Refine
Year of publication
- 2024 (25)
- 2023 (101)
- 2022 (132)
- 2021 (145)
- 2020 (157)
- 2019 (192)
- 2018 (168)
- 2017 (154)
- 2016 (154)
- 2015 (176)
- 2014 (166)
- 2013 (171)
- 2012 (154)
- 2011 (184)
- 2010 (179)
- 2009 (185)
- 2008 (155)
- 2007 (149)
- 2006 (160)
- 2005 (130)
- 2004 (161)
- 2003 (106)
- 2002 (130)
- 2001 (106)
- 2000 (108)
- 1999 (109)
- 1998 (99)
- 1997 (99)
- 1996 (81)
- 1995 (78)
- 1994 (86)
- 1993 (59)
- 1992 (54)
- 1991 (29)
- 1990 (39)
- 1989 (45)
- 1988 (57)
- 1987 (32)
- 1986 (19)
- 1985 (34)
- 1984 (22)
- 1983 (20)
- 1982 (29)
- 1981 (20)
- 1980 (36)
- 1979 (24)
- 1978 (34)
- 1977 (14)
- 1976 (13)
- 1975 (12)
- 1974 (3)
- 1973 (2)
- 1972 (2)
- 1971 (1)
- 1968 (1)
Document Type
- Article (3226)
- Conference Proceeding (1146)
- Part of a Book (184)
- Book (144)
- Doctoral Thesis (30)
- Patent (25)
- Other (9)
- Report (9)
- Working Paper (6)
- Lecture (5)
- Poster (4)
- Preprint (4)
- Talk (4)
- Master's Thesis (2)
- Bachelor Thesis (1)
- Contribution to a Periodical (1)
- Habilitation (1)
Language
- English (4801) (remove)
Keywords
- Biosensor (25)
- Finite-Elemente-Methode (12)
- Einspielen <Werkstoff> (10)
- CAD (8)
- civil engineering (8)
- Bauingenieurwesen (7)
- Blitzschutz (6)
- FEM (6)
- Gamification (6)
- Limit analysis (6)
- Shakedown analysis (6)
- avalanche (6)
- shakedown analysis (6)
- Clusterion (5)
- Earthquake (5)
- Enterprise Architecture (5)
- MINLP (5)
- solar sail (5)
- Air purification (4)
- Diversity Management (4)
Institute
- Fachbereich Medizintechnik und Technomathematik (1668)
- Fachbereich Elektrotechnik und Informationstechnik (693)
- IfB - Institut für Bioengineering (620)
- Fachbereich Energietechnik (579)
- INB - Institut für Nano- und Biotechnologien (555)
- Fachbereich Chemie und Biotechnologie (534)
- Fachbereich Luft- und Raumfahrttechnik (477)
- Fachbereich Maschinenbau und Mechatronik (278)
- Fachbereich Wirtschaftswissenschaften (207)
- Solar-Institut Jülich (164)
- Fachbereich Bauingenieurwesen (153)
- ECSM European Center for Sustainable Mobility (79)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (67)
- Nowum-Energy (28)
- Fachbereich Gestaltung (25)
- Institut fuer Angewandte Polymerchemie (23)
- Sonstiges (21)
- Fachbereich Architektur (20)
- Freshman Institute (18)
- Kommission für Forschung und Entwicklung (18)
Magnetic nanoparticles (MNPs) are used as therapeutic and diagnostic agents for local delivery of heat and image contrast enhancement in diseased tissue. Besides magnetization, the most important parameter that determines their performance for these applications is their magnetic relaxation, which can be affected when MNPs immobilize and agglomerate inside tissues. In this letter, we investigate different MNP agglomeration states for their magnetic relaxation properties under excitation in alternating fields and relate this to their heating efficiency and imaging properties. With focus on magnetic fluid hyperthermia, two different trends in MNP heating efficiency are measured: an increase by up to 23% for agglomerated MNP in suspension and a decrease by up to 28% for mixed states of agglomerated and immobilized MNP, which indicates that immobilization is the dominant effect. The same comparatively moderate effects are obtained for the signal amplitude in magnetic particle spectroscopy.
Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles’ magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.
Many efforts are made worldwide to establish magnetic fluid hyperthermia (MFH) as a treatment for organ-confined tumors. However, translation to clinical application hardly succeeds as it still lacks of understanding the mechanisms determining MFH cytotoxic effects. Here, we investigate the intracellular MFH efficacy with respect to different parameters and assess the intracellular cytotoxic effects in detail. For this, MiaPaCa-2 human pancreatic tumor cells and L929 murine fibroblasts were loaded with iron-oxide magnetic nanoparticles (MNP) and exposed to MFH for either 30 min or 90 min. The resulting cytotoxic effects were assessed via clonogenic assay. Our results demonstrate that cell damage depends not only on the obvious parameters bulk temperature and duration of treatment, but most importantly on cell type and thermal energy deposited per cell during MFH treatment. Tumor cell death of 95% was achieved by depositing an intracellular total thermal energy with about 50% margin to damage of healthy cells. This is attributed to combined intracellular nanoheating and extracellular bulk heating. Tumor cell damage of up to 86% was observed for MFH treatment without perceptible bulk temperature rise. Effective heating decreased by up to 65% after MNP were internalized inside cells.
Heating efficiency of magnetic nanoparticles decreases with gradual immobilization in hydrogels
(2019)
Dual frequency magnetic excitation of magnetic nanoparticles (MNP) enables enhanced biosensing applications. This was studied from an experimental and theoretical perspective: nonlinear sum-frequency components of MNP exposed to dual-frequency magnetic excitation were measured as a function of static magnetic offset field. The Langevin model in thermodynamic equilibrium was fitted to the experimental data to derive parameters of the lognormal core size distribution. These parameters were subsequently used as inputs for micromagnetic Monte-Carlo (MC)-simulations. From the hysteresis loops obtained from MC-simulations, sum-frequency components were numerically demodulated and compared with both experiment and Langevin model predictions. From the latter, we derived that approximately 90% of the frequency mixing magnetic response signal is generated by the largest 10% of MNP. We therefore suggest that small particles do not contribute to the frequency mixing signal, which is supported by MC-simulation results. Both theoretical approaches describe the experimental signal shapes well, but with notable differences between experiment and micromagnetic simulations. These deviations could result from Brownian relaxations which are, albeit experimentally inhibited, included in MC-simulation, or (yet unconsidered) cluster-effects of MNP, or inaccurately derived input for MC-simulations, because the largest particles dominate the experimental signal but concurrently do not fulfill the precondition of thermodynamic equilibrium required by Langevin theory.
Magnetic nanoparticle relaxation in biomedical application: focus on simulating nanoparticle heating
(2021)
Frequency mixing magnetic detection (FMMD) is a sensitive and selective technique to detect magnetic nanoparticles (MNPs) serving as probes for binding biological targets. Its principle relies on the nonlinear magnetic relaxation dynamics of a particle ensemble interacting with a dual frequency external magnetic field. In order to increase its sensitivity, lower its limit of detection and overall improve its applicability in biosensing, matching combinations of external field parameters and internal particle properties are being sought to advance FMMD. In this study, we systematically probe the aforementioned interaction with coupled Néel–Brownian dynamic relaxation simulations to examine how key MNP properties as well as applied field parameters affect the frequency mixing signal generation. It is found that the core size of MNPs dominates their nonlinear magnetic response, with the strongest contributions from the largest particles. The drive field amplitude dominates the shape of the field-dependent response, whereas effective anisotropy and hydrodynamic size of the particles only weakly influence the signal generation in FMMD. For tailoring the MNP properties and parameters of the setup towards optimal FMMD signal generation, our findings suggest choosing large particles of core sizes dc > 25 nm nm with narrow size distributions (σ < 0.1) to minimize the required drive field amplitude. This allows potential improvements of FMMD as a stand-alone application, as well as advances in magnetic particle imaging, hyperthermia and magnetic immunoassays.
Numerical algorithms with C
(1996)
This article describes the functionality of a MATLAB® library that can be used to develop motion-logic applications in MATLAB programming language for industrial drive and control systems using the well known sercos automation bus. Therewith MATLAB's functionality is extended to designing automation applications from single axis machines up to multi-kinematic robots.
Wind energy represents the dominant share of renewable energies. The rotor blades of a wind turbine are typically made from composite material, which withstands high forces during rotation. The huge dimensions of the rotor blades complicate the inspection processes in manufacturing. The automation of inspection processes has a great potential to increase the overall productivity and to create a consistent reliable database for each individual rotor blade. The focus of this paper is set on the process of rotor blade inspection automation by utilizing an autonomous mobile manipulator. The main innovations include a novel path planning strategy for zone-based navigation, which enables an intuitive right-hand or left-hand driving behavior in a shared human–robot workspace. In addition, we introduce a new method for surface orthogonal motion planning in connection with large-scale structures. An overall execution strategy controls the navigation and manipulation processes of the long-running inspection task. The implemented concepts are evaluated in simulation and applied in a real-use case including the tip of a rotor blade form.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
A new method for improved autoclave loading within the restrictive framework of helicopter manufacturing is proposed. It is derived from experimental and numerical studies of the curing process and aims at optimizing tooling positions in the autoclave for fast and homogeneous heat-up. The mold positioning is based on two sets of information. The thermal properties of the molds, which can be determined via semi-empirical thermal simulation. The second information is a previously determined distribution of heat transfer coefficients inside the autoclave. Finally, an experimental proof of concept is performed to show a cycle time reduction of up to 31% using the proposed methodology.
The hybrid K+/Ca2+ sensor based on laser scanned silicon transducer for multi-component analysis
(2002)
Low emission zones and truck bans, the rising price of diesel and increases in road tolls: all of these factors are putting serious pressure on the transport industry. Commercial vehicle manufacturers and their suppliers are in the process of identifying new solutions to these challenges as part of their efforts to meet the EEV (enhanced environmentally friendly vehicle) limits, which are currently the most robust European exhaust and emissions standards for trucks and buses.
Biofuels potentially interesting also for aviation purposes are predominantly liquid fuels produced from biomass. The most common biofuels today are biodiesel and bioethanol. Since diesel engines are rather rare in aviation this survey is focusing on ethanol admixed to gasoline products.
The Directive 2003/30/EC of the European Parliament and the Council of May 8th 2003 on the promotion of the use of biofuels or other renewable fuels for transport encourage a growing admixture of biogenic fuel components to fossil automotive gasoline. Some aircraft models equipped with spark ignited piston engines are approved for operation with automotive gasoline, frequently called “MOGAS” (motor gasoline). The majority of those approvals is limited to MOGAS compositions that do not contain methanol or ethanol beyond negligible amounts. In the past years (bio-)MTBE or (bio-)ETBE have been widely used as blending component of automotive gasoline whilst the usage of low-molecular alcohols like methanol or ethanol has been avoided due to the handling problems especially with regard to the strong affinity for water. With rising mandatory bio-admixtures the conversion of the basic biogenic ethanol to ETBE, causing a reduction of energetic payoff, becomes more and more unattractive. Therefore the direct ethanol admixture is accordingly favoured.
Due to the national enforcements of the directive 2003/30/EC more oxygenates produced from organic materials like bioethanol have started to appear in automotive gasolines already. The current fuel specification EN 228 already allows up to 3 % volume per volume (v/v) (bio-)methanol or up to 5 % v/v (bio-)ethanol as fuel components. This is also roughly the amount of biogenic components to comply with the legal requirements to avoid monetary penalties for producers and distributors of fuels.
Since automotive fuel is cheaper than the common aviation gasoline (AVGAS), creates less problems with lead deposits in the engine, and in general produces less pollutants it is strongly favoured by pilots. But being designed for a different set of usage scenarios the use of automotive fuel with low molecular alcohols for aircraft operation may have adverse effects in aviation operation. Increasing amounts of ethanol admixtures impose various changes in the gasoline’s chemical and physical properties, some of them rather unexpected and not within the range of flight experiences even of long-term pilots.