Technical University of Berlin

About: Technical University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Laser & Catalysis. The organization has 27292 authors who have published 59342 publications receiving 1414623 citations. The organization is also known as: Technische Universität Berlin & TU Berlin.

SchNetPack: A Deep Learning Toolbox For Atomistic Systems

Abstract: SchNetPack is a toolbox for the development and application of deep neural networks that predict potential energy surfaces and other quantum-chemical properties of molecules and materials. It contains basic building blocks of atomistic neural networks, manages their training, and provides simple access to common benchmark datasets. This allows for an easy implementation and evaluation of new models. For now, SchNetPack includes implementations of (weighted) atom-centered symmetry functions and the deep tensor neural network SchNet, as well as ready-to-use scripts that allow one to train these models on molecule and material datasets. Based on the PyTorch deep learning framework, SchNetPack allows one to efficiently apply the neural networks to large datasets with millions of reference calculations, as well as parallelize the model across multiple GPUs. Finally, SchNetPack provides an interface to the Atomic Simulation Environment in order to make trained models easily accessible to researchers that are no...

Highly indistinguishable photons from deterministic quantum-dot microlenses utilizing three-dimensional in situ electron-beam lithography

Abstract: Single indistinguishable photon sources with high flux rates and purity are needed in quantum communications. Here, Gschrey et al. use three-dimensional electron-beam lithography to pattern deterministic quantum-dot microlenses and demonstrate enhanced photon-extraction efficiency and photon indistinguishability.

Comparative analysis of the biosorption of cadmium, lead, nickel, and zinc by algae.

Abstract: Thirty strains of algae were examined for their biosorption abilities in the uptake of cadmium, lead, nickel, and zinc from aqueous solution. A wide range of adsorption capacities between the different strains of algae and between the four metals can be observed. The cyanophyceae Lyngbya taylorii exhibited high uptake capacities for the four metals. The algae showed maximum capacities according to the Langmuir Adsorption Model of 1.47 mmol lead, 0.37 mmol cadmium, 0.65 mmol nickel, and 0.49 mmol zinc per gram of dry biomass. The optimum pH for L. taylorii was between pH 3 and 7 for lead, cadmium, and zinc and between pH 4 and 7 for nickel. Studies with the algae indicated a preference for the uptake of lead over cadmium, nickel, and zinc in a four metal solution. The metal binding abilities of L. taylorii could be improved by phosphorylation of the biomass. The modified biosorbent demonstrated maximum capacities of 2.52 mmol cadmium, 3.08 mmol lead, 2.79 mmol nickel, and 2.60 mmol zinc per gram of dry biomass. Investigations with phosphated L. taylorii indicated high capacities for the four metals also at low pH. The selectivity remained quite similar to the unmodified algae.

Impact of temperature on lethality and energy efficiency of apple juice pasteurization by pulsed electric fields treatment

Abstract: The applicability of pulsed electric fields as a non-thermal preservation process for liquid food decontamination has been shown in several studies. However, high costs of operation due to the occurrence of a high amount of dissipated electrical energy inhibited an industrial exploitation so far. In this study the focus was put on improving energy efficiency of this process for pasteurization of apple juice inoculated with Escherichia coli by investigating the relation between achieved reduction in survivor count and electric field strength and treatment temperature. An empirical mathematical model was derived to predict the required input of electrical energy for a given inactivation. Using synergistic effects of elevated treatment temperature of 35–65 °C on microbial inactivation the energy consumption could be reduced from above 100 to less than 40 kJ kg−1 for a reduction of 6 log cycles and the need to preheat the juice before treatment provided a possibility to recover the dissipated electrical energy after treatment, leading to a drastic reduction in operation costs. To evaluate the thermal load of the product the pasteurization unit (PU) and the cook value, key benchmarks for the thermal load, were used to compare PEF and conventional heat treatment.