Dynamics Simulations Of Molecules Research Articles

Insight into the Mechanism of d-Glucose Accelerated Exchange in GLUT1 from Molecular Dynamics Simulations.

Transmembrane glucose transport, facilitated by glucose transporters (GLUTs), is commonly understood through the simple mobile carrier model (SMCM), which suggests that the central binding site alternates exposure between the inside and outside of the cell, facilitating glucose exchange. An alternative "multisite model" posits that glucose transport is a stochastic diffusion process between ligand-operated gates within the transporter's central channel. This study aims to test these models by conducting atomistic molecular dynamics simulations of multiple glucose molecules docked along the central cleft of GLUT1 at temperatures both above and below the lipid bilayer melting point. Our results show that glucose exchanges occur on a nanosecond time-scale as glucopyranose rings slide past each other within the channel cavities, with minimal protein conformational movement. While bilayer gelation slows net glucose transit, the frequency of positional exchanges remains consistent across both temperatures. This supports the observation that glucose exchange at 0 °C is much faster than net flux, aligning with experimental data that show approximately 100 times the rate of exchange flux relative to net flux at 0 °C compared to 37 °C.

Validating Structural Predictions of Conjugated Macromolecules in Espaloma-Enabled Reproducible Workflows.

We incorporated Espaloma forcefield parameterization into MoSDeF tools for performing molecular dynamics simulations of organic molecules with HOOMD-Blue. We compared equilibrium morphologies predicted for perylene and poly-3-hexylthiophene (P3HT) with the ESP-UA forcefield in the present work against prior work using the OPLS-UA forcefield. We found that, after resolving the chemical ambiguities in molecular topologies, ESP-UA is similar to GAFF. We observed the clustering/melting phase behavior to be similar between ESP-UA and OPLS-UA, but the base energy unit of OPLS-UA was found to better connect to experimentally measured transition temperatures. Short-range ordering measured by radial distribution functions was found to be essentially identical between the two forcefields, and the long-range ordering measured by grazing incidence X-ray scattering was qualitatively similar, with ESP-UA matching experiments better than OPLS-UA. We concluded that Espaloma offers promise in the automated screening of molecules that are from more complex chemical spaces.

Assessing synergistic effects: Ion-inducing and intermolecular interactions behind the aggregation and migration behaviors of crude molecules

The aggregation and adsorption of asphalt and resin molecules in the reservoir or pipeline can lead to the blockage of oil extraction channels, which significantly reduces the anticipated oil production. However, the micro-mechanisms behind the aggregating and migrating behaviors of crude molecules still remain poorly understood. In this work, we considered eight types of asphalt and resin molecules as models of crude oil and then built two systems to simulate the aggregation and migration processes, respectively, using molecule dynamics (MD) simulations. In the case of the aggregation process, our findings demonstrated that the aggregation process of crude molecules is directly triggered by metal ions, which are capable of attracting crude molecules containing acidic groups and heteroatoms to form aggregates. And the stacking structures in the forms of face-to-face and edgy-to-face between crude molecules were found to further lead to the formation of larger aggregates. In the case of the migration process, it was discovered that a few ions attached to the reservoir surfaces are able to induce polar molecules or clusters moving toward the surfaces, resulting in the adsorption behaviors of monomers and multimers. Besides, through a sequence of intermolecular interactions, it was found that the pre-aggregated clusters far away from the reservoir surfaces continued to migrate toward the rock surfaces. In conclusion, this work sheds light on the synergistic effects of ion-inducing and intermolecular interactions behind the aggregation and migration behaviors of crude molecules.

Modulating Coarse-Grained Dynamics by Perturbing Free Energy Landscapes.

We introduce an approach to describe the long-time dynamics of multiatomic molecules by modulating the free energy landscape (FEL) to capture dominant features of the energy-barrier crossing dynamics of the all-atom (AA) system. Notably, we establish that the self-diffusion coefficient of coarse-grained (CG) systems can be accurately delineated by enhancing conservative force fields with high-frequency perturbations. Using theoretical arguments, we show that these perturbations do not alter the lower-order distribution functions, thereby preserving the structure of the AA system after coarse-graining. We demonstrate the utility of this approach using molecular dynamics simulations of simple molecules in bulk with distinct dynamical characteristics with and without time scale separations as well as for inhomogeneous systems where a fluid is confined in a slit-like nanochannel. Additionally, we also apply our approach to more powerful many-body potentials optimized by using machine learning (ML).

Hydrogen purification via hydrate-based methods: Insights into H2-CO2-CO hydrate structures, thermodynamics, and kinetics

Hydrate-based H2 purification is promising for removing impurities owing to the cage-like structures formed by water molecules. Understanding the competition mechanism of multicomponent gas molecule in hydrate is critical for improving gas purification efficiency. This study investigated the hydrate structure, thermodynamics, and kinetics of ternary gas mixture (H2–CO2–CO) from natural gas reforming products. The results identified H2–CO2–CO hydrate as type sI and determined the lattice parameters using X-ray diffraction. Raman spectroscopy results confirmed the presence of H2, CO2, and CO gas molecules in the hydrate phase. Increasing pressure, compared to cooling, enhanced CO2 content in hydrate phase. The phase equilibrium conditions and average hydrate dissociation enthalpy (53.47 J/g) were determined using a high-pressure microcalorimeter. Gas chromatography identified that the content of CO2 in the hydrate was the highest, followed by H2, and CO was the least abundant. The molecule dynamics simulation results show CO2 molecule numbers reflected trends in 51262 cages, H2 numbers correlated with changes in 512 cages, while CO numbers showed insignificant variation. Under the gas composition studied, the ability of gas molecules to be incorporated within hydrates decreases in the following order: CO2, H2, and CO.

Stability and conformation of DNA-hairpin in cylindrical confinement

We conducted atomistic Molecular Dynamics (MD) simulations of DNA-Hairpin molecules encapsulated within Single-Walled Carbon Nanotubes (SWCNTs) at a temperature of 300 K. Our investigation revealed that the structural integrity of the DNA-Hairpin can be maintained within SWCNTs, provided that the diameter of the SWCNT exceeds a critical threshold value. Conversely, when the SWCNT diameter falls below this critical threshold, the DNA-Hairpin undergoes denaturation, even at a temperature of 300 K. The DNA-Hairpin model we employed consisted of a 12-base pair stem and a 3-base loop, and we studied various SWCNTs with different diameters. Our analyses identified a critical SWCNT diameter of 3.39 nm at 300 K. Examination of key structural features, such as hydrogen bonds (H-bonds), van der Waals (vdW) interactions, and other inter-base interactions, demonstrated a significant reduction in the number of H-bonds, vdW energy, and electrostatic energies among the DNA hairpin's constituent bases when confined within narrower SWCNTs (with diameters of 2.84 nm and 3.25 nm). However, it was observed that the increased interaction energy between the DNA-Hairpin and the inner surface of narrower SWCNTs promoted the denaturation of the DNA-Hairpin. In-depth analysis of electrostatic mapping and hydration status further revealed that the DNA-Hairpin experienced inadequate hydration and non-uniform distribution of counter ions within SWCNTs having diameters below the critical value of 3.39 nm. Our inference is that the inappropriate hydration of counter ions, along with their non-uniform spatial distribution around the DNA hairpin, contributes to the denaturation of the molecule within SWCNTs of smaller diameters. For DNA-Hairpin molecules that remained undenatured within SWCNTs, we investigated their mechanical properties, particularly the elastic properties. Our findings demonstrated an increase in the persistence length of the DNA-Hairpin with increasing SWCNT diameter. Additionally, the stretch modulus and torsional stiffness of the DNA-Hairpin were observed to increase as a function of SWCNT diameter, indicating that confinement within SWCNTs enhances the mechanical flexibility of the DNA-Hairpin.

Laser Irradiation Induced Electronic Structure Modulation of the Palladium-Based Nanosheets for Efficient Electrocatalysts.

Palladium nanosheets (Pd NSs) are widely used as electrocatalysts due to their high atomic utilization efficiency, and long-term stability. Here, the electronic structure modulation of the Pd NSs is realized by a femtosecond laser irradiation strategy. Experimental results indicate that laser irradiation induces the variation in the atomic structures and the macrostrain effects in the Pd NSs. The electronic structure of Pd NSs is modulated by laser irradiation through the balancing between Au-Pd charge transfer and the macros-strain effects. Finite element analysis (FEA) indicates that the lattice of the nanostructures undergoes fast heating and cooling during laser irradiation. The structural evolution mechanism is disclosed by a combined FEA and molecule dynamics (MD) simulation. These results coincide well with the experimental results. The L-AuPd NSs exhibit excellent mass activity and specific activity of 7.44 A mg-1 Pd and 18.70mA cm-2 toward ethanol oxidation reaction (EOR), 4.3 and 4.4 times higher than the commercial Pd/C. The 2500-cycle accelerated durability (ADT) test confirms the outstanding catalytic stability of the L-AuPd NSs. Density functional theory (DFT) calculations reveal the catalytic mechanism. This unique strategy provides a new pathway to design the ultrathin nanosheet-based materials with excellent performance.

Nano-twinned silicon in Al-Si alloys for high wear-resistance

Wear-failure is the most common damage for power transmission components in the field of engineering materials, constituting approximately one-fourth in service loss. The development of high wear-resistant Al alloys plays a crucial role in reducing energy demand and weight, and then attributes to the achievement of dual-carbon target. Here we report a novel strategy to develop outstanding wear-resistant (the coefficient of friction of 0.31) Al-10 wt%Si alloys at room temperature, based on the formation of multiple parallel {111} twins and hierarchical {111}-{111} double twins by a route of combining ultrahigh pressure solid solution and electropulsing assisted aging (HPEP), which overwhelms all values of Al alloys, even Ti alloys and high entropy alloys reported so far. The microstructure, formation process and wear-resistant mechanism of nano-twinned Si have been clarified by transmission electron microscopy observations, molecule dynamics simulations and the first principles calculations. It demonstrates that the interactive nano-twinned Si structures are mainly introduced through twin-twin collision or the phase/matrix interface prohibition of twin motion, which are effective to restrain atom separation in contrast to eutectic Si perfect crystal, resulting in homogeneous wear-loss and long operation life. Those new results provide insights towards designing wear-resistant materials with high mechanical properties.

Multi-GPU RI-HF Energies and Analytic Gradients─Toward High-Throughput Ab Initio Molecular Dynamics.

This article presents an optimized algorithm and implementation for calculating resolution-of-the-identity Hartree-Fock (RI-HF) energies and analytic gradients using multiple graphics processing units (GPUs). The algorithm is especially designed for high throughput ab initio molecular dynamics simulations of small and medium size molecules (10-100 atoms). Key innovations of this work include the exploitation of multi-GPU parallelism and a workload balancing scheme that efficiently distributes computational tasks among GPUs. Our implementation also employs techniques for symmetry utilization, integral screening, and leveraging sparsity to optimize memory usage. Computational results show that the implementation achieves significant performance improvements, including over 3 × speedups in single GPU AIMD throughput compared to previous GPU-accelerated RI-HF and traditional HF methods. Furthermore, utilizing multiple GPUs can provide superlinear speedup when the additional aggregate GPU memory allows for the storage of decompressed three-center integrals.

Deep learning model for precise prediction and design of low-melting point phthalonitrile monomers

Phthalonitrile is a widely applied resin due to its outstanding high-temperature resistance and versatility. However, the high melting point of its monomer limits its range of applications. Due to the scarcity of data, traditional deep learning models face challenges in accurately predicting the properties of phthalonitrile monomers. In this work, we propose a novel deep learning model based on techniques such as molecular similarity weighting, pre-training parameter averaging, and hybrid neural networks to address the issue of data sparsity. Our model exhibits exceptionally high accuracy for predicting the melting point of phthalonitrile monomers, e.g., the mean absolute error on the experimental dataset is 15.3 °C. To explore novel low-melting monomers, we develop a high-throughput molecule generation software and use our model to filter the virtual molecules, and ultimately obtain candidates that meet low-melting and synthesizability requirements. Moreover, we have successfully synthesized one candidate molecule, and the high consistency between our predictions and experimental measurements again demonstrates our model’s accuracy. Meanwhile, molecule dynamic simulations are conducted to provide explanations for the reduction in melting point. This study not only provides guidance for designing phthalonitrile monomers, but also proposes an innovative approach for exploring of new materials under conditions of sparse data.

Structure and interactions of CO2 with reline (a 1:2 choline chloride – Urea mixture) according to quantum chemical calculations and molecular dynamics simulation

Quantum chemical DFT calculations [B3LYP+GD3/6-311++g(2d,2p)] of the structure and interactions in various complexes of CO2 molecule with a choline cation, a chloride anion, urea molecules, a choline chloride ion pair and a 1:2 choline chloride – urea complex were carried out. The contributions of Coulomb and van der Waals interactions were calculated. The QTAIM method was used to evaluate the strength of various bonds. A molecular dynamics simulation of CO2 molecules in reline in the NPT ensemble (1 atm, 298 K) was also carried out. The radial distribution functions of the particle centers of mass, local mole fraction functions, spatial distribution functions, and density profiles were calculated. Stronger interactions, compared to the other DES components, were observed in case of the chloride anion and the CO2 molecule according to the DFT calculations. However, in the system, stronger interactions were observed between the chloride anion and the system components, namely NHCl and OHCl hydrogen bonds. This made the chloride anion inaccessible and unable to interact with the CO2 molecule, according to the MD simulation results. Additionally, the presence of a fairly extensive surface layer containing DES and CO2 molecules was shown.

STORMM: Structure and topology replica molecular mechanics for chemical simulations.

The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, vectorized central processor units and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM is built to run thousands of independent molecular mechanical calculations on a single GPU with novel implementations that tune numerical precision, mathematical operations, and scarce on-chip memory resources to optimize throughput. The libraries are built around accessible classes with detailed documentation, supporting fine-grained parallelism and algorithm development as well as copying or swapping groups of systems on and off of the GPU. A primary intention of the STORMM libraries is to provide developers of atomic simulation methods with access to a high-performance molecular mechanics engine with extensive facilities to prototype and develop bespoke tools aimed toward drug discovery applications. In its present state, STORMM delivers molecular dynamics simulations of small molecules and small proteins in implicit solvent with tens to hundreds of times the throughput of conventional codes. The engineering paradigm transforms two of the most memory bandwidth-intensive aspects of condensed-phase dynamics, particle-mesh mapping, and valence interactions, into compute-bound problems for several times the scalability of existing programs. Numerical methods for compressing and streamlining the information present in stored coordinates and lookup tables are also presented, delivering improved accuracy over methods implemented in other molecular dynamics engines. The open-source code is released under the MIT license.

Atomistic Molecular Dynamics Simulations of ABA-Type Polymer Peptide Conjugates: Insights into Supramolecular Structures and their Circular Dichroism Spectra.

A combination of atomistic molecular dynamics (aMD) simulations and circular dichroism (CD) analysis is used to explore supramolecular structures of amphiphilic ABA-type triblock polymer peptide conjugates (PPC). Using the example of a recently introduced PPC with pH- and temperature responsive self-assembling behavior [Otter etal., Macromolecular Rapid Communications 2018, 39, 1800459], this study shows how molecular dynamics simulations of simplified fragment molecules can add crucial information to CD data, which helps to correctly identify the self-assembled structures and monitor the folding/unfolding pathways of the molecules. The findings offer insights into the nature of structural transitions induced by external stimuli, thus contributing to the understanding of the connection of microscopic structures with macroscopicproperties.

Fe-NiO/MoO2 and in-situ reconstructed Fe, Mo-NiOOH with enhanced negatively charges of oxygen atoms on the surface for salinity tolerance seawater splitting

Seawater electrolysis is a promising technique for H2 production on a large scale. However, the electrocatalytic activity and stability will be deteriorated as the increase of salt concentrations which happened in the seawater splitting. Herein, through the electrodeposition and rapid Joule heating method, the Fe-NiO/MoO2 heterostructure is designed as a highly active bifunctional electrocatalyst. During the OER possess, Fe-NiO/MoO2 is reconstructed to the Fe, Mo-NiOOH with Fe and Mo co-doping. Based on the theoretical analysis, more electrons were transferred to the O atoms on the surface of Fe, Mo-NiOOH, thereby forming a more negatively charged surface. Moreover, that surface is found to repel Cl− ions while enriching H2O molecules to form a thin water layer on Fe, Mo-NiOOH surface based on molecule dynamics (MD) simulation, thereby improving the anti-corrosion capacity of Fe, Mo-NiOOH. The reconstructed Fe, Mo-NiOOH achieved an overpotential of 399 mV at 1000 mA cm−2 in alkaline seawater, and the increase of overpotential for Fe, Mo-NiOOH was about 0.02 V at 500 mA cm−2 from 0 M to 3 M NaCl in 1 M KOH electrolyte. For the HER, Fe-NiO/MoO2 achieved an overpotential of 169 mV and 417 mV at 100 and 1000 mA cm−2 in alkaline seawater, respectively, and the increase of overpotential for Fe-NiO/MoO2 was about 0 mV at 500 mA cm−2 from 0 M to 3 M NaCl in 1 M KOH electrolyte. This work sheds fresh light into the development of efficient electrocatalysts for salinity tolerance seawater splitting.

Sequence-Guided Redesign of an Omega-Transaminase from Bacillus megaterium for the Asymmetric Synthesis of Chiral Amines.

ω-Transaminases (ω-TAs) are attractive biocatalysts asymmetrically catalyzing ketones to chiral amines. However, poor non-native catalytic activity and substrate promiscuity severely hamper its wide application in industrial production. Protein engineering efforts have generally focused on reshaping the substrate-binding pockets of ω-TAs. However, hotspots around the substrate tunnel as well as distant sites outside the pockets may also affect its activity. In this study, the ω-TA from Bacillus megaterium (BmeTA) was selected for engineering. The tunnel mutation Y164F synergy with distant mutation A245T which was acquired through a multiple sequence alignment showed improved soluble expression, a 3.7-fold higher specific activity and a 19.9-fold longer half-life at 45 °C. Molecule Dynamics simulation explains the mechanism of improved catalytic activity, enhanced thermostability and improved soluble expression of BmeTAY164F/A245T(2 M). Finally, the resting cells of 2 M were used for biocatalytic processes. 450 mM of S-methoxyisopropylamine (S-MOIPA) was obtained with an ee value of 97.3 % and a conversion rate of 90 %, laying the foundation for its industrial production. Mutant 2 M was also found to be more advantageous in catalyzing the transamination of various ketones. These results demonstrated that sites that are far away from the active center also play an important role in the redesign of ω-TAs.

Blocking Interfacial Proton Transport via Self‐Assembled Monolayer for Hydrogen Evolution‐Free Zinc Batteries

AbstractAqueous Zn‐ion batteries (ZIBs) are promising next‐generation energy storage devices, yet suffer from the issues of hydrogen evolution reaction (HER) and intricate side reactions on the Zn anode surface. The hydrogen (H)‐bond networks play a critical role in interfacial proton transport that may closely relate to HER but are rarely investigated. Herein, we report a self‐assembled monolayer (SAM) strategy which is constructed by anchoring ionic liquid cations on Ti3C2Tx substrate for HER‐free Zn anode. Molecule dynamics simulations reveal that the rationally designed SAM with a high coordination number of water molecules (25–27, 4–6 for Zn2+) largely reduces the interfacial densities of H2O molecules, therefore breaking the connectivity of H‐bond networks and blocking proton transport on the interface, by which the HER is suppressed. Then, a series of in situ characterizations demonstrate that negligible amounts of H2 gas are collected from the Zn@SAM‐MXene anode. Consequently, the symmetric cell enables a long‐cycling life of 3000 h at 1 mA cm−2 and 1000 h at 5 mA cm−2. More significantly, the stable Zn@SAM‐MXene films are successfully used for coin full cells showing high‐capacity retention of over 94 % after 1000 cycles and large‐area (10×5 cm2) pouch cells with desired performance.

Blocking Interfacial Proton Transport via Self-Assembled Monolayer for Hydrogen Evolution-Free Zinc Batteries.

Aqueous Zn-ion batteries (ZIBs) are promising next-generation energy storage devices, yet suffer from the issues of hydrogen evolution reaction (HER) and intricate side reactions on the Zn anode surface. The hydrogen (H)-bond networks play a critical role in interfacial proton transport that may closely relate to HER but are rarely investigated. Herein, we report a self-assembled monolayer (SAM) strategy which is constructed by anchoring ionic liquid cations on Ti3C2Tx substrate for HER-free Zn anode. Molecule dynamics simulations reveal that the rationally designed SAM with a high coordination number of water molecules (25-27, 4-6 for Zn2+) largely reduces the interfacial densities of H2O molecules, therefore breaking the connectivity of H-bond networks and blocking proton transport on the interface, by which the HER is suppressed. Then, a series of in situ characterizations demonstrate that negligible amounts of H2 gas are collected from the Zn@SAM-MXene anode. Consequently, the symmetric cell enables a long-cycling life of 3000 h at 1 mA cm-2 and 1000 h at 5 mA cm-2. More significantly, the stable Zn@SAM-MXene films are successfully used for coin full cells showing high-capacity retention of over 94 % after 1000 cycles and large-area (10×5 cm2) pouch cells with desired performance.

Analysis of the relationship between starch molecular conformation and enzymatic hydrolysis efficiency

Resistant starch (RS) is important in controlling diabetes. The primary objective of this study is to examine the impact of molecular conformation on the enzymatic hydrolysis efficiency of starch by α-amylase. And the interactions between starch molecules with different conformations and α-amylase were analysed by using molecule dynamics simulation and molecular docking. It was found, the natural conformational starch molecule was hydrolysed from the middle of the starch chain by α-amylase, producing polysaccharides. The bent PS-conformational starch molecules with multiple O2-O3 intramolecular hydrogen bonds produced by high-pressure was hydrolysed from the head of the starch chain to produce glucose, which is not conducive to RS formation. The stretched H-conformation without intramolecular hydrogen bonds produced by heat treatment was not hydrolysed by α-amylase. However, it occupied the active groove and formed strong interactions with α-amylase, which prevented other starch molecules from binding to α-amylase, thus reducing hydrolysis efficiency. Moreover, the total interaction energies between the three starch molecules and α-amylase were approximately 78 kJ/mol. And several hydrogen bonds were formed between the starch molecules and α-amylase, which provides evidence for the continuous sliding hydrolysis hypothesis of α-amylase. Moreover, these results provide an important reference for elucidating the mechanism of RS formation.

Vitrification-enabled enhancement of proton conductivity in hydrogen-bonded organic frameworks

Hydrogen-bonded organic frameworks (HOFs) are versatile materials with potential applications in proton conduction. Traditional approaches involve incorporating humidity control to address grain boundary challenges for proton conduction. This study finds vitrification as an alternative strategy to eliminate grain boundary effect in HOFs by rapidly melt quenching the kinetically stable HOF-SXU-8 to glassy state HOF-g. Notably, a remarkable enhancement in proton conductivity without humidity was achieved after vitrification, from 1.31 × 10−7 S cm−1 to 5.62× 10−2 S cm−1 at 100 °C. Long term stability test showed negligible performance degradation, and even at 30 °C, the proton conductivity remained at high level of 1.2 × 10−2 S cm−1. Molecule dynamics (MD) simulations and X-ray total scattering experiments reveal the HOF-g system is consisted of three kinds of clusters, i.e., 1,5-Naphthalenedisulfonic acid (1,5-NSA) anion clusters, N,N-dimethylformamide (DMF) molecule clusters, and H+-H2O clusters. In which, the H+ plays an important role to bridge these clusters and the high conductivity is mainly related to the H+ on H3O+. These findings provide valuable insights for optimizing HOFs, enabling efficient proton conduction, and advancing energy conversion and storage devices.

The optimization of evaporation rate in graphene-water system by machine learning algorithm

Solar interfacial evaporation, as a novel practical freshwater production method, requires continuous research on how to improve the evaporation rates to increase water production. In this study, sets of data were obtained from molecule dynamics simulation and literature, in which the parameters included height, diameter, height–radius ratio, evaporation efficiency, and evaporation rate. Initially, the correlation between the four input parameters and the output of the evaporation rate was examined through traditional pairwise plots and Pearson correlation analysis, revealing weak correlations. Subsequently, the accuracy and generalization performance of the evaporation rate prediction models established by neural network and random forest were compared, with the latter demonstrating superior performance and reliability confirmed via random data extraction. Furthermore, the impact of different percentages (10%, 20%, and 30%) of the data on the model performance was explored, and the result indicated that the model performance is better when the test set is 20% and all the constructed model converge. Moreover, the mean absolute error and mean squared error of the evaporation rate prediction model for the three ratios were calculated to evaluate their performance. However, the relationship between the height- radius ratio and optimal evaporation rate was investigated using the enumeration method, and it was determined that the evaporation efficiency was optimal when the height–radius ratio was 6. Finally, the importance of height, diameter, height– radius ratio, and evaporation efficiency were calculated to optimize evaporator structure, increase evaporation rate, and facilitate the application of interfacial evaporation in solar desalination.