB-PEI content of approximately 34 wt % is thermodynamically favorable, with an upper limit of HB-PEI loading between 45 and 50 wt %. The distribution of CO2 and H2O molecules is primarily determined by their adsorptive binding energies, for which H2O molecules dominate the occupation of binding sites due to their strong affinity with silanol groups on MCM-41 and amine groups of HB-PEI. The HB-PEI content has a considerable impact on the diffusion of CO2 and H2O molecules. Furthermore, a larger number of water molecules (higher relative humidity) reduces the correlation of CO2 with the MCM-41 pore surface while enhancing the correlation of CO2 with the amine groups of the HB-PEI. Overall, the presence of H2O molecules increases the CO2 correlation with the amine groups and also the CO2 transport within HB-PEI-loaded MCM-41, meaning that the presence of H2O enhances the CO2 capture in the HB-PEI-loaded MCM-41. These findings are consistent with experimental observations of the impact of increasing humidity on CO2 capture while providing new, molecular-level explanations for the macroscopic experimental findings.

Dual-light emitting 3D encryption with printable fluorescent-phosphorescent metal-organic frameworks.

Optical encryption technologies based on room-temperature light-emitting materials are of considerable interest. Herein, we present three-dimensional (3D) printable dual-light-emitting materials for high-performance optical pattern encryption. These are based on fluorescent perovskite nanocrystals (NCs) embedded in metal-organic frameworks (MOFs) designed for phosphorescent host-guest interactions. Notably, perovskite-containing MOFs emit a highly efficient blue phosphorescence, and perovskite NCs embedded in the MOFs emit characteristic green or red fluorescence under ultraviolet (UV) irradiation. Such dual-light-emitting MOFs with independent fluorescence and phosphorescence emissions are employed in pochoir pattern encryption, wherein actual information with transient phosphorescence is efficiently concealed behind fake information with fluorescence under UV exposure. Moreover, a 3D cubic skeleton is developed with the dual-light-emitting MOF powder dispersed in 3D-printable polymer filaments for 3D dual-pattern encryption. This article outlines a universal principle for developing MOF-based room-temperature multi-light-emitting materials and a strategy for multidimensional information encryption with enhanced capacity and security.

Nonorthogonal Cascade Catalysis in Multicompartment Micelles.

Multicompartment micelles (MCMs) containing acid and base sites in discrete domains are prepared from poly(norbornene)-based amphiphilic bottlebrush copolymers in aqueous media. The acid and base sites are localized in different compartments of the micelle, enabling the nonorthogonal reaction sequence: deacetalization - Knoevenagel condensation - Michael addition of acetals to 2-amino chromene derivatives. Computational simulations using dissipative particle dynamics (DPD) elucidated the bottlebrush composition required to effectively site-isolate the nonorthogonal catalysts. This contribution presents MCMs as a new class of nanostructures for one-pot multistep nonorthogonal cascade catalysis, laying the groundwork for the isolation of three or more incompatible catalysts to synthesize value-added compounds in a single reaction vessel, in water.

The selective heating effect of microwave irradiation on a binary mixture of water and polyethylene oxide: a molecular dynamics simulation approach.

In this study, we investigate the molecular mechanisms of a microwave-driven selective heating process by performing molecular dynamics simulations for three different systems including pure water, pure polyethylene oxide (PEO), and water-PEO mixed systems in the presence of a microwave with two different intensities of electric field such as 0.001 V Å-1 and 0.01 V Å-1 at a frequency of 100 GHz. First, from performing molecular dynamics simulations of CO and CO2 in the presence of the microwave, it is confirmed that the molecular dipole moment is responsible for the rotational motion induced by the oscillating electric field. Second, by analyzing the MD simulations of the pure water system, we discover that the dipole moment of water exhibits a time lag with respect to the microwave. During the heating process, however, the temperature, kinetic, and potential energies increase synchronously with the oscillating electric field of the microwave, showing that the heating of the water system is caused by the molecular reaction of water to the microwave. Comparing the water-PEO mixed system to the pure water and pure PEO systems, the water-PEO mixed system has a higher heating rate than the pure PEO system but a lower heating rate than the pure water system. Therefore, we conclude that heating the water-PEO mixed system is driven by water molecules selectively activated by microwave irradiation. We also calculate the diffusion coefficients of water molecules and PEO chains by describing their mean square displacements, demonstrating that the diffusion coefficients are increased in the presence of microwaves for both water and PEO in pure and mixed systems. Lastly, during the microwave heating process, the structures of the water-PEO mixed system are altered as a function of the intensity of electric field, which is mainly driven by the response of water molecules.

Thermoresponsive Conductivity of Graphene-Based Fibers.

Smart materials are versatile material systems which exhibit a measurable response to external stimuli. Recently, smart material systems have been developed which incorporate graphene in order to share on its various advantageous properties, such as mechanical strength, electrical conductivity, and thermal conductivity as well as to achieve unique stimuli-dependent responses. Here, a graphene fiber-based smart material that exhibits reversible electrical conductivity switching at a relatively low temperature (60 °C), is reported. Using molecular dynamics (MD) simulation and density functional theory-based non-equilibrium Green's function (DFT-NEGF) approach, it is revealed that this thermo-response behavior is due to the change in configuration of amphiphilic triblock dispersant molecules occurring in the graphene fiber during heating or cooling. These conformational changes alter the total number of graphene-graphene contacts within the composite material system, and thus the electrical conductivity as well. Additionally, this graphene fiber fabrication approach uses a scalable, facile, water-based method, that makes it easy to modify material composition ratios. In all, this work represents an important step forward to enable complete functional tuning of graphene-based smart materials at the nanoscale while increasing commercialization viability.

Optimal high-throughput virtual screening pipeline for efficient selection of redox-active organic materials.

As global interest in renewable energy continues to increase, there has been a pressing need for developing novel energy storage devices based on organic electrode materials that can overcome the shortcomings of the current lithium-ion batteries. One critical challenge for this quest is to find materials whose redox potential (RP) meets specific design targets. In this study, we propose a computational framework for addressing this challenge through the effective design and optimal operation of a high-throughput virtual screening (HTVS) pipeline that enables rapid screening of organic materials that satisfy the desired criteria. Starting from a high-fidelity model for estimating the RP of a given material, we show how a set of surrogate models with different accuracy and complexity may be designed to construct a highly accurate and efficient HTVS pipeline. We demonstrate that the proposed HTVS pipeline construction and operation strategies substantially enhance the overall screening throughput.

Catalytically Active Multicompartment Micelles.

This article presents the self-assembly behavior of multicompartment micelles (MCMs) in water into morphologies with multiple segregated domains and their use as supports for aqueous catalysis. A library of poly(norbornene)-based amphiphilic bottlebrush copolymers containing covalently attached l-proline in the hydrophobic, styrene, and pentafluorostyrene domains and a poly(ethylene glycol)-containing repeat unit as the hydrophilic block have been synthesized using ring-opening metathesis polymerization. Interaction parameter (χ) values between amphiphilic blocks were determined using a Flory-Huggins-based computational model. The morphologies of the MCMs are observed via cryogenic transmission electron microscopy and modeled using dissipative particle dynamic simulations. The catalytic activities of these MCM nanoreactors were systematically investigated using the aldol addition between 4-nitrobenzaldehyde and cyclohexanone in water as a model reaction. MCMs present an ideal environment for catalysis by providing control over water content and enhancing interactions between the catalytic sites and the aldehyde substrate, thereby forming the aldol product in high yields and selectivities that is otherwise not possible under aqueous conditions. Catalyst location, block ratio, and functionality have substantial influences on micelle morphology and, ultimately, catalytic efficiency. "Clover-like" and "core-shell" micelle morphologies displayed the best catalytic activity. Our MCM-based catalytic system expands the application of these nanostructures beyond selective storage of guest molecules and demonstrates the importance of micelle morphology on catalytic activity.

Graphene Nanoribbon Hybridization of Zeolitic Imidazolate Framework Membranes for Intrinsic Molecular Separation.

Zeolitic imidazolate frameworks (ZIFs) are promising for gas separation membrane, but their molecular cut-off differs from that expected from its intrinsic aperture structure because of their flexibility. Herein, we introduced graphene nanoribbons (GNRs) to rigidify the ZIF framework. Because the sp2 edge of the GNRs induces strong anchoring effects, the modified layer can be rigidified. Particularly, when the GNRs were embedded and distributed in the ZIF-8 layer, an intrinsic aperture size of 3.4 Šwas observed, resulting in high H2 /CO2 separation (H2 permeance: 5.2×10-6  mol/m2 Pa s, ideal selectivity: 142). The performance surpasses the upper bound of polycrystalline MOF membrane performance. In addition, the membrane can be applied to blue H2 production, as demonstrated with a simulated steam reformed gas containing H2 /CO2 /CH4 . The separation performance was retained in the presence of water. The fundamentals of the molecular transport through the rigid ZIF-8 framework were revealed using molecular dynamics simulations.

Carbon Quantum Dot Modified Reduced Graphene Oxide Framework for Improved Alkali Metal Ion Storage Performance.

Organic materials with redox-active oxygen functional groups are of great interest as electrode materials for alkali-ion storage due to their earth-abundant constituents, structural tunability, and enhanced energy storage properties. Herein, a hybrid carbon framework consisting of reduced graphene oxide and oxygen functionalized carbon quantum dots (CQDs) is developed via the one-pot solvothermal reduction method, and a systematic study is undertaken to investigate its redox mechanism and electrochemical properties with Li-, Na-, and K-ions. Due to the incorporation of CQDs, the hybrid cathode delivers consistent improvements in charge storage performance for the alkali-ions and impressive reversible capacity (257 mAh g-1 at 50 mA g-1 ), rate capability (111 mAh g-1 at 1 A g-1 ), and cycling stability (79% retention after 10 000 cycles) with Li-ion. Furthermore, density functional theory calculations uncover the CQD structure-electrochemical reactivity trends for different alkali-ion. The results provide important insights into adopting CQD species for optimal alkali-ion storage.

Cooperativity in the Aldol Condensation Using Bifunctional Mesoporous Silica-Poly(styrene) MCM-41 Organic/Inorganic Hybrid Catalysts.

This work explores the efficacy of silica/organic hybrid catalysts, where the organic component is built from linear aminopolymers appended to the silica support within the support mesopores. Specifically, the role of molecular weight and polymer chain composition in amine-bearing atom transfer radical polymerization-synthesized poly(styrene-co-2-(4-vinylbenzyl)isoindoline-1,3-dione) copolymers is probed in the aldol condensation of 4-nitrobenzaldehyde and acetone. Controlled polymerization produces protected amine-containing poly(styrene) chains of controlled molecular weight and dispersity, and a grafting-to thiol-ene coupling approach followed by a phthalimide deprotection step are used to covalently tether and activate the polymer hybrid catalysts prior to the catalytic reactions. Site-normalized batch kinetics are used to assess the role of polymer molecular weight and chain composition in the cooperative catalysis. Lower-molecular-weight copolymers are demonstrated to be more active than catalysts built from only molecular organic components or from higher-molecular-weight chains. Molecular dynamics simulations are used to probe the role of polymer flexibility and morphology, whereby it is determined that higher-molecular-weight hybrid structures result in congested pores that inhibit active site cooperativity and the diffusivity of reagents, thus resulting in lower rates during the reaction.

Accelerating Solvent Selection for Type II Porous Liquids.

Type II porous liquids, comprising intrinsically porous molecules dissolved in a liquid solvent, potentially combine the adsorption properties of porous adsorbents with the handling advantages of liquids. Previously, discovery of appropriate solvents to make porous liquids had been limited to direct experimental tests. We demonstrate an efficient screening approach for this task that uses COSMO-RS calculations, predictions of solvent pKa values from a machine-learning model, and several other features and apply this approach to select solvents from a library of more than 11,000 compounds. This method is shown to give qualitative agreement with experimental observations for two molecular cages, CC13 and TG-TFB-CHEDA, identifying solvents with higher solubility for these molecules than had previously been known. Ultimately, the algorithm streamlines the downselection of suitable solvents for porous organic cages to enable more rapid discovery of Type II porous liquids.

Single-Step Fabrication of Polymeric Composite Membrane via Centrifugal Colloidal Casting for Fuel Cell Applications.

Recent interest in polymer electrolyte membranes (PEMs) for fuel cell systems has spurred the development of infiltration technology by which to insert ionomers into mechanically robust reinforcement structures by solution casting in order to produce a cost effective and highly efficient electrolyte. However, the results of the fabrication process often continue to present challenges related to the structural complexity and self-assembly dynamics between the hydrophobic and hydrophilic parts of the constituents which in turn, necessitates additional processing steps and increases production costs. Here, a single-step process is reported for highly compact polymeric composite membranes (PCMs), fabricated using a centrifugal colloidal casting (C3) method. Combined structural analyses as well as coarse-grained molecular dynamics simulations are employed to determine the micro-/macroscopic structural characteristics of the fabricated PCMs. These findings indicate that the C3 method is capable of forming highly dense ionomer matrix-reinforcement composites consisting of microphase-separated ionomer structures with tailored crystallinity and ionic cluster sizes. An outcome that is very unlikely with the single-step coating steps in conventional methods. These structural attributes ensure PCMs with better proton conductivity, greater strain stability, and lower gas crossover properties compared to commercial pristine membranes, expanding their possible range of applicability to PEMs.

DFT-Machine Learning Approach for Accurate Prediction of pKa.

In this study, we propose a novel method of pKa prediction in a diverse set of acids, which combines density functional theory (DFT) method with machine learning (ML) methods. First, the DFT method with B3LYP/6-31++G**/SM8 is used to predict pKa, yielding a mean absolute error of 1.85 pKa units. Subsequently, such pKa values predicted from the DFT method are employed as one of 10 molecular descriptors for developing ML models trained on experimental data. Kernel Ridge Regression (KRR), Gaussian Process Regression, and Artificial Neural Network are optimized using three Pipelines: Pipeline 1 involving only hyperparameter optimization (HPO), Pipeline 2 involving HPO followed by a relative contribution analysis (RCA) and recursive feature elimination (RFE), and Pipeline 3 involving HPO followed by RCA and RFE on an expanded set of composite features. Finally, it is demonstrated that KRR with Pipeline 3 yields optimal pKa prediction at an MAE of 0.60 log units. This algorithm was then utilized to predict the pKa of 37 novel acids. The two most important features were determined to be the number of hydrogen atoms in the molecule and the degree of oxidation of the acid. The predicted pKa values were documented for future reference.

Tailored Design of Electrochemically Degradable Anthraquinone Functionality toward Organic Cathodes.

In efforts to design organic cathode materials for rechargeable batteries, a fundamental understanding of the redox properties of diverse non-carbon-based functionalities incorporated into 9,10-anthraquinone is lacking despite their potential impact. Herein, a preliminary investigation of the potential of anthraquinones with halogenated nitrogen-based functionalities reveals that the Li-triggered structural collapse observed in the early stage of discharging can be ascribed to the preference toward the strong Lewis acid-base interaction of N-Li-X (X = F or Cl) over the repulsive interaction of the electron-rich N-X bond. A further study of three solutions (i.e., substitution of NX2 with (i) BX2, (ii) NH2, and (iii) BH2) to the structural decomposition issue highlights four conclusive remarks. First, the replacement of N and/or X with electron-deficient atom(s), such as B and/or H, relieves the repulsive force on the N-X bond without the assistance of Li, and thus, no structural decomposition occurs. Second, the incorporation of BH2 is verified to be the most beneficial for improving the theoretical performance. Third, all the redox properties are better correlated with electron affinity and solvation energy than the electronegativity of functionality, implying that these key parameters cooperatively contribute to the electrochemical redox potential; additionally, solvation energy plays a crucial role in determining cathodic deactivation. Fourth, the improvement to the Li storage capability of anthraquinone using the third solution can primarily be ascribed to solvation energy remaining at a negative value even after the binding of more Li atoms than the other derivatives.

Distribution and Transport of CO2 in Hydrated Hyperbranched Poly(ethylenimine) Membranes: A Molecular Dynamics Simulation Approach.

Hyperbranched poly(ethylenimine) (HB-PEI) has been distinguished as a promising candidate for carbon dioxide (CO2) capture. In this study, we investigate the distribution and transport of CO2 molecules in a HB-PEI membrane at various hydration levels using molecular dynamics (MD) simulations. For this, model structures consisting of amorphous HB-PEI membranes with CO2 molecules are equilibrated at various hydration levels. Under dry conditions, the primary and secondary amines are highly associated with CO2, indicating that they would participate in CO2 capture via the carbamate formation mechanism. Under hydrated conditions, the pair correlations of CO2 with the primary and secondary amines are reduced. This result suggests that the carbamate formation mechanism is less prevalent compared to dry conditions, which is also supported by CO2 residence time analysis. However, in the presence of water molecules, it is found that the CO2 molecules can be associated with both amine groups and water molecules, which would enable the tertiary amine as well as the primary and secondary amines to capture CO2 molecules via the bicarbonate formation mechanism. Through our MD simulation results, the feasibilities of different CO2 capture pathways in HB-PEI membranes are demonstrated at the molecular level.