Ingenieurwissenschaften und zugeordnete Tätigkeiten
Filtern
Erscheinungsjahr
Dokumenttyp
- Zeitschriftenartikel (1905) (entfernen)
Sprache
- Englisch (1905) (entfernen)
Referierte Publikation
- ja (1905) (entfernen)
Schlagworte
- Additive manufacturing (73)
- Quantum yield (64)
- Mechanochemistry (62)
- SAXS (61)
- Fluorescence (59)
- Nanoparticle (45)
- Lifetime (44)
- Microstructure (44)
- Nanoparticles (42)
- MALDI-TOF MS (41)
Organisationseinheit der BAM
- 6 Materialchemie (567)
- 5 Werkstofftechnik (301)
- 9 Komponentensicherheit (289)
- 6.3 Strukturanalytik (241)
- 8 Zerstörungsfreie Prüfung (193)
- 1 Analytische Chemie; Referenzmaterialien (180)
- 7 Bauwerkssicherheit (137)
- 8.5 Röntgenbildgebung (136)
- 1.2 Biophotonik (111)
- 5.1 Mikrostruktur Design und Degradation (110)
Paper des Monats
- ja (42)
The ionic liquid 1,3-dimethyl-imidazolium-dimethylphosphate ([MMIM]+[DMP]−) was analyzed using (hard) x-ray photoelectron spectroscopy.
Here, XPS and HAXPES spectra are shown in comparison. For the acquisition of the XPS spectra, monochromatic Al Kα radiation at 1486.6 eV was used, while for the acquisition of the HAXPES spectra, monochromatic Cr Kα radiation at 5414.8 eV was applied. Here, survey scans and high-resolution spectra of P 2p, P 2s, C 1s, O 1s, and N 1s for both methods and P 1s, P KL2,3L2,3, and P KL1L2,3 for HAXPES are shown.
1-Propyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide (Solarpur®), an ionic liquid was purchased from Merck (formerly Sigma Aldrich), was analyzed using hard x-ray photoelectron spectroscopy (HAXPES). The liquid is UHV stable, vertically and laterally homogeneous, and is easy to clean; thus, it can be used as a reference material. The HAXPES spectra of Solarpur® obtained using monochromatic Cr Kα radiation at 5414.8 eV include a survey scan, high-resolution spectra of C 1s, O 1s, N 1s, S 2p, S 1s, S 2s, F 1s, and S KLL.
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.
A novel cop olyme r based on supramolecular motif2,6-diaminopyridin e and water-soluble acrylamide, poly[N-(6-ace tamidopyridin-2-yl) acrylamide-co-acrylamide], was synthe-size d via rev ersible addi tion–fragmentation chain transfer (RAFT)polymerization with various monomer compositions. The thermo-respon sive behavior of the copolymers was studied by turbidime-try and dynamic light scattering (DLS). The obtained copolymersshowed an upper critical solution temperature (UCST)-typ e phasetransition behavior in water and electrolyte solution. The phasetransition temperature was found to increase with decreasingam ount of acrylamide in the copolymer and increasing concentra-tion of the solution. Furth ermore, the phase transition temperatureva ried in aqueous solutions of electrolytes according to the naturean d concentration of the electrolyte in accordance with theHoffmeister series. A dramatic solvent isotope effect on thetransition temperature was o bserved in this study, as the transitiontemperature was almost 10–12C higher in D2OthaninH2Oatthesame concentration and acrylamide co mposition. The size of theaggregates below the transition temperature was larger in D2Ocompared to that in H2O that can be explained by deuterium iso-tope effect. The thermoresponsive behavior of the copolymers wasalso investigated in different cell medium and found to be exhibitedUCST-type phase transition behavior in different cell medium.Such behavior of the copo lyme rs can be useful in many a pplica-tions including biomedical, microfluidics, optical materials, and indrug delivery.
AbstractThis work addresses the critical need for multifunctional materials and substrate‐independent high‐precision surface modification techniques that are essential for advancing microdevices and sensing elements. To overcome existing limitations, the versatility of mussel‐inspired materials (MIMs) is combined with state‐of‐the‐art multiphoton direct laser writing (DLW) microfabrication. In this way, 2D and 3D MIM microstructures of complex designs are demonstrated with sub‐micron to micron resolution and extensive post‐functionalization capabilities. This study includes polydopamine (PDA), mussel‐inspired linear, and dendritic polyglycerols (MI‐lPG and MI‐dPG), allowing their direct microstructure on the substrate of choice with the option to tailor the patterned topography and morphology in a controllable manner. The functionality potential of MIMs is demonstrated by successfully immobilizing and detecting single‐stranded DNA on MIM micropattern and nanoarray surfaces. In addition, easy modification of MIM microstructure with silver nanoparticles without the need of any reducing agent is shown. The methodology developed here enables the integration of MIMs in advanced applications where precise surface functionalization is essential.
2D evaluation of spectral LIBS data derived from heterogeneous materials using cluster algorithm
(2017)
Laser-induced Breakdown Spectroscopy (LIBS) is capable of providing spatially resolved element maps in regard to the chemical composition of the sample. The evaluation of heterogeneous materials is often a challenging task, especially in the case of phase boundaries. In order to determine information about a certain phase of a material, the need for a method that offers an objective evaluation is necessary. This paper will introduce a cluster algorithm in the case of heterogeneous building materials (concrete) to separate the spectral information of non-relevant aggregates and cement matrix. In civil engineering, the information about the quantitative ingress of harmful species like Cl−, Na+ and SO2−4 is of great interest in the evaluation of the remaining lifetime of structures (Millar et al., 2015; Wilsch et al., 2005). These species trigger different damage processes such as the alkali-silica reaction (ASR) or the chloride-induced corrosion of the reinforcement. Therefore, a discrimination between the different phases, mainly cement matrix and aggregates, is highly important (Weritz et al., 2006). For the 2D evaluation, the expectation-maximizationalgorithm (EM algorithm; Ester and Sander, 2000) has been tested for the application presented in this work. The method has been introduced and different figures of merit have been presented according to recommendations given in Haddad et al. (2014). Advantages of this method will be highlighted. After phase separation, non-relevant information can be excluded and only the wanted phase displayed. Using a set of samples with known and unknown composition, the EM-clustering method has been validated regarding to Gustavo González and Ángeles Herrador (2007).
Layer-by-layer additive manufacturing (AM) by means of laser-powder bed Fusion (L-PBF) offers many prospects regarding the design of lattice structures used, for example, in gas turbines. However, defects such as bulk porosity, Surface roughness, and re-entrant features are exacerbated in nonvertical structures, such as tilted struts. The characterization and quantification of these kinds of
defects are essential for the correct estimation of fracture and fatigue properties.
Herein, cylindrical struts fabricated by L-PBF are investigated by means of X-ray computed tomography (XCT), with the aim of casting light on the dependence of the three kinds of defects (bulk porosity, surface roughness, and re-entrant features) on the build angle. Innovative analysis methods are proposed to correlate shape and position of pores, to determine the angular-resolved Surface roughness, and to quantify the amount of re-entrant surface features, q. A meshing of the XCT surface enables the correlation of q with the classical Surface roughness Pa. This analysis leads to the conclusion that there is a linear correlation between q and Pa. However, it is conjectured that there must be a threshold of surface roughness, below which no re-entrant features can be build.
Laser metal deposition (LMD) is an established technology for two-dimensional surface coatings. It offers high deposition rates, high material flexibility, and the possibility to deposit material on existing components. Due to these features, LMD has been increasingly applied for additive manufacturing of 3D structures in recent years. Compared to previous coating applications, additive manufacturing of 3D structures leads to new challenges regarding LMD process knowledge. In this paper, the process steps for LMD as additive manufacturing technology are described. The experiments are conducted using titanium alloy Ti-6Al-4Vand Inconel 718. Only the LMD nozzle is used to create a shielding gas atmosphere. This ensures the high geometric flexibility needed for additive manufacturing, although issues with the restricted size and quality of the shielding gas atmosphere arise. In the first step, the influence of process parameters on the geometric dimensions of single weld beads is analyzed based on design of experiments. In the second step, a 3D build-up strategy for cylindrical specimen with high dimensional accuracy is described. Process parameters, travel paths, and cooling periods between layers are adjusted. Tensile tests show that mechanical properties in the as-deposited condition are close to wrought material. As practical example, the fir-tree root profile of a turbine blade is manufactured. The feasibility of LMD as additive technology is evaluated based on this component.
3D printing enables a better control over the microstructure of bone restoring constructs, addresses the challenges seen in the preparation of patient-specific bone scaffolds, and overcomes the bottlenecks that can appear in delivering drugs/growth factors promoting bone regeneration. Here, 3D printing is employed for the fabrication of an osteogenic construct made of hydrogel nanocomposites. Alginate dialdehyde-gelatin (ADA-GEL) hydrogel is reinforced by the incorporation of bioactive glass nanoparticles, i.e. mesoporous silica-calcia nanoparticles (MSNs), in two types of drug (icariin) loading. The composites hydrogel is printed as superhydrated composite constructs in a grid structure. The MSNs not only improve the mechanical stiffness of the constructs but also induce formation of an apatite layer when the construct is immersed in simulated body fluid (SBF), thereby promoting cell adhesion and proliferation. The nanocomposite constructs can hold and deliver icariin efficiently, regardless of its incorporation mode, either as loaded into the MSNs or freely distributed within the hydrogel. Biocompatibility tests showed that the hydrogel nanocomposites assure enhanced osteoblast proliferation, adhesion, and differentiation. Such optimum biological properties stem from the superior biocompatibility of ADA-GEL, the bioactivity of the MSNs, and the supportive effect of icariin in relation to cell Proliferation and differentiation. Taken together, given the achieved structural and biological properties and effective drug delivery capability, the hydrogel nanocomposites show promising potential for bone tissue engineering.
The Layerwise Slurry Deposition is a technology for the deposition of highly packed powder layers. A powder bed is achieved by depositing and drying layers of a ceramic suspension by means of a doctor blade. This deposition technique was combined with the binder jetting technology to develop a novel Additive Manufacturing technology, named LSD-print. The LSD-print was applied to a porcelain ceramic. It is shown that it was possible to produce parts with high definition, good surface finish and at the same time having physical and mechanical properties close to those of traditionally processed porcelain, e.g. by slip casting.
This technology shows high future potential for being integrated alongside traditional production of porce-lain, as it is easily scalable to large areas while maintaining a good definition. Both the Layerwise Slurry Deposition method and the binder jetting technologies are readily scalable to areas as large as > 1 m2.
A shape evolution approach based on the thermally activated self-organization of 3D printed parts into minimal surface area structures is presented. With this strategy, the present communication opposes currently established additive manufacturing strategies aiming to stipulate each individual volumetric element (voxel) of a part. Instead, a 3D structure is roughly defined in a 3D printing process, with all its advantages, and an externally triggered self-organization allows the formation of structural elements with a definition greatly exceeding the volumetric resolution of the printing process. For enabling the self-organization of printed objects by viscous flow of material, functionally graded structures are printed as rigid frame and melting filler. This approach uniquely combines the freedom in design, provided by 3D printing, with the mathematical formulation of minimal surface structures and the knowledge of the physical potentials governing self-organization, to overcome the paradigm which strictly orrelates the geometrical definition of 3D printed parts to the volumetric resolution of the printing process. Moreover, a transient liquid phase allows local programming of functionalities, such as the alignment of functional particles, by means of electric or magnetic fields.
The co-crystallisation of [NiEn3](NO3)2 (En = ethylenediamine) with Na2MoO4 and Na2WO4 from a water solution results in the formation of [NiEn3](MoO4)0.5(WO4)0.5 co-crystals. According to the X-ray diffraction analysis of eight single crystals, the parameters of the hexagonal unit cell (space group P–31c, Z = 2) vary in the following intervals: a = 9.2332(3)–9.2566(6); c = 9.9512(12)–9.9753(7) Å with the Mo/W ratio changing from 0.513(3)/0.487(3) to 0.078(4)/0.895(9). The thermal decomposition of [NiEn3](MoO4)0.5(WO4)0.5 individual crystals obtained by co-crystallisation was performed in He and H2 atmospheres. The ex situ X-ray study of thermal decomposition products shows the formation of nanocrystalline refractory alloys and carbide composites containing ternary Ni–Mo–W phases. The formation of carbon–nitride phases at certain stages of heating up to 1000 °C were shown.
A novel biomaterial comprising alginate dialdehyde-gelatine (ADA-GEL) hydrogel augmented by lysozyme loaded mesoporous cerium doped silica-calcia nanoparticles (Lys-Ce-MSNs) is 3D printed to create bioactive scaffolds. Lys-Ce-MSNs raise the mechanical stiffness of the hydrogel composite scaffold and induce surface apatite mineralization, when the scaffold is immersed in simulated body fluid (SBF). Moreover, the scaffolds can co-deliver bone healing (Ca and Si) and antioxidant ions (Ce), and Lys to achieve antibacterial (and potentially anticancer) properties. The nanocomposite hydrogel scaffolds can hold and deliver Lys steadily. Based on the in vitro results, the hydrogel nanocomposite containing Lys assured improved pre-osteoblast cell (MC3T3-E1) proliferation, adhesion, and differentiation, thanks to the biocompatibility of ADA-GEL, bioactivity of Ce-MSNs, and the stabilizing effect of Lys on the scaffold structure. On the other hand, the proliferation level of MG63 osteosarcoma cells decreased, likely due to the effect of Lys. Last but not least, cooperatively, alongside gentamicin (GEN), Lys brought about a proper antibacterial efficiency to the hydrogel nanocomposite scaffold against gram-positive and gram-negative bacteria. Taken together, ADA-GEL/Lys-Ce-MSN nanocomposite holds great promise for 3D printing of multifunctional hydrogel bone tissue engineering (BTE) scaffolds, able to induce bone regeneration, address infection, and potentially inhibit tumor formation and growth.
This study assesses the structural vulnerability of part of a later medieval earthen building at
Ambel (near Zaragoza, Spain), once a preceptory or monastic house belonging to the Military
Orders. An inspection of its morphology and materials coupled with the results of an extensive
campaign of static monitoring reveals marked structural inhomogeneities, the product of more
than a thousand years of construction, failure, and repair from the 10th century to the present
day. Building materials are inappropriately juxtaposed, there are discontinuities between construction
phases and fundamental concerns remain over the long-term stability of the structure.
The current condition of the structure is mainly influenced by structural discontinuities introduced
at the time of construction, the unintended consequences of repair and modification and the
material decay that has affected the base of the rammed earth walls. The overall findings of the
static monitoring show that there is no related damage, variations in crack widths are related to
the building seasonal cycle. While static analysis is an essential prerequisite before a suitable
maintenance program can be fully defined, this study argues that no evaluation of the structural
behavior of any historic building can afford to ignore its archaeological “biography” of modification
and repair.
There is no consensus on which hydration stoppage method is optimal to preserve the microstructure and mineral composition of samples, especially considering the specific aspects of different testing methods, such as TGA, MIP, or XRD. This paper presents a quantitative comparison between the most popular hydration stoppage strategies and parameters such as the sample piece size, the soaking time in a solvent, and the type, as examined on cement paste hydrated for 7 days. It was found that the carbonation appears either for samples smaller than 2.36 mm and bigger than 4.75 mm or samples soaked in a solvent for longer than 1 h. Fast solvent replacement leads to ettringite diminution and total pore volume increase. Among others, solvent replacement with subsequent gentle heating under a vacuum was found to be the most efficient, whereas it was experimentally demonstrated that isopropyl alcohol stops hydration faster than ethanol and acetone.
The mechanochemical formation of the ionic cocrystals of glucose (Glc) and sodium salts Glc2NaCl·H2O (1) and Glc2NaX (X = Br (2), I (3)) is presented. Products are formed by co-milling Glc with three sodium salts (NaCl, NaBr, NaI). The ionic cocrystals were obtained under both neat grinding and liquid-assisted grinding conditions, the later found to accelerate the reaction kinetics. The crystal structures of the ionic cocrystals (2) and (3) were solved from powder X-ray diffraction data. The structure solution contrasts with the structure of Glc2NaCl·H2O (1) where the electron density at three halide crystallographic sites is modeled as of being the intermediate between water molecule and a chloride ion. The reaction pathways of the three ionic cocrystals were investigated in real time using our tandem approach comprising a combination of in situ synchrotron powder X-ray diffraction and Raman spectroscopy. The results indicate the rapid formation of each cocrystal directly from their respective starting materials without any intermediate moiety formation. The products were further characterized by DTA-TG and elemental analysis.
Lake Magadi, East African Rift Valley, is a hyperalkaline and saline soda lake highly enriched in Na+, K+, CO32–, Cl–, HCO3–, and SiO2 and depleted in Ca2+ and Mg2+, where thick evaporite deposits and siliceous sediments have been forming for 100 000 years. The hydrogeochemistry and the evaporite deposits of soda lakes are subjects of growing interest in paleoclimatology, astrobiology, and planetary sciences. In Lake Magadi, different hydrates of sodium carbonate/bicarbonate and other saline minerals precipitate. The precipitation sequence of these minerals is a key for understanding the hydrochemical evolution, the paleoenvironmental conditions of ancient evaporite deposits, and industrial crystallization. However, accurate determination of the precipitation sequence of these minerals was challenging due to the dependency of the different hydrates on temperature, water activity, pH and pCO2, which could induce phase transformation and secondary mineral precipitation during sample handling. Here, we report a comprehensive methodology applied for monitoring the evaporitic mineral precipitation and hydrochemical evolution of Lake Magadi. Evaporation and mineral precipitations were monitored by using in situ video microscopy and synchrotron X-ray diffraction of acoustically levitated droplets. The mineral patterns were characterized by ex situ Raman spectroscopy, X-ray diffraction, and scanning electron microscopy. Experiments were coupled with thermodynamic models to understand the evaporation and precipitation-driven hydrochemical evolution of brines. Our results closely reproduced the mineral assemblages, patterns, and textural relations observed in the natural setting. Alkaline earth carbonates and fluorite were predicted to precipitate first followed by siliceous sediments. Among the salts, dendritic and acicular trona precipitate first via fractional crystallization─reminiscent of grasslike trona layers of Lake Magadi. Halite/villiaumite, thermonatrite, and sylvite precipitate sequentially after trona from residual brines depleted in HCO3–. The precipitation of these minerals between trona crystals resembles the precipitation process observed in the interstitial brines of the trona layers. Thermonatrite precipitation began after trona equilibrated with the residual brines due to the absence of excess CO2 input. We have shown that evaporation and mineral precipitation are the major drivers for the formation of hyperalkaline, saline, and SiO2-rich brines. The discrepancy between predicted and actual sulfate and phosphate ion concentrations implies the biological cycling of these ions. The combination of different in situ and ex situ methods and modeling is key to understanding the mineral phases, precipitation sequences, and textural relations of modern and ancient evaporite deposits. The synergy of these methods could be applicable in industrial crystallization and natural brines to reconstruct the hydrogeochemical and hydroclimatic conditions of soda lakes, evaporite settings, and potentially soda oceans of early Earth and extraterrestrial planets.
Physical adsorption at cryogenic temperature (cryoadsorption) is a reversible mechanism that can reduce the pressure of conventional compressed gas storage systems. Metal–organic framework (MOF) materials are remarkable candidates due to the combination of high specific surface area and density which, in some cases, provide a high volumetric storage capacity. However, such extensive use of MOFs for this application requires the selection of affordable structures, easy to produce and made from feasible metallic and organic components. Herein, we introduce a MOF database detailing the crystallographic and porous properties of 3600 existing MOFs made from industrially relevant metals and their organic composition. The comparison of the available minimum costs of linkers allowed the creation of a database to select affordable structures with high potential for volumetric hydrogen storage by cryoadsorption, considering their composition based on individual or mixed building blocks. A user interface, available online, facilitates the selection of MOFs based on the properties or names of structures and linkers.
Introducing a single silicon nanowire with a known orientation and dimensions to a specific layout location constitutes a major challenge. The challenge becomes even more formidable, if one chooses to realize the task in a monolithic fashion with an extreme topography, a characteristic of microsystems. The need for such a monolithic integration is fueled by the recent surge in the use of silicon nanowires as functional building blocks in various electromechanical and optoelectronic applications. This challenge is addressed in this work by introducing a top-down, silicon-on-insulator technology. The technology provides a pathway for obtaining well-controlled silicon nanowires along with microstructures up to a three-order-of-magnitude scale difference. A two-step etching process is developed, where the first shallow etch defines a nanoscale protrusion on the wafer surface. After applying a conformal protection on the protrusion, a deep etch step is carried out forming the surrounding microscale features. A minimum nanowire cross-section of 35 nm by 168 nm is demonstrated in the presence of an etch depth of 10 m. All cross-sectional features are characterized via transmission electron microscopy and linked to specific process steps. The technology allows control on all dimensional aspects along with the exact location and orientation of the silicon nanowire.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.