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The preparation of aminated monolayers with a controlled density of functional groups on silica surfaces through a simple vapor deposition process employing different ratios of two suitable monoalkoxysilanes, (3-aminopropyl)diisopropylethoxysilane (APDIPES) and (3-cyanopropyl)dimethylmethoxysilane (CPDMMS), and advances in the reliable quantification of such tailored surfaces are presented here. The one-step codeposition process was carried out with binary silane mixtures, rendering possible the control over a wide range of densities in a single step. In particular, APDIPES constitutes the functional silane and CPDMMS the inert component. The procedure requires only small amounts of silanes, several ratios can be produced in a single batch, the deposition can be carried out within a few hours and a dry atmosphere can easily be employed, limiting self-condensation of the silanes. Characterization of the ratio of silanes actually bound to the surface can then be performed in a facile manner through contact angle measurements using the Cassie equation. The reliable estimation of the number of surface functional groups was approached with a dual-mode BODIPY-type fluorescence label, which allows quantification by fluorescence and XPS on one and the same sample. We found that fluorescence and XPS signals correlate over at least 1 order of magnitude, allowing for a direct linking of quantitative fluorescence analysis to XPS quantification. Employment of synchrotron-based methods (XPS; reference-free total reflection X-ray fluorescence, TXRF) made the traceable quantification of surface functional groups possible, providing an absolute reference for quantitative fluorescence measurements through a traceable measurement chain.
Low temperature functionalization of two-dimensional boron nitride for electrochemical sensing
(2019)
Two-dimensional hexagonal boron nitride(h-BN)as an emerging nanomaterial exhibits uniquephysicochemical properties, making it suitable candidate for a wide spectrum of applications.However, due to its poor functionality, the processability of this nanomaterial is low. In this work, wereport on a straightforward and scalable approach for the functionalization of h-BN by nitrene[2+1]cycloaddition at room temperature. The triazine-functionalized h-BN(Trz-BNs)showed ahigh reactivity toward nucleophiles, through which post-modifications are performable. The post-modification of Trz-BNs by L-cysteine was studied using cyclic voltammetry and differential pulsevoltammetry. Taking advantage of the scalable and straightforward functionalization as well as abilityof triazine functional groups for the controlled post-modifications, Trz-BNs is a promisingnanoplatform for a wide range of future applications.
The chemical composition of surfaces functionalized with self-assembled monolayers (SAMs) is an important parameter that determines their performance in a broad range of applications, from immobilizing molecular machines to initiation and growth control of MOFs (Metal-Organic Frameworks). In this article, a critical Survey of XPS (X-ray photoelectron spectroscopy) and NEXAFS (near edge X-ray absorption fine structure) spectroscopy data for pyridine-functionalized monolayers on gold surfaces is presented to compile correlations that have been indiscernible before. Monolayers with aromatic backbones are compared to monolayers with aliphatic backbones.
Monolayers with pyridine end-groups are compared to mixed monolayers formed terpyridine-functionalized by molecules end-groups and non-functionalized molecules. Thiol-oxidation during ageing of the SAMs in air is addressed. And finally, the addressability of the SAMs for the deposition of metal-ions and organic molecules is investigated and compared. This work consequently delivers a comprehensive set of spectroscopic data of (ter-)pyridine-terminated SAMs and their performance as template for the preparation of functional multilayers of macrocycles exhibiting a preferential orientation.
Imaging and small-spot (small area) XPS have become increasingly important components of surface chemical analysis during the last three decades, and its use is growing. Some ambiguity in the use of terminology, understanding of concepts, and lack of appropriate reference materials leads to confusing and not always reproducible data. In this paper, it is shown that by using existing knowledge, appropriate test specimens, and standardized approaches, problems of comparability and such reproducibility issues recently observed for XPS data reported in the scientific literature can be overcome. The standardized methods of ISO 18516:2019, (i) the straight-edge, (ii) the narrow-line, and (iii) the grating method, can be used to characterize and compare the lateral resolution achieved by imaging XPS instruments and are described by reporting examples. The respective measurements are made using new test specimens. When running an XPS instrument in the small-spot (small area) mode for a quantitative analysis of a feature of interest, the question arises as to what contribution to the intensity originates from outside the analysis area. A valid measurement approach to control the intensity from outside the nominal analysis area is also described. As always, the relevant resolution depends on the specific question that needs to be addressed. The strengths and limitations of methods defining resolution are indicated.
The certified reference material BAM-L200, a nanoscale stripe pattern for length calibration and specification of lateral resolution, is described. BAM-L200 is prepared from a cross-sectioned epitaxially grown layer stack of AlxGa1-xAs and InxGa1 xAs on a GaAs substrate. The surface of BAM-L200 provides a flat pattern with stripe widths ranging down to 1 nm. Calibration distances, grating periods and stripe widths have been certified by TEM with traceability to the length unit. The combination of gratings, isolated narrow stripes and sharp edges of wide stripes offers a plenty of options for the determination of lateral resolution, sharpness and calibration of length scale at selected settings of imaging surface analytical instruments. The feasibility of the reference material for an analysis of the lateral resolution is demonstrated in detail by evaluation of ToF-SIMS, AES and EDX images. Other applications developed in the community are summarized, too. BAM-L200 fully supports the implementation of the revised International Standard ISO 18516 (in preparation) which is based on knowledge outlined in the Technical Report ISO/TR 19319:2013.
The sonication process is commonly used for de-agglomerating and dispersing nanomaterials in aqueous based media, necessary to improve homogeneity and stability of the suspension. In this study, a systematic step-wise approach is carried out to identify optimal sonication conditions in order to achieve a stable dispersion. This approach has been adopted and shown to be suitable for several nanomaterials (cerium oxide, zinc oxide, and carbon nanotubes) dispersed in deionized (DI) water. However, with any change in either the nanomaterial type or dispersing medium, there needs to be optimization of the basic protocol by adjusting various factors such as sonication time, power, and sonicator type as well as temperature rise during the process. The approach records the dispersion process in detail. This is necessary to identify the time Points as well as other above-mentioned conditions during the sonication process in which there may be undesirable changes, such as damage to the particle surface thus affecting surface properties. Our goal is to offer a harmonized approach that can control the Quality of the final, produced dispersion. Such a guideline is instrumental in ensuring dispersion quality repeatability in the nanoscience community, particularly in the field of nanotoxicology.
Magnetic iron oxide nanoparticle clusters (mnpc) coated with organic stabilizers were investigated using scanning transmission x-ray microscopy (STXM). Simultaneous surface and bulk sensitive Fe L3 edge absorption spectra, obtained using a photomultiplier tube and a channeltron, were used to detect subtle changes in the oxidation state in the surface and bulk of Iron Oxide mnpc.
The effectiveness of this mode of STXM operation is demonstrated for These nanoparticle clusters.
The international ISO Standard 20579‐4, dealing with the history and preparation of nano‐objects for surface analysis, has been developed to help address some of the replication and reproducibility issues caused by the fundamental nature of nanoobjects.
Although all types of samples requiring surface analysis need thoughtful preparation, nano‐objects, for which many properties are controlled by their surfaces, present additional challenges in order to avoid variations and artefacts due to the handling and preparation of materials prior to analysis. This international standard is part of a series of standards related to preparation of samples for surface chemical analysis. Parts 1 and 2 of ISO Standard series 20579 address general issues that apply to many samples. Part 3, which is still in development, will focus on biomaterials. Part 4 specifically considers issues that arise due to the inherent nature of nano‐objects.
Because of sensitivity to their environment, the standard indicates the minimum Information that needs to be reported about the handling and preparation of nano‐objects prior to surface analysis. This information should become part of sample provenance information that helps assure the reliability and usefulness of data obtained from surface‐analysis in the context of the synthesis, processing, and analysis history of a batch of material. Application of this standard can help address reproducibility and traceability issues associated with synthesis, processing, and characterization of nano‐objects in research and commercial applications.
Mechanically interlocked molecules (MIMs) such as rotaxanes and catenanes are capable of mechanical motion on the nanoscale and are therefore promising prototypes for molecular machines in recent nanotechnology. However, most of the existing examples are isotropically distributed in solution, which prohibits concerted movement and with it the generation of macroscopic effects. Thus, arranging them in ordered arrays is of huge interest in recent research. We report the deposition of quite densely packed multilayers of tetralactam macrocycles on gold surfaces by metal-coordinated layer-by-layer self-assembly. Linear dichroism effects in angle-resolved NEXAFS spectra indicate a preferential orientation of the macrocycles. The sequence of the metal ions can be programmed by the use of different transition metal ions at each deposition step. Additionally, reversible on-surface pseudorotaxane formation was successfully realized by repeated uptake and release of axle molecules inside the macrocycles cavities.
Detection of suspended nanoparticles with near-ambient pressure x-ray photoelectron spectroscopy
(2017)
Two systems of suspended nanoparticles have been studied with near-ambient pressure x-ray photoelectron spectroscopy: silver nanoparticles in water and strontium fluoride—calcium fluoride core-shell nanoparticles in ethylene glycol. The corresponding dry samples were measured under ultra high vacuum for comparison. The results obtained under near-ambient pressure were overall comparable to those obtained under ultra high vacuum, although measuring silver nanoparticles in water requires a high pass energy and a long acquisition time. A shift towards higher binding energies was found for the silver nanoparticles in aqueous Suspension compared to the corresponding dry sample, which can be assigned to a change of surface potential at the water-nanoparticle interface. The shell-thickness of the core-shell nanoparticles was estimated based on simulated spectra from the National Institute of Standards and Technology database for simulation of electron spectra for surface analysis. With the instrumental set-up presented in this paper, nanoparticle suspensions in a suitable Container can be directly inserted into the analysis chamber and measured without prior sample preparation.
Magnetic iron oxide nanoparticle clusters (mnpc) coated with organic stabilizers were investigated using scanning transmission x-ray microscopy (STXM). Simultaneous surface and bulk sensitive Fe L₃ edge absorption spectra, obtained using a photomultiplier tube and a channeltron, were used to detect subtle changes in the oxidation state in the surface and bulk of Iron Oxide mnpc. The effectiveness of this mode of STXM operation is demonstrated for these nanoparticle clusters.
Software-driven scientific workflows are often characterized by a complex interplay of various pieces of software executed in a particular order. The output of a computational step may serve as input to a subsequent computation, which requires them to be processed sequentially with a proper mapping of outputs to inputs. Other computations are independent of each other and can be executed in parallel. Thus, one of the main tasks of a workflow tool is a proper and efficient scheduling of the individual processing steps.
Each processing step, just as the workflow itself, typically processes some input and produces output data. Apart from changing the input data to operate on, processing steps can usually be configured by a set of parameters to change their behavior. Moreover, the behavior of a processing step is determined by its source code and/or executable binaries/packages that are called within it. Beyond this, the computation environment not only has a significant influence on its behavior, but is also crucial in order for the processing step to work at all. The environment includes the versions of the interpreters or compilers, as well as all third-party libraries and packages that contribute to the computations carried out in a processing step.
In this paper, the imperialist competitive optimization algorithm is improved by damage functions to detect damage in a model steel frame test structure for offshore applications. A finite element model of the test structure is developed, validated and updated using the proposed method. As there are much more design variables, which are related to the stiffness of each finite element than the measured mode shapes, the problem is underdetermined. Therefore, damage functions are used to regularize the problem and decrease the number of design variables. A new objective function is proposed for the algorithm using the mode shapes and their l1 norm. The first ten measured mode shapes are used to solve the problem. It is shown that the proposed method is capable of predicting the damage locations with acceptable accuracy.
Biomedical applications, including functional biomaterials, carbohydrate-arrays, and glycan-based biosensors.
The chemistry of glycan immobilization plays an essential role in the bioavailability and function of surface bound carbohydrate moieties. For biomedical applications the stability over time (shelf life) of glycan arrays is a crucial factor. Herein we report on approaches for surface and interface characterization relevant to the needs of production of glycan microarrays which were tested using model carbohydrate surfaces. For detailed characterization of glycan model surfaces we used a combination of X-ray photoelectron spectroscopy (XPS), near edge X-ray absorption fine structure spectroscopy (NEXAFS) and ToF SIMS which are complementary techniques of surface chemical analysis. Links to fluorescence spectroscopy often used for characterization in the microarray community were established as well. In detail, amine-reactive silicon oxide and glass surfaces were used for anchoring oligosaccharides with an amino linker. The amount of surface bound carbohydrates was estimated by X-ray photoelectron spectroscopy (XPS). Glycan immobilization was investigated using lectins, which are glycan-binding molecules. A shelf life study of model glycan microarrays on epoxy-coated glass surfaces was done over a period of 160 days under different storage conditions utilizing fluorescence, ToF-SIMS and XPS analysis. It was shown that glycan activity of the models used can be maintained at least for half a year of storage at 4 °C.
The fluorolytic sol–gel synthesis is applied with the intention to obtain two different types of core–shell nanoparticles, namely, SrF2–CaF2 and CaF2–SrF2. In two separate fluorination steps for core and shell formation, the corresponding metal lactates are reacted with anhydrous HF in ethylene glycol. Scanning transmission electron microscopy (STEM) and dynamic light scattering (DLS) confirm the formation of particles with mean dimensions between 6.4 and 11.5 nm. The overall chemical composition of the particles during the different reaction steps is monitored by quantitative Al Kα excitation X-ray photoelectron spectroscopy (XPS). Here, the formation of stoichiometric metal fluorides (MF2) is confirmed, both for the core and the final core–shell particles. Furthermore, an in-depth analysis by synchrotron radiation XPS (SR-XPS) with tunable excitation energy is performed to confirm the core–Shell character of the nanoparticles. Additionally, Ca2p/Sr3d XPS intensity ratio in-Depth profiles are simulated using the software Simulation of Electron Spectra for Surface Analysis (SESSA). In principle, core–shell like particle morphologies are formed but without a sharp interface between calcium and strontium containing phases.
Surprisingly, the in-depth chemical distribution of the two types of nanoparticles is equal within the error of the experiment. Both comprise a SrF2-rich core domain and CaF2-rich shell domain with an intermixing zone between them. Consequently, the internal morphology of the final nanoparticles seems to be independent from the synthesis chronology.
Small-area/spot photoelectron spectroscopy (SAXPS) is a powerful tool for the investigation of small surface features like microstructures of electronic devices, sensors or other functional surfaces, and so forth. For evaluating the quality of such microstructures, it is often crucial to know whether a small signal in a spectrum is an unwanted contamination of the field of view (FoV), defined by the instrument settings, or it originated from outside. To address this issue, the d80/20 parameter of a line scan across a chemical edge is often used. However, the typical d80/20 parameter does not give information on contributions from the long tails of the X-ray beam intensity distribution or the electron-optical system as defined by apertures. In the VAMAS TWA2 A22 project “Applying planar, patterned, multi-metallic samples to assess the impact of analysis area in surface-chemical analysis,” new test specimen was developed and tested. The here presented testing material consists of a silicon wafer substrate with an Au-film and embedded Cr circular and square spots with decreasing dimensions from 200 μm down to 5 μm. The spot sizes are traceable to the length unit due to size measurements with a metrological SEM. For the evaluation of the FoV, we determined the Au4f intensities measured with the center of the FoV aligned with the center of the spot and normalized to the Au4f intensity determined on the Au-film. With this test specimen, it was possible to characterize, as an example, the FoV of a Kratos AXIS Ultra DLD XPS instrument.
Numerical models built as virtual-twins of a real structure (digital-twins) are considered the future ofmonitoring systems. Their setup requires the estimation of unknown parameters, which are not directly measurable. Stochastic model identification is then essential, which can be computationally costly and even unfeasible when it comes to real applications. Efficient surrogate models, such as reduced-order method, can be used to overcome this limitation and provide real time model identification. Since their numerical accuracy influences the identification process, the optimal surrogate not only has to be computationally efficient, but also accurate with respect to the identified parameters. This work aims at automatically controlling the Proper Generalized Decomposition (PGD) surrogate’s numerical accuracy for parameter identification. For this purpose, a sequence of Bayesian model identification problems, in which the surrogate’s accuracy is iteratively increased, is solved with a variational Bayesian inference procedure. The effect of the numerical accuracy on the resulting posteriors probability density functions is analyzed through two metrics, the Bayes Factor (BF) and a criterion based on the Kullback-Leibler (KL) divergence. The approach is demonstrated by a simple test example and by two structural problems. The latter aims to identify spatially distributed damage, modeled with a PGD surrogate extended for log-normal random fields, in two different structures: a truss with synthetic data and a small, reinforced bridge with real measurement data. For all examples, the evolution of the KL-based and BF criteria for increased accuracy is shown and their convergence indicates when model refinement no longer affects the identification results.
In recent years, the use of simulation-based digital twins for monitoring and assessment of complex mechanical systems has greatly expanded. Their potential to increase the information obtained from limited data makes them an invaluable tool for a broad range of real-world applications. Nonetheless, there usually exists a discrepancy between the predicted response and the measurements of the system once built. One of the main contributors to this difference in addition to miscalibrated model parameters is the model error. Quantifying this socalled model bias (as well as proper values for the model parameters) is critical for the reliable performance of digital twins. Model bias identification is ultimately an inverse problem where information from measurements is used to update the original model. Bayesian formulations can tackle this task. Including the model bias as a parameter to be inferred enables the use of a Bayesian framework to obtain a probability distribution that represents the uncertainty between the measurements and the model. Simultaneously, this procedure can be combined with a classic parameter updating scheme to account for the trainable parameters in the original model.
This study evaluates the effectiveness of different model bias identification approaches based on Bayesian inference methods. This includes more classical approaches such as direct parameter estimation using MCMC in a Bayesian setup, as well as more recent proposals such as stat-FEM or orthogonal Gaussian Processes. Their potential use in digital twins, generalization capabilities, and computational cost is extensively analyzed.