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Institution

Technical University of Berlin

EducationBerlin, Germany
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.


Papers
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Journal ArticleDOI
TL;DR: This Review provides state-of-the-art knowledge on the underlying mechanisms of NRPSs and the variety of their products along with detailed analysis of the challenges for future reprogrammed biosynthesis.
Abstract: Nonribosomal peptide synthetases (NRPSs) are large multienzyme machineries that assemble numerous peptides with large structural and functional diversity. These peptides include more than 20 marketed drugs, such as antibacterials (penicillin, vancomycin), antitumor compounds (bleomycin), and immunosuppressants (cyclosporine). Over the past few decades biochemical and structural biology studies have gained mechanistic insights into the highly complex assembly line of nonribosomal peptides. This Review provides state-of-the-art knowledge on the underlying mechanisms of NRPSs and the variety of their products along with detailed analysis of the challenges for future reprogrammed biosynthesis. Such a reprogramming of NRPSs would immediately spur chances to generate analogues of existing drugs or new compound libraries of otherwise nearly inaccessible compound structures.

526 citations

Journal ArticleDOI
TL;DR: The experimental design explicitly addresses criticisms provoked by previous biodiversity experiments, in particular, the choice of functional groups, the statistical separation of sampling versus complementarity effects, and testing for the effects of particular functional groups differ from previous experiments.

526 citations

Journal ArticleDOI
TL;DR: This Review highlights some recent promising activities and developments in heterogeneous catalysis using only carbon and carbon nitride as catalysts, which could be candidates for green chemistry with low emission and an efficient use of the chemical feedstock.
Abstract: The current established catalytic processes used in chemical industries use metals, in many cases precious metals, or metal oxides as catalysts. These are often energy-consuming and not highly selective, wasting resources and producing greenhouse gases. Metal-free heterogeneous catalysis using carbon or carbon nitride is an interesting alternative to some current industrialized chemical processes. Carbon and carbon nitride combine environmental acceptability with inexhaustible resources and allow a favorable management of energy with good thermal conductivity. Owing to lower reaction temperatures and increased selectivity, these catalysts could be candidates for green chemistry with low emission and an efficient use of the chemical feedstock. This Review highlights some recent promising activities and developments in heterogeneous catalysis using only carbon and carbon nitride as catalysts. The state-of-the-art and future challenges of metal-free heterogeneous catalysis are also discussed.

523 citations

Journal ArticleDOI
TL;DR: In this paper, the optical and spin-relaxation properties of millimeter-scale diamond samples were characterized using confocal microscopy, visible and infrared absorption, and optically detected magnetic resonance.
Abstract: Nitrogen-vacancy (NV) centers in millimeter-scale diamond samples were produced by irradiation and subsequent annealing under varied conditions. The optical and spin-relaxation properties of these samples were characterized using confocal microscopy, visible and infrared absorption, and optically detected magnetic resonance. The sample with the highest ${\text{NV}}^{\ensuremath{-}}$ concentration, approximately 16 ppm $(2.8\ifmmode\times\else\texttimes\fi{}{10}^{18}\text{ }{\text{cm}}^{\ensuremath{-}3})$, was prepared with no observable traces of neutrally charged vacancy defects. The effective transverse spin-relaxation time for this sample was ${T}_{2}^{\ensuremath{\ast}}=118(48)\text{ }\text{ns}$, predominately limited by residual paramagnetic nitrogen which was determined to have a concentration of 49(7) ppm. Under ideal conditions, the shot-noise limited sensitivity is projected to be $\ensuremath{\sim}150\text{ }\text{fT}/\sqrt{\text{Hz}}$ for a $100\text{ }\ensuremath{\mu}\text{m}$-scale magnetometer based on this sample. Other samples with ${\text{NV}}^{\ensuremath{-}}$ concentrations from 0.007 to 12 ppm and effective relaxation times ranging from 27 to over 291 ns were prepared and characterized.

523 citations

Journal ArticleDOI
TL;DR: A new measure (phase-slope index) to estimate the direction of information flux in multivariate time series is proposed that is insensitive to mixtures of independent sources, gives meaningful results even if the phase spectrum is not linear, and properly weights contributions from different frequencies.
Abstract: We propose a new measure (phase-slope index) to estimate the direction of information flux in multivariate time series. This measure (a) is insensitive to mixtures of independent sources, (b) gives meaningful results even if the phase spectrum is not linear, and (c) properly weights contributions from different frequencies. These properties are shown in extended simulations and contrasted to Granger causality which yields highly significant false detections for mixtures of independent sources. An application to electroencephalography data (eyes-closed condition) reveals a clear front-to-back information flow.

521 citations


Authors

Showing all 27602 results

NameH-indexPapersCitations
Markus Antonietti1761068127235
Jian Li133286387131
Klaus-Robert Müller12976479391
Michael Wagner12435154251
Shi Xue Dou122202874031
Xinchen Wang12034965072
Michael S. Feld11955251968
Jian Liu117209073156
Ary A. Hoffmann11390755354
Stefan Grimme113680105087
David M. Karl11246148702
Lester Packer11275163116
Andreas Heinz108107845002
Horst Weller10545144273
G. Hughes10395746632
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023191
2022650
20213,307
20203,387
20193,105
20182,910