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Monte Carlo analysis of free and near free molecular flow through circular tubes for mass, momentum and energy transfer
Absolute total negative charge production cross sections for N2 + CO, CO + N2, CO + CO, N2 + NO, N2 + CH4, and N2 + CO2 collisions are reported, and a simple model of collisions is discussed. The cross sections were measured to within about 1 eV of their thresholds. Specific reaction channels were investigated by referring to mass spectrometric identification of the product ions scattered in the forward direction, and these product ion identifications were used to explain characteristic structures in the total charge production cross sections in the near-threshold regions. The extent of the importance of dissociative ionization and 'simple' ionization in the studied collisions at low energy is considered, and charge transfer cross sections for (CO)+ + CO, CO(+) + CH4, and N2(+) + CH4 are presented.
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We performed calculations of electronic excitation energies and associated oscillator strengths based on the time-dependent density-functional tight-binding (TD-DFTB) method [1]. The SMILES (Simplified molecular-input line-entry system) strings of the molecules from the AISD HOMO-LUMO database [2] were converted to a 3D atomistic structure and stored in a PDB file after preliminary geometry optimization using the Merck Molecular Force Field (MMFF94) in RDKit [3,4]. The primary information stored in the PDB file archive consists of Cartesian coordinates for each atom of the molecule in their 3D location in space, along with summary information about the structure, sequence, and experiment. We then performed molecular geometry optimization using the density-functional tight-binding (DFTB) method [5] in the electronic ground state, followed by single-point excited states calculations, as described below. We note that, since RDKit employs a random choice for the generation of molecular conformers, the molecular geometries obtained in this dataset could be different from the ones that were generated when the AISD HOMO-LUMO dataset was generated. The computed excitation energies and associated oscillator strengths can be converted to predict UV/Vis absorption spectra, where excitation energies correspond to absorption peak positions, and oscillator strengths are a good measure of the probability of absorption of visible or UV light in transitions between electronic ground and excited states. The conversion of SMILES strings to 3D Cartesian coordinates of fully DFTB-optimized molecules was successful for 10,502,904 out of 10,502,917 molecules. For these molecules, both geometry optimizations and excited states calculations were successful. The DFTB calculations did not complete for 13 molecules of the original AISD HOMO-LUMO dataset. We still provide information about the geometry of these molecules. The molecules are diverse for chemical compositions (which span 5 non-hydrogen elements: oxygen, carbon, nitrogen, fluorine, sulfur) and molecular size (the smallest molecule contains 5 non-hydrogen atoms, and the largest molecule contains 71 non-hydrogen atoms). The DFTB method [5] is an approximation to density functional theory (DFT), utilizing a minimal basis set in conjunction with a two-center approximation to the electronic Hamiltonian and overlap matrix elements. The DFTB total energy is the sum of an electronic and a repulsive energy contribution, and their calculation requires optimized electronic parameters and diatomic repulsive potential energy functions. All DFTB calculations were performed using the DFTB+ code [6] (version 21.2) and the wrapper for DFTB+ in the Atomic Simulation Environment (ASE) (version 3.22.1) [7], which performed an internal conversion of Cartesian coordinates from PDB to the .gen file format. For the geometry optimizations on the electronic ground state potential energy surface of the molecules, we have chosen the third-order DFTB (DFTB3) method [5c] and employed the matching 3ob set of electronic parameters and repulsive potentials [8]. The empirical γ-damping for hydrogen bond correction, and Grimme's D3 empirical dispersion correction with Becke-Johnson damping (D3(BJ)) [9] dispersion correction was included to improve the description of non-covalent interactions. For excited states single-point energy calculations, we employed the TD-DFTB method in conjunction with the DFTB2 method [5b] and the matching mio [5b,10] and halorg [11] parameter sets. We opted to request the simultaneous calculation of 50 excited states for singlet transition to investigate sufficient number of excited states, based on linear response theory using the Casida equation [Ref: T. A. Niehaus, S. Suhai, F. Della Sala, P Lugli, M. Elstner, G. Seifert, and Th. Frauenheim. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 63:085108, 2001] and the ARPACK diagonalizer [R. B. Lehoucq, D. C. Sorensen, and C. Yang. Arpack users guide: Solution of large-scale eigenvalue problems by implicitly restarted arnoldi methods, 1997. 46, 51]. The dataset contains 1001 tar.gz files. Tar files are named as “ornl_aisd_ex_1.tar.gz†through “ornl_aisd_ex_1000.tar.gzâ€. Additionally, the 13 failed molecules are in “ornl_aisd_ex_unprocessed.tar.gzâ€. Except for the tar files listed below, each tar file contains 10,500 molecules. Tar files numbered 34, 121, 128, 352, 360, 429, 495, 509, 518, 627, 676, 668, and 862 contain 10,499 molecules each. The last tar file numbered 1000 contains 13,417 molecules. The total size of the uncompressed dataset is over 283 Gigabytes. The code for calculating the electronic excitation energies and statistical analysis of the dataset is provided at the following GitLab repository: https://github.com/ORNL/Analysis-of-Large-Scale-Molecular-Datasets-with-Python Calculating the UV spectrum of a molecule requires performing 3 main operations: 1. Converting the smiles string representation of a molecule into a geometric structure where each atom is assigned XYZ coordinates. The geometric structure is written to the file smiles.pdb. 2. Using smiles.pdb to compute the relaxed geometry of the molecule, which corresponds with the position of the atoms at the position of equilibrium at the ground state. This generates the files band.out, detailed.out, and geo_end.gen. 3. Using geo_end.gen to calculate the UV spectrum of the molecule which is written into the file EXC.DAT. Every molecule in the dataset has its own directory. The files contained in each molecule directory are as follows: 1. geo_end.gen 2. detailed.out 3. band.out 4. EXC.DAT 5. smiles.pdb REFERENCES [1] Niehaus, T. A.; Suhai, S.; Della Salla, F.; Lugli, P.; Elstner, M.; Seifert, G.; Frauenheim, Th. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 2001, 63, 085108/1-9. [2] Blanchard, A.; Gounley, J.; Metha, K.; Yoo, P.; Irle, S. AISD HOMO-LUMO. DOI: 10.13139/ORNLNCCS/1869409 [3] RDKit: Cheminformatics and Machine Learning Software. 2013, [http://www.rdkit.org] [4] Tosco, P.; Stiefl, N. and Landrum, G. Bringing the MMFF force field to the RDKit: implementation and validation. J Cheminform. 2014, 6, 1–4. [5] a) Porezag, D.; Frauenheim, T.; Kohler, T.; Seifert, G.; Kaschner, Construction of tight-binding-like potentials on the basis of density-functional theory: Application to carbon, R. Phys. Rev. B 1995, 51, 12947-12957; b) Elstner, M.; Porezag, D.; Jungnickel, G.; Elsner, J.; Haugk, M.; Frauenheim, Th.; Suhai, S.; Seifert, G.; Phys. Rev. B 1998, 58, 7260-7268; c) Gaus, M.; Cui, Q.; Elstner, M. DFTB3: Extension of the Self-Consistent-Charge Density-Functional Tight-Binding Method (SCC-DFTB), J. Chem. Theory Comput. 2011, 7, 931-948; d) Cui, Q.; Elstner, M. Density functional tight binding: values of semi-empirical methods in an ab initio era, Phys. Chem. Chem. Phys. 2014, 16, 14368-14377. [6] Hourahine, B. et al. DFTB+, a software package for efficient approximate density functional theory based atomistic simulations, J. Chem. Phys. 2020, 152, 124101/1-19. [7] Larsen, A. H. et al. The atomic simulation environment—a Python library for working with atoms. J. Phys.: Cond. Matter 2017, 29, 273002. [8] Kubillus, M.; Kubar, T.; Gaus, M.; Rezac, J.; Elstner, M. Parameterization of the DFTB3 Method for Br, Ca, Cl, F, I, K, and Na in Organic and Biological Systems, J. Chem. Theory Comput. 2015, 11, 332-342. [9] Brandenburg, J. G.; Grimme, S. Accurate Modeling of Organic Molecular Crystals by Dispersion-Corrected Density Functional Tight Binding (DFTB), J. Phys. Chem. Lett. 2014, 5, 1785−1789. [10] a) Niehaus, T. A.; Elstner, M.; Frauenheim, Th.; Suhai, S. Application of an approximate density-functional method to sulfur containing compounds. J. Mol. Struct.: THEOCHEM 2001, 541, 185-94; b) Elstner, M.; Hobza, P.; Frauenheim, Th.; Suhai, S.; Kaxiras, E. Hydrogen bonding and stacking interactions of nucleic acid base pairs: A density-functional-theory based treatment. J. Chem. Phys. 2001, 114, 5149-55. [11] Kubar, T.; Bodrog, Z.; Gaus, M.; Köhler, C.; Aradi, B.; Frauenheim, Th.; Elstner, M. Parametrization of the SCC-DFTB Method for Halogens. J. Chem. Theory Comput. 2013, 9, 2939-49.
Single-molecule spectroscopy has made considerable impact on many disciplines including chemistry, physics, and biology. To date, most single-molecule spectroscopy work is accomplished by detecting fluorescence. On the other hand, many naturally occurring chromophores, such as retinal, hemoglobin and cytochromes, do not have detectable fluorescence. There is an emerging need for single-molecule spectroscopy techniques that do not require fluorescence. In the last proposal period, we have successfully demonstrated stimulated emission microscopy, single molecule absorption, and stimulated Raman microscopy based on a high-frequency modulation transfer technique. These first-of-a- kind new spectroscopy/microscopy methods tremendously improved our ability to observe molecules that fluorescence weakly, even to the limit of single molecule detection for absorption measurement. All of these methods employ two laser beams: one (pump beam) excites a single molecule to a real or virtual excited state, and the other (probe beam) monitors the absorption/emission property of the single. We extract the intensity change of the probe beam with high sensitivity by implementing a high-frequency phase-sensitive detection scheme, which offers orders of magnitude improvement in detection sensitivity over direct absorption/emission measurement. However, single molecule detection based on fluorescence or absorption is fundamentally limited due to their broad spectral response. It is important to explore other avenues in single molecule detection and imaging which provides higher molecular specificity for studying a wide variety of heterogeneous chemical and biological systems. This proposal aimed to achieve single-molecule detection sensitivity with near resonance stimulated Raman scattering (SRS) microscopy. SRS microscopy was developed in our lab as a powerful technique for imaging heterogeneous samples based on their intrinsic vibrational contrasts, which provides much higher molecular specificity than absorption and fluorescence. Current sensitivity limit of SRS microscopy has not yet reached single molecule detection. We proposed to capitalize on our state-of-the-art SRS microscopy and develop near-resonance enhanced SRS for single molecule detection of carotenoids and heme proteins. The specific aims we pursued are: (1) building the next SRS generation microscope that utilizes near resonance enhancement to allow detection and imaging of single molecules with undetectable fluorescence, such as -carotene. (2) using near-resonance SRS as a contrast mechanism to study dye-sensitize semiconductor interface, elucidating the heterogeneous electron ejection kinetics with high spatial and temporal resolution. (3) studying the binding and unbinding of oxygen in single hemoglobin molecules in order to gain molecular level understanding of the long-standing issue of cooperativity. The new methods developed in the fund period of this grant have advanced the detection sensitivity in many aspects. Near-resonance SRS improved the signal by using shorter wavelengths for SRS microscopy. Frequency modulation and multi-color SRS target the reduction of background to improve the chemical specificity of SRS while maintaining the high imaging speed. Time-domain coherent Raman scattering microscopy targets to reduce the noise floor of coherent Raman microscopy. These methods have already demonstrated first-of-a-kind new applications in biology and medical research. However, we are still one order of magnitude away from single molecule limit. It is important to continue to improve the laser specification and develop new imaging methods to finally achieve label-free single molecule microscopy.
In this project we investigated electronic structure of an intermediate-sized copper-based molecule and magnetic and hyperfine properties of several small non-magnetic and magnetic molecules including transition-metal elements by applying self-interaction corrections to density functional theory (DFT). In a sufficient number of cases, DFT-calculated electronic structure and magnetic properties of single-molecule magnets qualitatively differ from corresponding experimental data. This is partly due to self-interacting electrons within the DFT formalism. Recently, an efficient method to correct the self-interactions was proposed, i.e., Fermi-Lowdin prbital (FLO) based self-interaction corrected (SIC) methodology, within DFT. Henceforth, this method is referred to as FLO-SIC method which exists in FLOSIC code. We used this FLO-SIC method for our studies of electronic structure and magnetic and hyperfine properties of small magnetic molecules and non-magnetic molecules. Our study will provide insight into predictions of magnetic properties of single-molecule magnets where self-interaction corrections play a critical role. There are two components of this project. In the first work, we studied the electronic structure of a planar mononuclear Cu-based molecule in two oxidation states, using DFT with the FLO-SIC method. We chose this system because it is small enough and it includes a transition metal element. We found that the standard FLO-SIC method takes too much compute time even for the small transition-metal molecule and so we slightly modified the method in order to expedite the process. In the dianionic state, we found that the FLO-SIC spin density agrees quantitatively with accurate quantum chemistry methods, while DFT spin density without self-interaction corrections are severely deviated from the quantum chemistry methods. We also showed that the energy gap between the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of the dianionic state is larger than that of the monoanionic state. This result is consistent with experimental data. In the second work, we investigated how the interaction between the electron spin and nuclear spin is affected by electron self-interactions within small non-magnetic and magnetic molecules. Such an interaction is called hyperfine interaction. For molecules without significant orbital angular momentum, the hyperfine interaction consists of Fermi contact and dipolar interaction terms. Since the Fermi contact term depends on electron spin density at the nuclear site, it would be highly affected by self-interaction corrections. Therefore, we calculated the hyperfine interaction for the small molecules using DFT with the slightly modified expedited FLO-SIC method which was obtained in the first work, and compared the results to experimental data and DFT calculations without self-interaction corrections. We found significant improvement of the Fermi contact term computed using the FLO-SIC method for small magnetic molecules. Overall, the first and second work provided positive outlook of application of the FLO-SIC method to magnetic molecules and systems including transition-metal elements.
A systematic study is reported on the interaction of two representative redox active organic molecules and two solvent molecules with pristine and defective graphene surfaces as a model of an electrode surface of a redox flow battery (RFB). The redox active molecules include a catholyte, 2,5-di-tert-butyl-1,4-dimethoxybenzene (DDB), and an anolyte molecule, benzothiadiazole (BTZ), and the solvent molecules include acetonitrile (MeCN) and ethylene carbonate (EC). The graphene defects investigated include a single vacancy, double vacancy, zigzag step edge, and armchair step edge. Computations suggest that the interactions of all molecules with a pristine graphene surface are relatively weak (0.2 to 0.8 eV) and dominated by van der Waals effects; therefore, these molecules are chemically stable upon interacting with pristine nondefective graphene. The BTZ, DDB, MeCN, and EC molecules interact strongly (1.5 to 5.5 eV) with the single vacancy and zigzag step edges of graphene that leads to the possible decomposition of the molecules with strength of interaction in the order of MeCN > BTZ > DDB > EC and MeCN > EC > BTZ > DDB, respectively. Calculations show that the BTZ, DDB, MeCN, and EC molecules interact less strongly (0.2 to 1.4 eV) to the double vacancy and armchair step edge than to the single vacancy and zigzag step edge. The binding energies of the molecules were significantly reduced when interacting with the passivated defects, suggesting that the passivation of the defects could help prevent unwanted chemical interactions between the neutral molecules and the electrode surface. In all organic RFBs, one of the crucial bottlenecks is the stability of the constituent molecules with the electrode material, and this study provides insights into the chemical interaction of selected candidate species with a model carbon electrode.
High-fidelity quantum-chemical calculations can provide accurate predictions of molecular energies, but their high computational costs limit their utility, especially for larger molecules. We have shown in previous work that machine learning models trained on high-level quantum-chemical calculations (G4MP2) for organic molecules with one to nine non-hydrogen atoms can provide accurate predictions for other molecules of comparable size at much lower costs. Here we demonstrate that such models can also be used to effectively predict energies of molecules larger than those in the training set. To implement this strategy, we first established a set of 191 molecules with 10–14 non-hydrogen atoms having reliable experimental enthalpies of formation. We then assessed the accuracy of computed G4MP2 enthalpies of formation for these 191 molecules. The error in the G4MP2 results was somewhat larger than that for smaller molecules, and the reason for this increase is discussed. Two density functional methods, B3LYP and ωB97X-D, were also used on this set of molecules, with ωB97X-D found to perform better than B3LYP at predicting energies. The G4MP2 energies for the 191 molecules were then predicted using these two functionals with two machine learning methods, the FCHL-Δ and SchNet-Δ models, with the learning done on calculated energies of the one to nine non-hydrogen atom molecules. The better-performing model, FCHL-Δ, gave atomization energies of the 191 organic molecules with 10–14 non-hydrogen atoms within 0.4 kcal/mol of their G4MP2 energies. Thus, this work demonstrates that quantum-chemically informed machine learning can be used to successfully predict the energies of large organic molecules whose size is beyond that in the training set.
Electronic devices composed of single molecules constitute the ultimate limit in the continued downscaling of electronic components. A key challenge for single-molecule electronics is to control the temperature of these junctions. Controlling heating and cooling effects in individual vibrational modes can, in principle, be utilized to increase stability of single-molecule junctions under bias, to pump energy into particular vibrational modes to perform current-induced reactions, or to increase the resolution in inelastic electron tunneling spectroscopy by controlling the life-times of phonons in a molecule by suppressing absorption and external dissipation processes. Under bias the current and the molecule exchange energy, which typically results in heating of the molecule. However, the opposite process is also possible, where energy is extracted from the molecule by the tunneling current. Designing a molecular “heat sink” where a particular vibrational mode funnels heat out of the molecule and into the leads would be very desirable. It is even possible to imagine how the vibrational energy of the other vibrational modes could be funneled into the “cooling mode,” given the right molecular design. Previous efforts to understand heating and cooling mechanisms in single molecule junctions have primarily been concerned with small models, where it is unclear which molecular systems they correspond to. In this paper, our focus is on suppressing heating and obtaining current-induced cooling in certain vibrational modes. Strategies for cooling vibrational modes in single-molecule junctions are presented, together with atomistic calculations based on those strategies. Cooling and reduced heating are observed for two different cooling schemes in calculations of atomistic single-molecule junctions.
Electron transport and optical properties of a single molecule in contact with conductive materials have attracted considerable attention because of their scientific importance and potential applications. With the recent progress in experimental techniques, especially by virtue of scanning tunneling microscope (STM)-induced light emission, where the tunneling current of the STM is used as an atomic-scale source for induction of light emission from a single molecule, it has become possible to investigate single-molecule properties at subnanometer spatial resolution. Despite extensive experimental studies, the microscopic mechanism of electronic excitation of a single molecule in STM-induced light emission has yet to be clarified. Here we present a formulation of single-molecule electroluminescence driven by electron transfer between a molecule and metal electrodes based on a many-body state representation of the molecule. The effects of intramolecular Coulomb interaction on conductance and luminescence spectra are investigated using the nonequilibrium Hubbard Green’s function technique combined with first-principles calculations. We compare simulation results with experimental data and find that the intramolecular Coulomb interaction is crucial for reproducing recent experiments for a single phthalocyanine molecule. The developed theory provides a unified description of the electron transport and optical properties of a single molecule in contact with metal electrodes driven out of equilibrium, and thereby, it contributes to a microscopic understanding of optoelectronic conversion in single molecules on solid surfaces and in nanometer-scale junctions.
Low-energy excitations of a single water molecule are studied when confined within a nano-size cavity formed by the ionic crystal lattice. Optical spectra are measured of manganese doped beryl single crystal Mn:Be{sub 3}Al{sub 2}Si{sub 6}O{sub 18}, that contains water molecules individually isolated in 0.51 nm diameter voids within the crystal lattice. Two types of orientation are distinguished: water-I molecules have their dipole moments aligned perpendicular to the c axis and dipole moments of water-II molecules are parallel to the c-axis. The optical conductivity σ(ν) and permittivity ε{sup ′}(ν) spectra are recorded in terahertz and infrared ranges, at frequencies from several wavenumbers up to ν = 7000 cm{sup −1}, at temperatures 5–300 K and for two polarizations, when the electric vector E of the radiation is parallel and perpendicular to the c-axis. Comparative experiments on as-grown and on dehydrated samples allow to identify the spectra of σ(ν) and ε{sup ′}(ν) caused exclusively by water molecules. In the infrared range, well-known internal modes ν{sub 1}, ν{sub 2}, and ν{sub 3} of the H{sub 2}O molecule are observed for both polarizations, indicating the presence of water-I and water-II molecules in the crystal. Spectra recorded below 1000 cm{sup −1} reveal a rich set of highly anisotropic features in the low-energy response of H{sub 2}O molecule in a crystalline nano-cavity. While for E∥c only two absorption peaks are detected, at ∼90 cm{sup −1} and ∼160 cm{sup −1}, several absorption bands are discovered for E⊥c, each consisting of narrower resonances. The bands are assigned to librational (400–500 cm{sup −1}) and translational (150–200 cm{sup −1}) vibrations of water-I molecule that is weakly coupled to the nano-cavity “walls.” A model is presented that explains the “fine structure” of the bands by a splitting of the energy levels due to quantum tunneling between the minima in a six-well potential relief felt by a molecule within the cavity.
Advances in our ability to slow down and cool atoms and molecules to ultracold temperatures have paved the way to a revolution in basic research on molecules. Ultracold molecules are sensitive of very weak interactions, even when separated by large distances, which allow studies of the effect of those interactions on the behavior of molecules. In this program, we have explored ways to form ultracold molecules starting from pairs of atoms that have already reached the ultracold regime. We devised methods that enhance the efficiency of ultracold molecule production, for example by tuning external magnetic fields and using appropriate laser excitations. We also investigates the properties of those ultracold molecules, especially their de-excitation into stable molecules. We studied the possibility of creating new classes of ultra-long range molecules, named macrodimers, thousand times more extended than regular molecules. Again, such objects are possible because ultra low temperatures prevent their breakup by collision. Finally, we carried out calculations on how chemical reactions are affected and modified at ultracold temperatures. Normally, reactions become less effective as the temperature decreases, but at ultracold temperatures, they can become very effective. We studied this counter-intuitive behavior for benchmark chemical reactions involving molecular hydrogen.
The Protein Data Bank (PDB) is the single global repository for three-dimensional structures of biological macromolecules and their complexes, and its more than 100 000 structures contain more than 20 000 distinct ligands or small molecules bound to proteins and nucleic acids. Information about these small molecules and their interactions with proteins and nucleic acids is crucial for our understanding of biochemical processes and vital for structure-based drug design. Small molecules present in a deposited structure may be attached to a polymer or may occur as a separate, non-covalently linked ligand. During curation of a newly deposited structure by wwPDB annotation staff, each molecule is cross-referenced to the PDB Chemical Component Dictionary (CCD). If the molecule is new to the PDB, a dictionary description is created for it. The information about all small molecule components found in the PDB is distributed via the ftp archive as an external reference file. Small molecule annotation in the PDB also includes information about ligand-binding sites and about covalent and other linkages between ligands and macromolecules. During the remediation of the peptide-like antibiotics and inhibitors present in the PDB archive in 2011, it became clear that additional annotation was required for consistent representation of these molecules, which are quite often composed of several sequential subcomponents including modified amino acids and other chemical groups. The connectivity information of the modified amino acids is necessary for correct representation of these biologically interesting molecules. The combined information is made available via a new resource called the Biologically Interesting molecules Reference Dictionary, which is complementary to the CCD and is now routinely used for annotation of peptide-like antibiotics and inhibitors.
Rhizosphere, the narrow region surrounding plant roots directly influenced by root exudates and the root associated microbiome, plays an important role in plant productivity and the rhizosphere is well known for stimulating microbial metabolic activities. How microbial communities interact to form stable, metabolically interconnected functional communities is an area of intense interest. The question remains on how microbially produced secreted molecules that function as intercellular communication signals shape the structure and function of microbial communities. Our goal is to detect and quantify signal molecules produced by microbes or plants in the root‐soil environment, spatially and temporarily. As a proof‐of‐concept, we are imaging diffusible extracellular microbial metabolites involved in a bacteria‐bacteria communication process called quorum‐sensing. Quorum‐sensing relies on the accumulation of high concentrations of signal molecules in the environment to control bacterial gene expression, influencing rhizosphere colonization and plant health. Local concentration of quorum sensing molecules are determined using aptamer based sensors. Aptamers that can specifically bind the desired signal molecules are selected through SELEX and immobilized on the surface of nano‐porous membranes. Binding of the signal molecules and aptamer covered surface results in changes in surface charge distribution and steric hinderance and thus modifying the transmembrane ionic transport. Changes in transmembrane impedance can be measured through electrochemical impedance spectroscopy methods to monitor local concentrations of signal molecules. Sensor responses were determined for different concentrations of signal molecules and results showed detection of C4‐HSL in a soil‐mimic solution with K D of 10 nM. We demonstrate that the quorum‐sensing signal molecule C4‐homoserine lactone and (C4‐HSL) can rapidly diffuse in a soil‐mimic gel, providing evidence for our use of a soil‐mimic for further aptasensor development and validation. The sensors were then inserted into soil mimic gel for monitoring C4‐HSL diffusion and the resulted impedance changes were used to determine the C4‐HSL concentration at different positions in the gel. Measurements of local C4‐HSL concentrations variation and numerical solution of diffusion equation were used to create 4D images of C4‐HSL molecule diffusion in the soil‐mimic gel.
This project is focused on the use of single-molecule high spatial and temporal resolved techniques to study molecular dynamics in condensed phase and at interfaces, especially, the complex reaction dynamics associated with electron and energy transfer rate processes. The complexity and inhomogeneity of the interfacial ET dynamics often present a major challenge for a molecular level comprehension of the intrinsically complex systems, which calls for both higher spatial and temporal resolutions at ultimate single-molecule and single-particle sensitivities. Combined single-molecule spectroscopy and electrochemical atomic force microscopy approaches are unique for heterogeneous and complex interfacial electron transfer systems because the static and dynamic inhomogeneities can be identified and characterized by studying one molecule at a specific nanoscale surface site at a time. The goal of our project is to integrate and apply these spectroscopic imaging and topographic scanning techniques to measure the energy flow and electron flow between molecules and substrate surfaces as a function of surface site geometry and molecular structure. We have been primarily focusing on studying interfacial electron transfer under ambient condition and electrolyte solution involving both single crystal and colloidal TiO 2 and related substrates. The resulting molecular level understanding of the fundamental interfacial electron transfer processes will be important for developing efficient light harvesting systems and broadly applicable to problems in fundamental chemistry and physics. We have made significant advancement on deciphering the underlying mechanism of the complex and inhomogeneous interfacial electron transfer dynamics in dyesensitized TiO 2 nanoparticle systems that strongly involves with and regulated by molecule-surface interactions. We have studied interfacial electron transfer on TiO 2 nanoparticle surfaces by using ultrafast single-molecule spectroscopy and electrochemical AFM metal tip scanning microscopy, focusing on understanding the interfacial electron transfer dynamics at specific nanoscale electron transfer sites with high-spatially and temporally resolved topographic-and-spectroscopic characterization at individual molecule basis, characterizing single-molecule rate processes, reaction driving force, and molecule-substrate electronic coupling. One of the most significant characteristics of our new approach is that we are able to interrogate the complex interfacial electron transfer dynamics by actively pin-point energetic manipulation of the surface interaction and electronic couplings, beyond the conventional excitation and observation.
Structural characterization of ions in the gas phase is facilitated by measurement of ion collision cross sections (CCS) using techniques such as ion mobility spectrometry. Further information is gained from CCS measurement when comparison is made between measurements and accurately predicted CCSs for model ion structures and the gas in which measurements are made. While diatomic gases, namely molecular nitrogen and air, are being used in CCS measurement with increasingly prevalency, the majority of studies in which measurements are compared to predictions use models in which gas molecules are spherical or non-rotating, which is not necessarily appropriate for diatomic gases. Here, we adapt a momentum transfer based CCS calculation approach to consider rotating, diatomic gas molecule collisions with polyatomic ions, and compare CCS predictions with a diatomic gas molecule to those made with a spherical gas molecular for model spherical ions, tetra-alkylammonium ions, and multiply charged polyethylene glycol ions. CCS calculations are performed using both specular-elastic and diffuse-inelastic collisions rules, which mimic negligible internal energy exchange and complete thermal accommodation, respectively, between gas molecule and ion. The influence of the long range ion-induced dipole potential on calculations is also examined with both gas molecule models. In large part we find that CCSs calculated with specular-elastic collision rules decrease, while they increase with diffuse-inelastic collision rules when using diatomic gas molecules. Results clearly show the structural model of both the ion and gas molecule, the potential energy field between ion and gas molecule, and finally the modeled degree of kinetic energy exchange between ion and gas molecule internal energy are coupled to one another in CCS calculations, and must be considered carefully to obtain results which agree with measurements.
Highlights: • We evaluated both single molecule binding ability and expression level of 4 ICAM-1 mutations. • AFM was used to measure single-molecule binding ability on living cells. • The SNP of ICAM-1 may induce changes in expressions rather than single-molecule binding ability. - Abstract: Atherosclerosis (As) is characterized by chronic inflammation and is a major cause of human mortality. ICAM-1-mediated adhesion of leukocytes in vessel walls plays an important role in the pathogenesis of atherosclerosis. Two single nucleotide polymorphisms (SNPs) of human intercellular adhesion molecule-1 (ICAM-1), G241R and K469E, are associated with a number of inflammatory diseases. SNP induced changes in ICAM-1 function rely not only on the expression level but also on the single-molecule binding ability which may be affected by single molecule conformation variations such as protein splicing and folding. Previous studies have shown associations between G241R/K469E polymorphisms and ICAM-1 gene expression. Nevertheless, few studies have been done that focus on the single-molecule forces of the above SNPs and their ligands. In the current study, we evaluated both single molecule binding ability and expression level of 4 ICAM-1 mutations – GK (G241/K469), GE (G241/E469), RK (R241/K469) and RE (R241/E469). No difference in adhesion ability was observed via cell adhesion assay or atomic force microscopy (AFM) measurement when comparing the GK, GE, RK, or RE genotypes of ICAM-1 to each other. On the other hand, flow cytometry suggested that there was significantly higher expression of GE genotype of ICAM-1 on transfected CHO cells. Thus, we concluded that genetic susceptibility to diseases related to ICAM-1 polymorphisms, G241R or K469E, might be due to the different expressions of ICAM-1 variants rather than to the single-molecule binding ability of ICAM-1.