Molecule-surface Interactions Research Articles

Electric Field Generated at the Millisecond Pulse-Polarized Interface Facilitates the Electrolytic Conversion of SO2 into H2S.

Interfacial electric field holds significant importance in determining both the polar molecular configuration and surface coverage during electrocatalysis. This study introduces a methodology leveraging the varying electric dipole moment of SO2 under distinct interfacial electric field strengths to enhance the selectivity of the SO2 electroreduction process. This approach presented the first attempt to utilize pulsed voltage application to the Au/PTFE membrane electrode for the control of the molecular configuration and coverage of SO2 on the electrode surface. Remarkably, the modulation of pulse duration resulted in a substantial inhibition of the hydrogen evolution reaction (HER) (FEH2 < 3%) under millisecond pulse conditions (ta = 10 ms, tc = 300 ms, Ea = -0.8 V (vs Hg/Hg2SO4), Ec = -1.8 V (vs Hg/Hg2SO4)), concomitant with a noteworthy enhancement in H2S selectivity (FEH2S > 97%). A comprehensive analysis, incorporating in situ Raman spectroscopy, electrochemical quartz crystal microbalance, COMSOL simulations, and DFT calculations, corroborated the increased selectivity of H2S products was primarily associated with the inherently large dipole moment of the SO2 molecule. The enhancement of the interfacial electric field induced by millisecond pulses was instrumental in amplifying SO2 coverage, activating SO2, facilitating the formation of the pivotal intermediate product *SOH, and effectively reducing the reaction energy barrier in the SO2 reduction process. These findings provide novel insights into the influences of ion and molecular transport dynamics, as well as the temporal intricacies of competitive pathways during the SO2 electroreduction process. Moreover, it underscores the intrinsic correlation between the electric dipole moment and surface-molecule interaction of the catalyst.

Testing functional anchor groups for the efficient immobilization of molecular catalysts on silver surfaces

Modifications of complexes by attachment of anchor groups are widely used to control molecule-surface interactions. This is of importance for the fabrication of (catalytically active) hybrid systems, viz. of surface immobilized molecular catalysts. In this study, the complex fac-Re(S-Sbpy)(CO)3Cl (S-Sbpy = 3,3′-disulfide-2,2′-bipyridine), a sulfurated derivative of the prominent Re(bpy)(CO)3Cl class of CO2 reduction catalysts, was deposited onto the clean Ag(001) surface at room temperature. The complex is thermostable upon sublimation as supported by infrared absorption and nuclear magnetic resonance spectroscopy. Its anchoring process has been analyzed using scanning tunneling microscopy (STM) and density functional theory (DFT) calculations. The growth behavior was directly contrasted to the one of the parent complex fac-Re(bpy)(CO)3Cl (bpy = 2,2′-bipyridine). The sulfurated complex nucleates as single molecule at different surface sites and at molecule clusters. In contrast, for the parent complex nucleation only occurs in clusters of several molecules at specifically oriented surface steps. While this shows that surface immobilization of the sulfurated complex is more efficient as compared to the parent, symmetry analysis of the STM topographic data supported by DFT calculations indicates that more than 90% of the complexes adsorb in a geometric configuration very similar to the one of the parent complex.

Competing Intermolecular and Molecule–Surface Interactions: Dipole–Dipole-Driven Patterns in Mixed Carborane Self-Assembled Monolayers

Competing Intermolecular and Molecule–Surface Interactions: Dipole–Dipole-Driven Patterns in Mixed Carborane Self-Assembled Monolayers

Vibrational energy transfer in collisions of molecules with metal surfaces.

The Born-Oppenheimer approximation (BOA), which serves as the basis for our understanding of chemical bonding, reactivity and dynamics, is routinely violated for vibrationally inelastic scattering of molecules at metal surfaces. The title-field therefore represents a fascinating challenge to our conventional wisdom calling for new concepts that involve explicit electron dynamics occurring in concert with nuclear motion. Here, we review progress made in this field over the last decade, which has witnessed dramatic advances in experimental methods, thereby providing a much more extensive set of diverse observations than has ever before been available. We first review the experimental methods used in this field and then provide a systematic tour of the vast array of observations that are currently available. We show how these observations - taken together and without reference to computational simulations - lead us to a simple and intuitive picture of BOA failure in molecular dynamics at metal surfaces, one where electron transfer between the molecule and the metal plays a preeminent role. We also review recent progress made in the theory of electron transfer mediated BOA failure in molecule-surface interactions, describing the most important methods and their ability to reproduce experimental observation. Finally, we outline future directions for research and important unanswered questions.

Nanostructures as the Substrate for Single-Molecule Magnet Deposition.

Anchoringsingle-molecule magnets (SMMs) on the surface of nanostructures is gaining particular interest in the field of molecular magnetism. The accurate organization of SMMs on low-dimensional substrates enables controlled interactions and the possibility of individual molecules' manipulation, paving the route for a broad range of nanotechnological applications. In this comprehensive review article, the most studied types of SMMs are presented, and the quantum-mechanical origin of their magnetic behavior is described. The nanostructured matrices were grouped and characterized to outline to the reader their relevance for subsequent compounding with SMMs. Particular attention was paid to the fact that this process must be carried out in such a way as to preserve the initial functionality and properties of the molecules. Therefore, the work also includes a discussion of issues concerning both the methods of synthesis of the systems in question as well as advanced measurement techniques of the resulting complexes. A great deal of attention was also focused on the issue of surface-molecule interaction, which can affect the magnetic properties of SMMs, causing molecular crystal field distortion or magnetic anisotropy modification, which affects quantum tunneling or magnetic hysteresis, respectively. In our opinion, the analysis of the literature carried out in this way will greatly help the reader to design SMM-nanostructure systems.

Assessing the dynamics of CO adsorption on Cu(110) using the vdW-DF2 functional and artificial neural networks

In this work, we revisit the dynamics of carbon monoxide molecular chemisorption on Cu(110) by using quasi-classical trajectory calculations. The molecule–surface interaction is described through an atomistic neural network approach based on Density Functional Theory calculations using a nonlocal exchange–correlation (XC) functional that includes the effect of long-range dispersion forces: vdW-DF2 [Lee et al. Phys. Rev. B, 82, 081101 (2010)]. With this approach, we significantly improve the agreement with experiments with respect to a similar previous study based on a semi-local XC functional. In particular, we obtain excellent agreement with molecular beam experimental data concerning the dependence of the initial sticking probability on surface temperature and impact energy at normal incidence. For off-normal incidence, our results also reproduce two trends observed experimentally: (i) the preferential sticking for molecules impinging parallel to the [1̄10] direction compared to [001] and (ii) the change from positive to negative scaling as the impact energy increases. Nevertheless, understanding the origin of some remaining quantitative discrepancies with experiments requires further investigations.

Accurate descriptions of molecule-surface interactions for understanding CO2 capture by MgO-based sorbents in wet conditions

MgO shows promise as a CO2 sorbent material for the intermediate temperature range. Here, a hybrid computation scheme, xDH:GGA that combines the XYG3-type of doubly hybrid (xDH) and the generalized gradient approximation (GGA) functionals, is applied. It aims to provide an accurate description of molecular-surface interactions to reduce calculation uncertainties in exploring CO2 capture mechanisms for MgO-based systems. After validating the accuracy of the hybrid scheme by modeling CO adsorption on both MgO(100) and NaCl(100) surfaces against the experimental results, CO2 capture in wet conditions is examined. The results highlight the importance of competitive adsorption between CO2 and water, which undermines the significance of the conventionally identified active sites on MgO surfaces. In contrast, the intermediate Mg(OH)2 layer emerges as a more viable active phase, whose presence was experimentally observed, where the layered structure of Mg(OH)2 is found to kinetically retard water dissociative adsorption. In addition to surface areas and pore structures, our study emphasizes the pivotal role played by selective CO2 chemical adsorption in the development of effective CO2 sorbent materials.

Quantum computation of reactions on surfaces using local embedding

Modeling electronic systems is an important application for quantum computers. In the context of materials science, an important open problem is the computational description of chemical reactions on surfaces. In this work, we outline a workflow to model the adsorption and reaction of molecules on surfaces using quantum computing algorithms. We develop and compare two local embedding methods for the systematic determination of active spaces. These methods are automated and based on the physics of molecule-surface interactions and yield systematically improvable active spaces. Furthermore, to reduce the quantum resources required for the simulation of the selected active spaces using quantum algorithms, we introduce a technique for exact and automated circuit simplification. This technique is applicable to a broad class of quantum circuits and critical to enable demonstration on near-term quantum devices. We apply the proposed combination of active-space selection and circuit simplification to the dissociation of water on a magnesium surface using classical simulators and quantum hardware. Our study identifies reactions of molecules on surfaces, in conjunction with the proposed algorithmic workflow, as a promising research direction in the field of quantum computing applied to materials science.

Dispersion-Corrected DFT-D4 Study of the Adsorption of Halobenzenes and 1,3,5-Trihalobenzenes on the Cu(111) Surface─Effect of Sigma Hole Properties.

Halogen bonds, characterized by directionality, tunability, hydrophobicity, and variable sizes, are ideal noncovalent interactions to design and control the formation of self-assembled nanostructures. The specific self-assembly cases formed by the halogen-bonding interaction have been well studied by scanning tunneling microscopy (STM) experiments and density functional theory (DFT) calculations. However, there is a lack of systematic theoretical adsorption studies on halogenated molecules. In this work, the adsorption of halobenzenes and 1,3,5-trihalobenzenes on the Cu(111) surface was examined by dispersion-corrected DFT methods. The adsorption geometries, noncovalent molecule-surface interactions, electronic densities, and electrostatic potential maps were examined for their most stable adsorption sites using the DFT-D4 method. Our calculations revealed that the iodo compounds favor a different adsorption geometry from aryl chlorides and bromides. Down the halogen group (Cl to I), the adsorption energy increases and the distance between the halogen atom and Cu surface decreases, which indicates stronger molecule-surface interactions. This is supported by the changes in the density of states upon adsorption. Noncovalent interaction analysis was also employed to further understand the nature and relative strength of the molecule-surface interactions. Electrostatic potential maps revealed that the positive character of the halogen sigma hole becomes stronger upon adsorption. Thus, surface adsorption of the halogenated molecule will enhance the formation of intermolecular halogen bonds. The present theoretical findings are expected to contribute toward a more comprehensive understanding of halogen bonding on the Cu(111) surface.

Xsorb: A software for identifying the most stable adsorption configuration and energy of a molecule on a crystal surface

Molecular adsorption is the first important step of many surface-mediated chemical processes, from catalysis to lubrication. This phenomenon is controlled by physical/chemical interactions, which can be accurately described by first-principles calculations. Several computational tools have been developed to study molecular adsorption based on high throughput/automatized approaches in recent years. However, these tools can sometimes be over-sophisticated for non-expert users. Here we present Xsorb, a Python-based program for identifying the accurate adsorption energy and geometry of complex molecules on crystalline (reconstructed) surfaces. The program automatically samples the potential energy surface (PES) that describes the molecule-surface interaction by generating several adsorption configurations through symmetry operations. The set of the most representative ones is automatically identified through a fast pre-optimization scheme. Finally, the PES global minimum is identified through a full structural optimization process. We show the program capabilities through an example consisting of a hydrocarbon molecule, 1-hexene, adsorbed over the (110) surface of iron and the reconstructed (001) surface of diamond. This program, despite its conceptual simplicity, is very effective in reducing the computational workload usually associated with the creation and optimization of several adsorption configurations. Program summaryProgram title: XsorbCPC Library link to program files:https://doi.org/10.17632/kv97tgybx8.1Developer's repository link:https://gitlab.com/triboteam/xsorbed/Licensing provisions: CC by 4.0Programming language: Python (version 3.7 and above) and Quantum ESPRESSO (for the ab initio calculations).Nature of problem: Identifying the most stable adsorption configuration of a molecule over a substrate and compute its adsorption energy.Solution method: Creating a Python-based code that generates many adsorption configurations with different molecular orientations, performs a preliminary partial geometrical optimization with density functional theory calculations of all these configurations, identifies the most relevant ones for the full geometrical optimization and computes the adsorption energy.

Rotationally Inelastic Scattering Dynamics of NO from Ag(111): Influence of Interaction Potentials

State-to-state molecular scattering from surfaces represents a sensitive probe of the molecule–surface interaction potential. For NO scattering from Ag(111), a benchmark system for studying gas–surface energy transfer, abundant experimental data have provided us a great testing ground to validate the accuracy of first-principles description of molecule–surface interactions. Here, we use an accurate neural network fitting method to construct two high-dimensional potential energy surfaces (PESs) based on density functional theory (DFT) single points using PBE and revPBE functionals, respectively, for describing the rotationally inelastic scattering of NO from Ag(111). Quasi-classical trajectory calculations based on the two PESs have been compared with a diversity of experimental data and the influence of scattering angle, initial molecular orientation, and incidence energy on the rotational state distribution is discussed. It is found in general that revPBE-based results agree better than PBE-based ones with the measured scattering angle and final rotational state distributions, capturing reasonably the rotational rainbow feature at a small incidence energy and the steric effect. But neither PES reproduces all experimental data quantitatively. The different performance of the two PESs can be attributed to their difference in the attractiveness, anisotropy, and corrugation in the entrance channel. Our results suggest the need of further improvement of the accuracy of DFT with commonly used density functionals toward a chemically accurate description of molecule–surface interactions.

Structure and Stability of Metalloporphyrin Networks on Au(111)

We use density functional theory (DFT) calculations to analyze the properties of FeTPyP self-assembled monolayers (SAMs) and FeTPyP+Fec metal–organic coordination networks (MOCNs) on Au(111). Through a rigorous step-by-step approach, we determine the relative importance of the multiple competing interactions that determine the optimum structure and stability of both networks. For FeTPyP/Au(111) SAMs, we see a complex energy landscape, with molecules preferring to stay at molecule–molecule distances dop ∼ 13.7 and 14.3 Å. Molecule–surface interactions are more prominent in less dense packing (dop ∼ 14.3 Å), and intermolecular interactions favor the compact structure (dop ∼ 13.7 Å). In the case of the FeTPyP–Fec/Au(111) MOCN, the strong Fec–Npy bond between the peripheral iron atom Fec and nitrogen atoms of neighboring pyridyl groups (Npy) is what causes the network development and that the preferred molecule–molecule distance remains at dop ∼ 13.7 Å. Our findings demonstrate the necessity of theoretical treatments that take into account all relevant interactions in order to adequately describe the primary characteristics of surface-supported SAMs and MOCNs.

Accurate descriptions of molecule-surface interactions in electrocatalytic CO2 reduction on the copper surfaces

Copper-based catalysts play a pivotal role in many industrial processes and hold a great promise for electrocatalytic CO2 reduction reaction into valuable chemicals and fuels. Towards the rational design of catalysts, the growing demand on theoretical study is seriously at odds with the low accuracy of the most widely used functionals of generalized gradient approximation. Here, we present results using a hybrid scheme that combines the doubly hybrid XYG3 functional and the periodic generalized gradient approximation, whose accuracy is validated against an experimental set on copper surfaces. A near chemical accuracy is established for this set, which, in turn, leads to a substantial improvement for the calculated equilibrium and onset potentials as against the experimental values for CO2 reduction to CO on Cu(111) and Cu(100) electrodes. We anticipate that the easy use of the hybrid scheme will boost the predictive power for accurate descriptions of molecule-surface interactions in heterogeneous catalysis.

Towards 3D printing of lipids - The impact of surface polarity on lipid assembly under spatial confinement.

Molecular dynamics (MD) simulations in the MARTINI model are used to study the assembly of 1-palmitoyl-2-oleoylphosphatidylcholine (POPC) molecules under spatial confinement, such as during solvent evaporation from ultrasmall (femtoliter quantity) droplets. The impact of surface polarity on molecular assembly is discussed in detail. Our results reveal that solvent evaporation gives rise to the formation of well-defined stacks of lipid bilayers in a smectic alignment. These smectic mesophases form on both polar and nonpolar surfaces but with a notable distinction. On polar surfaces, the director of the stack is oriented perpendicular to the support surface. By contrast, the stacks orient at an angle on the nonpolar surfaces. The packing of head groups on surfaces and lipid molecular mobility exhibits significant differences as surface polarity changes. The role of glycerol in the assembly and stability is also revealed. The insights revealed from the simulation have a significant impact on additive manufacturing, biomaterials, model membranes, and engineering protocells. For example, POPC assemblies via evaporation of ultrasmall droplets were produced and characterized. The trends compare well with the bilayer stack models. The surface polarity influences the local morphology and structures at the interfaces, which could be rationalized via the molecule-surface interactions observed from simulations.

2023 ACS National Award winners—Part III

ACS Award in Surface Chemistry: Joachim Sauer Sponsor : Procter & Gamble Citation: For seminal contributions to atomistic understanding of the surface chemistry of complex oxides and for the development of computational tools for molecule surface interactions Current position: Senior researcher, Humboldt University of Berlin Education: Diplom, chemistry, and Dr. rer. nat., chemistry, Humboldt University of Berlin; Dr. sc. nat., chemistry, East German Academy of Sciences Sauer on his proudest career moment: “Getting the Dr. sc. nat. degree at the Academy of Sciences in East Berlin, because I achieved this based on my own scientific merits without any career support from the ruling (Communist) party in East Germany.” What Sauer’s colleagues say: “Joachim’s contributions are unique in their combination of rigor, relevance, and depth of theory–experiment collaboration.”—Laura Gagliardi, University of Chicago ACS Award in the Chemistry of Materials: Reshef Tenne Sponsor: DuPont Citation: For the discovery, elucidation, and commercial development

Atomistic simulations for investigation of substrate effects on lipid in-source fragmentation in secondary ion mass spectrometry.

In beam-based ionization methods, the substrate plays an important role on the desorption mechanism of molecules from surfaces. Both the specific orientation that a molecule adopts at a surface and the strength of the molecule-surface interaction can greatly influence desorption processes, which in turn will affect the ion yield and the degree of in-source fragmentation of a molecule. In the beam-based method of secondary ion mass spectrometry (SIMS), in-source fragmentation can be significant and molecule specific due to the hard ionization method of using a primary ion beam for molecule desorption. To investigate the role of the substrate on orientation and in-source fragmentation, we have used atomistic simulations-molecular dynamics in combination with density functional theory calculations-to explore the desorption of a sphingolipid (palmitoylsphingomyelin) from a model surface (gold). We then compare SIMS data from this model system to our modeling findings. Using this approach, we found that the combined adsorption and binding energy of certain bonds associated with the headgroup fragments (C3H8N+, C5H12N+, C5H14NO+, and C5H15PNO4 +) was a good predictor for fragment intensities (as indicated by relative ion yields). This is the first example where atomistic simulations have been applied in beam-based ionization of lipids, and it presents a new approach to study biointerfacial lipid ordering effects on SIMS imaging.

Machine-learning based prediction of small molecule-surface interaction potentials.

Predicting the adsorption affinity of a small molecule to a target surface is of importance to a range of fields, from catalysis to drug delivery and human safety, but a complex task to perform computationally when taking into account the effects of the surrounding medium. We present a flexible machine-learning approach to predict potentials of mean force (PMFs) and adsorption energies for chemical-surface pairs from the separate interaction potentials of each partner with a set of probe atoms. We use a pre-existing library of PMFs obtained via atomistic molecular dynamics simulations for a variety of inorganic materials and molecules to train the model. We find good agreement between original and predicted PMFs in both training and validation groups, confirming the predictive power of this approach, and demonstrate the flexibility of the model by producing PMFs for molecules and surfaces outside the training set.

Hollow nano-CaCO3's VOC sensing properties: A DFT calculation and experimental assessments

Air is the most critical and necessary for life, and air quality significantly impacts people's health. Both indoor and outdoor pollution frequently contain volatile organic compounds (VOCs). Such contaminants provide immediate or long-term health risks to the living system. The present study investigates sorption characteristics of VOCs on hollow nano calcite (CaCO3) particles with 250 nm and 40 nm pore sizes to remove from the air ambient using the quartz crystal microbalance (QCM) technique at room temperature both experimentally and theoretically. The results were supported by density functional theory (DFT), and adsorption-desorption characteristics were studied with Langmuir adsorption isotherms. The QCM measurements showed a stable signal without having hysteresis, and the response of polar VOCs on hollow nano-CaCO3 particles such as ethanol, propanol, and humidity with higher polarity was less compared to solvents such as chloroform and dichloromethane, which revealed that the surfaces of CaCO3 particles have mostly non-polar properties. CaCO3 surface and VOC molecule interactions overlap with the Langmuir model. With DFT calculations, VOC and water molecule adsorption changes the CaCO3 Egap. Our findings show that the ΔEgap values increase as chloroform > dichloromethane > propanol > ethanol > water. This order suggests that the sensing response of the hollow CaCO3 structure is linearly proportional to the adsorption energies of VOC and water. The linear adsorption characteristics, high sensing response, and short recovery time illustrated that the newly synthesized nano-CaCO3 could be implemented as a new VOC adsorbent material for health, environmental sustainability, and in vitro microbiome cultures.

Versatile Role of Molecule–Surface Interactions for Monolayer Self-Assembly at Liquid–Solid Interfaces: Substrate-Induced Polymorphism, Thermodynamic Stability, and New Polymorphs

Versatile Role of Molecule–Surface Interactions for Monolayer Self-Assembly at Liquid–Solid Interfaces: Substrate-Induced Polymorphism, Thermodynamic Stability, and New Polymorphs

Roles of regulatory B cells in the pathogenesis of allergic rhinitis.

Allergic rhinitis (AR) is a common otolaryngologic disease with frequent episodes of sneezing, clear nasal discharge flow and nasal congestion. The mechanisms of AR are complex and considered generally caused by the immune tolerance deficiency. Regulatory B cells (Bregs) are immunosuppressive cells that can modulate immune responses by the secretion of IL-10, IL-35, and tumor growth factor-β (TGF-β) and via the interaction of membrane surface molecules. However, Bregs are numerically deficient and/or dysfunctional in airway allergic diseases such as AR and allergic asthma, and the related mechanisms remain unclear. In this review, we summarize the role of Bregs in AR pathogenesis and highlight the importance of Bregs in maintaining immune tolerance. It is believed that further research on Bregs will contribute to developing new treatments and finding specific biomarkers that could help to predict disease progression.