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. 2025 Sep 7;10(36):41492–41501. doi: 10.1021/acsomega.5c04952

Decoding the Structure–Property–Function Relationships in Covalent Organic Frameworks for Sustainable Battery Design

Tarek M Madkour †,‡,*, Hani M El-Kaderi ‡
PMCID: PMC12444515  PMID: 40978382

Abstract

Ion transport and storage in porous materials play a vital role in numerous energy storage and conversion technologies, such as batteries, capacitors, and fuel cells. In this study, molecular dynamics simulations are used to investigate the structure–property–function relationship of lithium and sodium ion transport and storage in highly porous and π-conjugated Aza-linked covalent organic frameworks (COFs). The simulations reveal that the diffusion coefficients of free lithium ions are significantly higher than those of free sodium ions across all of the COF structures, highlighting the influence of ion size on mobility in the absence of solvent molecules. The presence of nitrogen atoms in the imidazole and phenazine rings of the framework of BCOF-1, referred to throughout this article as Aza-COF, was found to significantly decrease the diffusion coefficients of the metal ions due to the significant electrostatic attraction between the ions and the lone pairs of the nitrogen atoms. Replacing the nitrogen atoms with carbon atoms led to increased diffusion coefficients, suggesting that the lone pairs and π-electrons of the frameworks play critical roles in ion binding. Pore decoration of the frameworks with glycol side chains dramatically reduced ion mobility due to increased electrostatic interactions. This indicates that the ether groups in these side chains create a more restrictive environment for ion movement. Overall, the simulations reveal that the electronic properties and chemical functionality of the pore walls, the free volume of the pores, and the solid-state packing of the COF structure significantly impact the ion transport and storage within the framework. This understanding paves the way for the rational design of new COF materials with tailored ion transport and storage properties for potential use as electrodes and solid-state electrolytes in sustainable batteries.

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1. Introduction

Owing to their unique structural and chemical features, covalent organic frameworks (COFs) have gained significant attention as promising materials for next-generation energy storage and conversion technologies such as rechargeable batteries, capacitors, and fuel cells. − COFs are crystalline porous organic polymers formed from linking organic building blocks through strong covalent bonds. , COFs offer a flexible platform for modifying their textural, chemical, and electronic properties to achieve high capacity, rapid charge–discharge rates, and a prolonged cycle life. The primary advantages of COFs in energy storage stem from their highly cross-linked structure that resists dissolution in electrolytes, their extensive π-conjugation that enables fast charge transfer, and their inherent porosity that promotes efficient ion transport. , This distinct combination makes COFs effective as electrode materials, addressing many of the challenges faced by traditional inorganic materials, small organic molecules, and organic polymers. Research on COFs has increasingly concentrated on enhancing their electrochemical performance by investigating various functional groups and architectures. − Nitrogen-rich COFs, especially those incorporating phenazine rings, have exhibited remarkable capacity and energy density, approaching the theoretical limits of organic materials. For instance, BCOF-1, referred to throughout this article as Aza-COF, synthesized via the polycondensation of hexaazatrinaphthalenehexamine (HATNHA) and terephthalaldehyde (TA), exhibited high specific capacity and good rate capability in sodium batteries (Figure ). The choice of these building blocks is driven by the need to increase the density of redox-active sites in the framework while enabling possible pore decoration with chemical functionalities to regulate ion transport. The latter synthetic approach has been explored in the field of COFs to advance ion transport and gas separation. As such, unraveling the role of pore chemical functionality in the aforementioned applications is vital for designing new functional COFs. In sodium batteries, the Aza-COF demonstrates high specific capacity, excellent rate capability, and strong cycling stability, rivaling the best-performing organic electrodes known to date. , This outstanding performance is further supported by the material’s high theoretical capacity of 603 mAh g–1 (Aza-COF-1) and 392 mAh g–1 (BCOF-1) attributed to the reversible reaction of the phenazine core with sodium ions. , Aza-COFs were also investigated for lithium, magnesium, and aluminum batteries and showed remarkable properties due to their textural and redox-active nature. The impressive results are the result of rapid surface-controlled redox processes and favorable diffusion rates of Li+, Na+, Mg2+, and Al3+ ions within the porous electrode.

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Chemical structures of Aza-COF modifications used in the molecular dynamics (MD) simulation.

Although significant attention has been given to COFs for use in lithium-ion batteries (LIBs), only a few studies have explored their potential in sodium batteries. − The interest in sodium-based batteries − (sodium metal and sodium-ion batteries) is due to the abundance of this metal and its low cost in comparison to lithium. Nevertheless, extensive research is still needed to advance sodium electrodes and electrolytes to make this battery technology commercially viable. The most promising COFs feature nitrogen-rich frameworks to boost the capacity and improve the poor rate performance of sodium batteries. Aza-COF, with its highly porous and π-conjugated structure, is expected to enable rapid sodium-ion diffusion and access to the redox-active aza sites, resulting in a high specific capacity, long cycling stability, and excellent rate capability. However, unlike the well-understood Li-ion storage mechanism in LIBs, − the storage mechanism for Na ions remains less clear. , Gaining insight into the chemical functionality of the nanopores within the COF structures and the solid-state packing of 2D sheets of COFs, the metal-ion diffusion rates are crucial for understanding the Na ion transport and storage in these COFs. This is especially important because of the larger size of sodium ions compared to lithium ions, which limits their use as common electrode materials in SIBs. Therefore, it is crucial to understand how the mechanism of Na ion transport through Aza-COFs in comparison to that of Li ions tailors the design of new materials with superior ion transport and storage properties.

In this study, we utilize different molecular simulation strategies to investigate the fundamental structure–property relationships of lithium- and sodium-loaded COFs. It builds on recent findings in this area to provide a clear understanding of the impact of porosity, electronic properties, and solid-state packing on the nature of lithium and sodium ion transport and storage in Aza-COFs and their derivatives. Based on this understanding, the work is extended to tailor-design new Aza-COFs with pore decoration done through the introduction of side-chain functionalization inside the nanopores of the nitrogen-rich skeletons to advance the use of COFs in energy storage and conversion applications.

2. Theoretical Methodology

All proposed COFs depicted in this work are expected to form 2D sheets that pack in an eclipsed fashion due to the favorable π–π stacking of the building blocks, which creates 1D pore channels through which Li and Na ions diffuse.

2.1. Molecular Simulation of the Unloaded and Li- and Na-Loaded COF Systems

Molecular models of various unloaded and Li- and Na-loaded COF systems were constructed and investigated using MD simulation modules in the Materials Studio simulation package available from Accelrys, Inc., UK. Lithium and sodium ion transport through Aza-COFs was investigated in terms of the diffusion coefficients of the metal ions calculated by evaluating the mean square displacements of the ions using MD simulations. To test the influence of the presence of nitrogen atoms and π-electrons on the diffusion coefficients of the ions, we envisaged hypothetical variations of the Aza-COF structure. The first modification was carried out by replacing the imidazole N atoms with C atoms and was given the code name Aza-COF-Im-C. This was followed by repeating the same step but for the phenazine N atoms, which was given the code name Aza-COF-Ph-C. Third, both imidazole and phenazine N atoms in the Aza-COF were replaced by C atoms while keeping the same hybridization of the replaced N atoms, with the code name Aza-COF-C-sp2, and finally converting all replaced atoms with sp3 C atoms, and the hypothetical structure was given the code name Aza-COF-C-sp3. In all of these hypothetical structures, referred to throughout the work as substituted Aza-COFs, the hydrogen atoms were adjusted to render accurate chemical formulas. The diffusion behavior for these structures was evaluated against that of the original Aza-COF to provide an explicit understanding of the structure–property relationship of COFs and the underlying parameters for the ion transport behavior.

In the second part of the MD simulations, three new structures of functionalized Aza-COFs were modeled. In each of these structures, each hydrogen atom of the N–H sites of the imidazole ring is replaced by a side chain consisting of four repeat units only. This side-chain length was chosen to not cause crowdedness of the pore cavities of the COF structures. The side chains were polyethylene (PE), poly­(ethylene oxide) (PEO), and poly­(propylene oxide) (PPO) structures. It is envisioned that the presence of the ether oxygen on the side chain influences the behavior of the metal ion transport and storage and, hence, the use of PEO side chains. Nevertheless, to test this hypothesis, PE was used to highlight the role of ether oxygen in this regard, and the use of PPO was done to test the influence of increased hydrophobicity on the metal-ion diffusion through the organic frameworks. The diffusion behavior for these structures was evaluated against that of the original Aza-COF to provide a well-understood structure–function relationship of COFs and aid in the tailoring of new and improved Aza-COF materials.

2.2. Construction of the Simulation Cells of Crystalline COF Systems

A triclinic crystal lattice with P1 symmetry was used to construct the individual simulation cells of the unloaded and Li- and Na-loaded Aza-COF structures. The cell dimensions were a = 37.7158 Å, b = 37.7156 Å, and c = 3.44240 Å with anglesα = 89.9066°, β = 89.9787°, and γ = 120.000°. All simulations were run using the COMPASS force field assigned charges and the Ewald summation method. The COMPASS force field was specifically chosen as it is a high-quality force field extensively parametrized and validated for accurately predicting the structural, conformational, and transport properties of organic polymers and crystals in condensed-phase environments. Its proven reliability for systems dominated by covalent and nonbonded electrostatic interactions makes it highly suitable for the COF structures investigated herein, which was validated against the experimental data estimated for the experimentally synthesized COFs. Following the construction, each simulation cell was geometrically optimized using the MS Forcite module until complete convergence. Once the simulation cells were minimized, they were all equilibrated using an equilibration scheme that consisted of a 1 ns NVT simulation run at room temperature, which is followed by a 5 ns NPT run at 1 atm. Following the equilibration procedures, MD runs using the NVT ensemble for 25 ns with a 1 fs time step at the temperature of 298 K were performed to produce the desired trajectories for further molecular analysis. Recent studies , indicated that performing the simulations for this length of time produces meaningful trajectories with reproducible results and allows for better sampling averages over the whole course of the simulation. Full trajectories were saved every 10,000 steps, and the last 2.5 ns of the trajectories were ultimately used for data analysis since they provide the most meaningful statistical representation of the system. During the simulation, the temperature was controlled using an Anderson thermostat.

2.3. Evaluation of the Mean Square Displacement and Self-Diffusion Coefficients

To enhance the sampling efficiency in calculating the self-diffusion coefficients of the various COF structures, the average value of four separate MD runs was considered. The diffusion coefficients of the metal ions were calculated by selecting the metal ions only and evaluating their mean square displacements. The diffusion coefficients of the ions through the COF pores were calculated using the following Einstein relation:

Do=16Nlimt→∞⁡ddt∑i=1N⟨[ri(t)−ri(0)]2⟩ 1

where r i is the position vector of atom i and N is the number of all atoms in the chain. The angular brackets denote averaging over all choices of time origin and all particles. The diffusion coefficients of the metal ions are thus considered as a portrayal of their transport through the pore channels of the COF systems.

2.4. Modeling of the Porosity of the COF Systems

The porosity of the COF structures plays an important role in the diffusion of metal ions. Changes in the electronic nature of the pore walls, the free volume of the pores, and/or the solid-state packing of the COF structures are expected to influence metal ion transport and storage. To examine the influence of these parameters on the COF porosity, trajectories generated from the MD simulations are used to calculate the free volume and the Connolly surface of the different COF structures. A Connolly surface is the van der Waals surface of the model that is accessible to a solvent molecule having a nonzero radius. The surface is generated by rolling a spherical probe of a specified radius over the van der Waals surface of the models.

2.5. Estimating the Binding Energy of the Metal Ions to the COF Structures

It is obvious from the previous discussion that the binding energy (ΔE) between the COF structures and the metal ions plays an important role in controlling the transport and storage characteristics of these ions. This can be evaluated by considering the cohesive energies of the metal ions and the COF structures from the molecular simulations according to the following equation: ,

ΔE=ϕ1CED1+ϕ2CED2−(ϕ1+ϕ2)CED12 2

where ϕi refers to the mole fraction of component i and CED i refers to the cohesive energy density of system i, defined as the energy required to break all the intermolecular physical links in a unit volume, and is given by

CED=ΔE/V 3

which can be estimated readily from the simulation data by calculating the energy of the parent COF structure in bulk with the periodic boundary conditions implemented, E bulk, and the energy of the isolated structure in a vacuum, E vac, according to

CED=(Evac−Ebulk)/V 4

3. Results and Discussion

Trajectories produced from the MD simulation were analyzed and used to predict the structure–property–function relationships of Li- and Na-loaded COF systems. On the first inspection of the trajectories, it was clear that while some metal ions are attracted to the N atoms of the imidazole and phenazine centers of the COF structure as a result of the attraction forces between the positive charge on the metal ions and the lone pairs of the N atoms, others escaped this electronic trap and were free to move through the 1D pore channels of the COF structure. This has effectively created two classes of metal ions referred to throughout the article as bound ions and free ions, respectively, and were both followed separately during the analysis of the mean square displacements and diffusion coefficients of the metal ions.

3.1. Impact of the Electronic Properties of the N-Rich Microstructure on Ion Transport and Storage

To fully understand the impact of the COF microstructure on ion mobility, several hypothetical variations of the original Aza-COF were investigated, as described earlier. Figure shows the mean square displacements of free Li ions (a) and bound Li ions (b) through the substituted Aza-COFs, while Figure shows those for the Na ions.

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Mean square displacements of Li ions through substituted Aza-COFs: (a) free Li ions and (b) bound Li ions. The secondary axis in (b) is for the Aza-COF-C-sp3 showing the major jump in its displacement values.

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Mean square displacements of Na ions through substituted Aza-COFs: (a) free Na ions and (b) bound Na ions.

The diffusion coefficients calculated from the Einstein relation (eq ) for these systems are shown in Figures and for free and bound ions, respectively, for both metal ions. It is obvious from the figures that there is a clear relationship between the type of substitution on the Aza-COF framework and the diffusion coefficients of the ions. Free Li ions exhibit higher diffusion coefficients than free Na ions across all materials, indicating Li’s greater mobility stemming from its small size when compared to that of the Na ions. However, the opposite was true in the case of bound metal ions, indicating greater binding energies between the bound Li ions and the COF resulting from a greater effective nuclear charge of the Li nuclei.

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Diffusion coefficients of free Li and Na ions through substituted Aza-COFs.

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Diffusion coefficients of bound Li and Na ions through substituted Aza-COFs.

Among the modified Aza-COF structures, the replacement of either the imidazole or phenazine N atoms with sp2-hybridized C atoms (Aza-COF-Im-C and Aza-COF-Ph-C, respectively) resulted in an increase of the diffusion coefficients of the ions, indicating less electrostatic attraction between the ions and the COF structures due to the absence of N atom lone pairs. Replacement of all N atoms in the COF structures with sp2-hydridized C atoms (Aza-COF-C-sp2) or sp3-hybridized C atoms (Aza-COF-C-sp3) resulted, as expected, in greater diffusion coefficients of the metal ions. So much so that in the case of Aza-COF-C-sp3, the lack of lone pairs and π-electrons has resulted in a massive increase in the slope of the mean square displacements, Figure b, and the diffusion coefficients, Figure , of the metal ions, particularly for Li, through Aza-COF-C-sp3. The pronounced difference between the diffusion of free and bound ions in both figures highlights the strong impact of the ion interaction with the COF structure and the nature of the functional groups on the transport and storage of the metal ions.

The excellent rate capability performance of COFs could thus be attributed to the high surface area, high electronic conductivity, and the honeycomb-like porous channels of Aza-COF. Charge/discharge hysteresis was observed at 0.1C because of depletion of the Na ions within the pores in the inner regions caused by the lower diffusion rate compared to that in the outermost areas of the Aza-COF framework, which would restrict the accessibility of the Na ions to the aza-active sites.

3.2. Impact of Pore Decoration on Metal Ion Transport and Storage

According to literature, , pore modification of imidazole-linked COFs has been carried out by imidazole ring deprotonation with strong bases like NaH and nBuLi, followed by treatment with bromo-alkanes in THF solvent. The one-step N-alkylation reaction enables pore decoration with various functional groups without compromising the framework crystallinity or porosity. To predict the impact of pore decoration via ether side chains on ion transport and storage, newly envisioned COF structures were functionalized with PE, PEO, and PPO side chains, as described earlier. The new COF structures Aza-COF-PE, Aza-COF-PEO, and Aza-COF-PPO were simulated and compared to the original Aza-COF referred to as Aza-COF for simplicity.

Figures and depict the mean square displacements of the various functionalized COF structures loaded with free and bound Li and Na ions.

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Mean square displacements of Li ions through functionalized Aza-COFs: (a) free Li ions and (b) bound Li ions. The displacement values for PEO- and PPO-functionalized COFs are quite low to be observed.

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Mean square displacements of Na ions through functionalized Aza-COFs: (a) free Na ions and (b) bound Na ions. The displacement values for PEO- and PPO-functionalized COFs are quite low to be observed.

Diffusion coefficients evaluated from the figures for the various systems are shown in Table . It is clear from the figures and the table that the metal ions show significantly lower diffusion coefficients for bound ions compared to the free ones of more than 4 orders of magnitude, suggesting that metal ions trapped by the electrostatic field of the lone pairs and π-electrons residing on the pore walls are drastically restricted to the frameworks.

1. Diffusion Coefficients of Free and Bound Li and Na Ions through Functionalized Aza-COFs.

  Li ions
 Na ions
system D 0 (m2/s) free ions D 0 (m2/s) bound ions D 0 (m2/s) free ions D 0 (m2/s) bound ions
Aza-COF 5.24 × 10–2 1.61 × 10–6 1.51 × 10–2 4.73 × 10–6
Aza-COF-PE 7.96 × 10–2 1.22 × 10–6 2.64 × 10–2 4.24 × 10–6
Aza-COF-PEO 7.17 × 10–10 9.28 × 10–13 2.21 × 10–8 5.06 × 10–10
Aza-COF-PPO 2.90 × 10–9 3.66 × 10–12 7.09 × 10–10 3.44 × 10–12
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In Aza-COF-PE, functionalization enhanced the mobility of free Li ions, as seen by the increased diffusion coefficient (7.96 × 10–2 m2/s), while the diffusion of bound Li ions slightly decreases (1.22 × 10–6 m2/s), reflecting a subtle change in the binding environment. It should be mentioned here that while diffusion rates are calculated experimentally through an electrolyte medium, theoretically, these were calculated in a vacuum, hence the observed difference between the theoretical and experimental values. This was done to cut down on expensive calculation times beyond the computational capabilities of many CPUs. However, it should be noted that while the values may be different between modeling and experiment, the predicted trends match those determined experimentally, as the objective of the research here is to model the impact of structural and morphological modifications on the properties of the systems under study. Na ions in Aza-COF-PE also exhibit higher free ion mobility (2.64 × 10–2 m2/s), while the bound ion diffusion coefficient (4.24 × 10–6 m2/s) remains in a similar range to that of the original COF structure, suggesting that the functional group affects the free state more than the bound state. The Aza-COF-PEO introduces a significant drop in ion diffusion, with Li ions showing extremely low free ion diffusion (7.17 × 10–10 m2/s) and bound ion diffusion (9.28 × 10–13 m2/s), suggesting that PEO functionalization heavily restricts the metal ion mobility due to stronger electrostatic interactions and denser packing within the framework. Na ions in Aza-COF-PEO showed slightly higher mobility than Li ions, with free ion diffusion at 2.21 × 10–8 m2/s and bound ion diffusion at 5.06 × 10–10 m2/s, although both are still significantly lower than in the case of Aza-COF-PE or the original COF structure. Aza-COF-PPO exhibits a similar trend, where both Li and Na ions experience very limited mobility. The free diffusion coefficient for Li ions in Aza-COF-PPO is 2.90 × 10–9 m2/s, with bound diffusion at 3.66 × 10–12 m2/s, indicating that this functionalization also significantly impedes ion movement. Na ions in Aza-COF-PPO display slightly higher mobility than Li ions with free diffusion at 7.09 × 10–10 m2/s and bound diffusion at 3.44 × 10–12 m2/s. Overall, these results suggest that functionalization, particularly with PEO and PPO groups, dramatically reduces ion diffusion, especially in the bound state, which may result from increased interaction with the ether oxygen of the side chains and the reduced pore cavity.

Thus far, the impact of the COF structures on the metal ion mobility has been studied; however, it will also be interesting to evaluate the influence of loading different metal ions into the different COF structures on the self-diffusion of the COFs themselves. Table lists the self-diffusion coefficients of the various functionalized Aza-COFs in the presence of no, Li, or Na ions.

2. Self-Diffusion Coefficients of Various Functionalized Aza-COFs Loaded with No, Li, or Na Ions.

  no ions Li ions Na ions
system D 0 (m2/s) D 0 (m2/s) D 0 (m2/s)
Aza-COF 2.29 × 10–12 1.61 × 10–6 4.73 × 10–6
Aza-COF-PE 6.45 × 10–13 1.23 × 10–6 4.25 × 10–6
Aza-COF-PEO 3.61 × 10–13 3.19 × 10–13 3.06 × 10–12
Aza-COF-PPO 2.31 × 10–13 2.21 × 10–13 2.14 × 10–13
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When Li or Na ions are introduced, the self-diffusion coefficients of the Aza-COF and Aza-COF-PE structures significantly increase, reflecting the increased mobility of the framework as a result of the electrostatic interactions between the COF and ions. However, the presence of PEO and PPO side chains did not influence the framework self-diffusion coefficients, indicating that the ether side chains create a highly restrictive environment not only for the metal-ion diffusion but also for the pore wall mobility resulting from the strong interactions between the ions and the framework.

Understanding the structure–property–function relationship is crucial for designing COF materials for applications in which controlled ion diffusion is necessary, such as in ion transport, energy storage, or separation technologies. Furthermore, it highlights the importance of using modeling simulation techniques in understanding and designing new COF structures for specific applications.

3.3. Impact of the Porosity and Solid-State Packing on the Ion Transport and Storage

To investigate the impact of solid-state packing on metal ion transport and storage, MD techniques were used to construct both crystalline and amorphous simulation cells for the various COF systems. As a representation of the simulated cells, Figure shows the snapshots of the molecular simulations of crystalline and amorphous PPO-functionalized Aza-COF loaded with Li and Na ions. Since the porosity of COFs provides a more extensive pore–electrolyte interface and, thus, higher metal ion transfer, it is prudent to investigate the porosity parameter of the simulated cells, as illustrated in Figure .

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Snapshots of the molecular simulations of (a) crystalline PPO-functionalized Aza-COF loaded with Li ions, (b) amorphous PPO-functionalized Aza-COF loaded with Li ions, (c) crystalline PPO-functionalized Aza-COF loaded with Na ions, and (d) amorphous PPO-functionalized Aza-COF loaded with Na ions.

Table provides a detailed comparison of the porosity parameters such as the free volume and Connolly surface-to-volume ratio for various crystalline and amorphous functionalized Aza-COFs decorated with PE, PEO, and PPO side chains. For Aza-COF, the crystalline structure exhibits a high free volume with 71.47% in the case of Li-ion loading and 70.04% in the case of Na-ion loading, both having a surface/volume ratio of 0.13. However, in the amorphous COF, the free volume drops significantly to 34.91% for Li and 39.64% for Na loading, while the surface/volume ratio increases to around 0.32.

3. Porosity Parameters of Crystalline and Amorphous Functionalized Aza-COFs.

    Li ions
 Na ions
system   free volume (%) surface/volume ratio free volume (%) surface/volume ratio
Aza-COF crystalline 71.47 0.13 70.04 0.13
  amorphous 34.91 0.32 39.64 0.31
Aza-COF-PE crystalline 54.57 0.18 52.44 0.17
  amorphous 40.55 0.41 43.51 0.44
Aza-COF-PEO crystalline 47.73 0.18 45.86 0.17
  amorphous 24.93 0.36 32.79 0.32
Aza-COF-PPO crystalline 46.27 0.19 45.49 0.19
  amorphous 22.12 0.35 25.27 0.31
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It can be concluded that the shift from amorphous to crystalline morphology results in a more open structure with higher porosity and a lower packing density, reflecting an increase in the surface area that can enhance ion accessibility. Similarly, for COF-PE, the crystalline structure shows a free volume of 54.57% for Li loading and 52.44% for Na loading with surface/volume ratios of 0.18 and 0.17, respectively. In contrast, the amorphous COF-PE has a lower free volume (40.55% for Li and 43.51% for Na) but a significantly higher surface/volume ratio, reaching 0.41 and 0.44, respectively, indicating that the amorphous structure creates a less porous framework compared to its crystalline counterpart. The trend continues with Aza-COF-PEO and Aza-COF-PPO. Overall, the results suggest that while the crystalline forms of COFs have open structures and low packing densities, the amorphous forms present a denser structure, especially when functionalized with PE, PEO, or PPO side chains. The impact of crystallinity on the ion transport indicates that crystalline Aza-COFs exhibit a remarkable enhancement in ion transport as compared to the amorphous analogs due to the facilitated diffusion of metal ions along the 1D channels. These studies infer that the solid-state ordering of COFs is vital for rapid ion diffusion and transport. These findings highlight the significant impact of the structural state and functionalization on the COF porosity. It is thus anticipated that the typically ion diffusion-limited kinetics can be enhanced by providing shorter paths for the metal ions to travel and better accessibility to the redox-active sites of the frameworks. As a result, the electrochemical process converts from an ion diffusion-controlled process for the pristine COF to a charge-transfer-dominated one for the functionalized materials.

Interestingly, the binding energies of Li and Na ions with various functionalized Aza-COFs were evaluated and are shown in Figure as a function of metal ion mole fraction. The data in the figure show that different functionalizations of Aza-COFs did not affect the binding affinity of the metal ions. However, the increase in the ion loading enhanced this binding between the metal ions and the COF structures. Interestingly, Li ions showed a stronger binding with the COFs than Na ions, which coincides with conclusions made from the evaluation of the ion diffusion coefficients, Figures and . Stronger binding leads to a lower mobility of the free ions, as they are more likely to interact with the COF structure, thus hindering their diffusion. Conversely, Na ions, with weaker binding, diffuse more freely.

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Binding energies of Li and Na ions with various functionalized Aza-COFs at different mole fraction loadings.

4. Conclusion

The molecular modeling study provides critical insights into the impact of structural modifications and functionalization on the ion transport behavior of Aza-COFs, highlighting their potential for energy storage applications. The substitution of nitrogen atoms within the COF framework enhances lithium-ion diffusion due to reduced electrostatic attraction, emphasizing the significance of the electronic properties of the framework. Additionally, the porous architecture and π-conjugated systems play vital roles in facilitating ion transport through 1D pore channels. Functionalization of COF pores, particularly with poly­(ethylene oxide) (PEO) and poly­(propylene oxide) (PPO) side chains, has a profound effect on ion mobility. While the hydrophobic polyethylene (PE) side chains enhance free ion diffusion, hydrophilic PEO and PPO restrict it, indicating the importance of side-chain chemistry in influencing ion transport. The MD simulations reveal that solid-state packing significantly affects ion transport, with crystalline structures exhibiting higher porosity and faster ion diffusion than amorphous ones. These findings emphasize the need for a balanced approach to functionalization and underscore the relevance of the structure–property–function relationship in optimizing COF materials. Crucially, this study provides a theoretical roadmap to guide the rational design of next-generation materials. Future research should focus on the experimental synthesis and characterization of COFs featuring the most promising side-chain functionalizations identified here, such as PEO and PPO, to validate these computational predictions and assess their practical performance. This targeted experimental work, guided by our findings, will be essential for advancing the development of COF-based energy storage devices. This knowledge paves the way for designing tailored COFs for specific applications in Li- and Na-ion batteries, supercapacitors, and fuel cells, unlocking their full potential in sustainable energy technologies.

Supplementary Material

ao5c04952_si_001.xlsx (87.2KB, xlsx)

Acknowledgments

T.M.M. would like to thank the American University in Cairo for supporting the sabbatical leave, which made this work possible. H.M.K. acknowledges the support provided by the National Academies of Sciences, Engineering, and Medicine (National Academies) under award number SCON-10000859.

The data and experimental information utilized to create this manuscript, as well as the information required to replicate the reported work, are all available in the various sections of this manuscript.

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.5c04952.

  • The coordinates for all COF chemical structures simulated throughout the research work depicted in this manuscript (XLSX)

#.

Functional Materials Group, Gulf University for Science and Technology, Hawally 32093, Kuwait

Madkour, T.M.: Conceptualization; data curation and interpretation; funding acquisition; manuscript writing. El-Kaderi, H.: Conceptualization; data interpretation; paper writing and revision; project administration.

The authors declare no competing financial interest.

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ao5c04952_si_001.xlsx (87.2KB, xlsx)

Data Availability Statement

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