Self-Assembled Monolayers for the Control of Intermolecular Interactions Towards New Sustainable Water Cleaning Agents

Self-assembled monolayers (SAMs) offer the possibility to modify the surface of materials in an astonishing range of options. The contribution of surfaces, in particular, becomes a dominating factor for the properties of nanomaterials, such as nanoparticles (NPs), and are in constant interaction with their environment. The wide range of possible chemical compositions of SAMs can control these interactions. This work focuses in detail on investigating such non-covalent interactions of SAMs. The aim is to understand the adsorption mechanisms between SAMs and organic substances to use the NPs developed here as efficient adsorbents for water purification. First, NPs are functionalized with different SAM-forming ligands (SFLs). The properties of the SAMs, such as their density on the surface, their effect on the whole hybrid SAM-NP system, and their dispersion properties, are investigated. The SAM-NPs are characterized in detail using thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), electrophoretic light scattering (ELS), and optical contact angle (OCA). For this purpose, phosphonic acid derivatives are used to attach the SAMs to the metal oxide surface of aluminum oxide () or iron oxide () NPs. The density of the SAM shows a pronounced dependency on the choice of SAM structure, particularly of the head group. The choice of SAM can change the wetting behavior of the dried SAM-NPs from superhydrophobic to hydrophilic. Most importantly, the chosen SAM can alter the zeta potential and thus the dispersion properties such as agglomeration. Although the zeta potential strongly depends on the adjusted pH value and all particles have similar maximum and minimum values, they show different isoelectric points (IEP). The IEP can be in both the acidic and basic range due to the choice of SAM, whereby partly fluorinated SFLs shift the IEP into the acidic range and positively charged SFLs shift the IEP into the basic range. Mixed SAMs consisting of two SFLs can adjust the mentioned properties even more precisely. Secondly, the adsorption behavior of different organic molecules on the SAM-NPs is investigated. During the work, different model molecules, also called water contaminants (CONs), are selected to study specific non-covalent interactions. The adsorption rates are determined by Steady-state absorption spectroscopy (UV-VIS), Steady-state fluorescence spectroscopy (FL), or High-performance liquid chromatography (HPLC), depending on the CON being analyzed. Polyaromatic hydrocarbons (PAHs) with increasing numbers of conjugated -systems show increased adsorption rates with increasing molecule size. The observation can be attributed to the increasing hydrophobicity of the PAHs. Likewise, an increased adsorption of PAHs is shown with increased hydrophobicity of the SAM-NPs used. Additionally, an increased adsorption rate onto phenyl-terminated SAMs can be observed, which indicates further interactions between the -systems of the SAM and the PAH. A second group of investigated CONs were charged molecules. Charged CONs show a pronounced preference depending on the NP surface charge, thus dependent on the pH value of the media. The number and type of charges have the most significant influence. In this way, it is possible to selectively remove one of the two substances from water samples containing a mixture of two different charged contaminants, depending on the SAM. However, if the surface charge is reduced by adjusting the pH value, hydrophobic interactions dominate the adsorption. The last chapter of the thesis investigates the interaction of mixed SAMs containing different ratios of alkyl SAMs and partially fluorinated SAMs with two amphiphiles (AM) containing either fluor or alkyl chains. These AMs combine hydrophobic and electrostatic interactions in separate parts of the molecule. The simultaneous addition of the two AMs creates an adsorption equilibrium of the two substances on the particle surface based on the forces at work. The acting forces thus influence the stoichiometric ratio of the AMs that adsorb. The selective accumulation of the respective chemically similar structures can be observed through chemical recognition. In the stoichiometric ratio of the two AMs, the proportion of the AM with fluorine chain is higher when a SAM-NP with fluorine SFL is used for adsorption. Conversely, the proportion of AM with an alkylated chain in the stoichiometric ratio is higher when an alkyl SFL is used for adsorption. This adsorption tendency can be controlled with the mixing ratio of the two SFLs on the NPs

Mrlje od polikvsternih spojeva u proizvodima za njegu

U praonicama se sve češće pojavljuju mrlje nakon pranja, najčešće na proizvodima od frotira koji se koriste u wellness centrima. Stručnjaci za industrijsko pranje i čišćenje iz Udruge za kvalitetu ispravne njege pranjem, uočili su tu problematiku i razradili su strategiju za prevenciju i korekciju takvih mrlja

Tunable Composition of Mixed Self‐Assembled Shell‐by‐Shell Structures on Nanoparticle Surfaces

Abstract The formation of mixed shell‐by‐shell (SbS) systems with tunable shell compositions is demonstrated by using molecular self‐assembly driven by chemical recognition motifs. Aluminum oxide nanoparticles (AlOx‐NPs) act as template surface for a self‐assembled monolayer (SAM) of either partially fluorinated fluoroalkyl or alkyl chained phosphonic acid derivatives or defined stoichiometric mixtures of those. By providing an equimolar mixture of corresponding fluoroalkyl and alkyl‐chained amphiphiles in water, the stoichiometry of underlaying mixed SAM on the NP‐surface preferentially directs the composition of the secondary self‐assembly. The composition of the shell‐by‐shell assemblies is studied by high performance liquid chromatography and fluorescence spectroscopy. The concept allows the formation of NP‐templated vesicle‐like bilayer structures, even consisting of orthogonal chain structures in tunable composition driven by chemical recognition and hydrophobic segregation

Remediation of charged organic pollutants—binding motifs for highly efficient water cleaning with nanoparticles

AbstractMany charged organic molecules behave as persistent and hazardous pollutants with harmful effects on human health and ecosystems. They are widely distributed related to their charged molecular structure that provides water solubility. In order to track the fate and behavior of such pollutants, charged dyes with specific absorption in the visible spectra serve as convenient model compounds. We provide a platform of smart adsorbers that efficiently remediate positively and negatively charged dyes (crystal violet and Amaranth) from water. Metal oxide nanoparticles serve as a core with an intrinsically large surface area. The surface potential was tuned towards positive or negative by decorating the cores with self‐assembled monolayers of dedicated long‐chained phosphonic acid derivatives. Selective remediation of the dyes was obtained with corresponding oppositely charged core‐shell nanoparticles. Mixed dye solution can be cleaned by a cascade approach or by applying both particle systems simultaneously. The removal efficiency was determined as a function of particle concentration via UV‐spectroscopy. The results of remediation experiments at different pH values and using superparamagnetic iron oxide nanoparticle cores lead to a simple process with recycling capability.</jats:p

Infrastructure for Detector Research and Development towards the International Linear Collider

The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture

Search for resonances decaying into photon pairs in 139 fb−1 of pp collisions at √s = 13 TeV with the ATLAS detector

Searches for new resonances in the diphoton final state, with spin 0 as predicted by theories with an extended Higgs sector and with spin 2 using a warped extra-dimension benchmark model, are presented using 139 fb−1 of √ s =13 TeV pp collision data collected by the ATLAS experiment at the LHC. No significant deviation from the Standard Model is observed and upper limits are placed on the production cross-section times branching ratio to two photons as a function of the resonance mass.publishedVersio

Random Amino Acid Mutations and Protein Misfolding Lead to Shannon Limit in Sequence-Structure Communication

The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions) and in structure (structural defects) trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a) sensitive to random errors and (b) restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials

Constant Velocity Constraints for Self-Supervised Monocular Depth Estimation

We present a new method for self-supervised monocular depth estimation. Contemporary monocular depth estimation methods use a triplet of consecutive video frames to estimate the central depth image. We make the assumption that the ego-centric view progresses linearly in the scene, based on the kinematic and physical properties of the camera. During the training phase, we can exploit this assumption to create a depth estimation for each image in the triplet. We then apply a new geometry constraint that supports novel synthetic views, thus providing a strong supervisory signal. Our contribution is simple to implement, requires no additional trainable parameter, and produces competitive results when compared with other state-of-the-art methods on the popular KITTI corpus

Measurement of the tt¯ tt¯ production cross section in pp collisions at √s = 13 TeV with the ATLAS detector

A measurement of four-top-quark production using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 139 fb−1 is presented. Events are selected if they contain a single lepton (electron or muon) or an opposite-sign lepton pair, in association with multiple jets. The events are categorised according to the number of jets and how likely these are to contain b-hadrons. A multivariate technique is then used to discriminate between signal and background events. The measured four-top-quark production cross section is found to be 26+17−15 fb, with a corresponding observed (expected) significance of 1.9 (1.0) standard deviations over the background-only hypothesis. The result is combined with the previous measurement performed by the ATLAS Collaboration in the multilepton final state. The combined four-top-quark production cross section is measured to be 24+7−6 fb, with a corresponding observed (expected) signal significance of 4.7 (2.6) standard deviations over the background-only predictions. It is consistent within 2.0 standard deviations with the Standard Model expectation of 12.0 ± 2.4 fb.publishedVersio

Search for R-parity-violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using √s = 13 TeV proton–proton collision data

A search for R-parity-violating supersymmetry in final states characterized by high jet multiplicity, at least one isolated light lepton and either zero or at least three b-tagged jets is presented. The search uses 139fb−1 of s√=13 TeV proton–proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the b-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine-learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine-learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.publishedVersio