Study of the Catalytic Activity–Semiconductive Properties Relationship For BaTiO<Subscript>3</Subscript> and PbTiO<Subscript>3</Subscript> Perovskites,Catalysts for Methane Combustion

Abstract  

The electrical conductivity of barium and lead perovskites used as catalysts for the total oxidation of methane, has been measured under nitrogen, methane–nitrogen mixture, air and methane–air mixture (reaction mixture) at the catalytic reaction temperature. The two compounds appeared to be p-type semiconductors under air with positive holes as the main charge carriers but became n-type when contacted with methane–nitrogen mixture. Their conductivities differ by 1.5 orders of magnitude as n-type semiconductors and by three orders of magnitude when being p-type semiconductors. These results explained the difference in the catalytic activity encountered on the two solids. The alkane activation was proposed to be related in both cases to the p-type semiconducting properties of the solids, likely through hydrogen abstraction by a surface O⁻ species, forming a CH₃^• radical. The overall reaction mechanism on both perovskites can be assimilated to a Mars and van Krevelen mechanism.     

Photoinduced electron transfer reactions: from the elucidation of old problems in bulk solutions towards the exploration of interfaces

The activities of our research group in the field of photoinduced electron transfer reactions are discussed and illustrated by several examples.     

ENGINEERING ASPECTS OF PENICILLIN G TRANSFER AND CONVERSION TO 6-AMINOPENICILLANIC ACID IN A BIOREACTOR WITH A MOBILE BED OF IMMOBILIZED PENICILLIN AMIDASE

This article presents studies on the external and internal mass transfers of penicillin G for 6-aminopenicillanic acid enzymatic production using a bioreactor with a stirred bed of immobilized penicillin amidase. By means of the substrate mass balance for a single particle of biocatalyst and considering the kinetic model adapted for competitive and noncompetitive inhibitions, specific mathematical models were developed for describing the profiles of penicillin G concentration in the outer and inner regions of biocatalyst and for estimating its mass flows in the liquid boundary layer surrounding the particle and inside the particle. The values of the mass flows are significantly influenced by the internal diffusion velocity and rate of the enzymatic conversion of substrate. These cumulated influences led to the appearance of an enzymatic inactive region near the particle center, its magnitude varying from 0 to 9.2% of the overall volume of particles.     

基于知网的词语语义相似度改进算法研究

词语语义相似度计算在很多自然语言处理相关领域都有着广泛应用.基于知网的现有词语语义相似度计算方法未深入考虑同棵义原层次树的义原距离、义原深度、义原密度及主次关系的影响,致使相似度计算结果并不够精确.针对该问题,提出一种词语语义相似度改进算法,通过分析知网中的义项表达式和义原层次树,用集合的加权平均值代替了义项相似度最大...     

Molecular Subtyping of Invasive Breast Cancer Using a PAM50-Based Multigene Expression Test-Comparison with Molecular-Like Subtyping by Tumor Grade/Immunohistochemistry and Influence on Oncologist’s Decision on Systemic Therapy in a Real-World Setting

In intermediate risk hormone receptor (HR) positive, HER2 negative breast cancer (BC), the decision regarding adjuvant chemotherapy might be facilitated by multigene expression tests. In all, 142 intermediate risk BCs were investigated using the PAM50-based multigene expression test Prosigna® in a prospective multicentric study. In 119/142 cases, Prosigna® molecular subtyping was compared with local and two central (C1 and C6) molecular-like subtypes relying on both immunohistochemistry (IHC; HRs, HER2, Ki-67) and IHC + tumor grade (IHC+G) subtyping. According to local IHC, 35.4% were Luminal A-like and 64.6% Luminal B-like subtypes (local IHC+G subtype: 31.9% Luminal A-like; 68.1% Luminal B-like). In contrast to local and C1 subtyping, C6 classified >2/3 of cases as Luminal A-like. Pairwise agreement between Prosigna® subtyping and molecular-like subtypes was fair to moderate depending on molecular-like subtyping method and center. The best agreement was observed between Prosigna® (53.8% Luminal A; 44.5% Luminal B) and C1 surrogate subtyping (Cohen’s kappa = 0.455). Adjuvant chemotherapy was suggested to 44.2% and 88.6% of Prosigna® Luminal A and Luminal B cases, respectively. Out of all Luminal A-like cases (locally IHC/IHC+G subtyping), adjuvant chemotherapy was recommended if Prosigna® testing classified as Prosigna® Luminal A at high / intermediate risk or upgraded to Prosigna® Luminal B.     

Locating experts and carving out the state of the art: A systematic review on Industry 4.0 and energy system analysis

As Germany's manufacturing industry highly depends on international competitiveness, German companies must rapidly assimilate to current processes of digitization and so‐called Industry 4.0. These processes will also affect the German energy system. Understanding and predicting the implications of these changes is one of the core elements of energy system analysis. To address this issue, herein, we present a structured and systematic review of literature within the intersection of industrial digitalization in the sense of Industry 4.0 and scientific energy system analysis. The goals of this study are (1) to reveal the locations and institutions of relevant experts and (2) to carve out the current state of the art with regard to technologies that enable (digitized) industries to interact with the energy system in order to contribute to a smart energy system. Our approach is based on a systematic and reproducible keyword search using the scientific literature database Scopus. Both a quantitative evaluation and a qualitative evaluation of the relevant literature are conducted. The quantitative results are presented using GIS‐based visualizations. This facilitates us to identify the European Union as main contributor on a global level and the United Kingdom as the most prolifically publishing country within the European Union. Focusing on Germany, we find North Rhine‐Westphalia to be the most scientifically active area and Aachen/Dortmund to be the cities where most publications originate. In the qualitative, content‐based part of this review, we show that in particular sector coupling and the integration of distributed energy prosumers can lead to a working smart energy system. We demonstrate that industrial digitalization processes in the sense of Industry 4.0 can serve as enabling factor in this respect. Further, we provide extensive summaries regarding both the technological and economic potentials and challenges of different technologies in future smart energy systems. Taking all of the results into account, we outline a framework to connect the highly discussed topics of digitalized industries and smart energy systems to corresponding experts.     

Artificial Enzymes for Diels-Alder Reactions

The Diels-Alder (DA) reaction is a cycloaddition of a conjugated diene and an alkene (dienophile) leading to the formation of a cyclohexene derivative through a concerted mechanism. As DA reactions generally proceed with a high degree of regio- and stereoselectivity, they are widely used in synthetic organic chemistry. Considering eco-conscious public and governmental movements, efforts are now directed towards the development of synthetic processes that meet environmental concerns. Artificial enzymes, which can be developed to catalyze abiotic reactions, appear to be important synthetic tools in the synthetic biology field. This review describes the different strategies used to develop protein-based artificial enzymes for DA reactions, including for in cellulo approaches.     

Machine Learning in Chemical Engineering: A Perspective

The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio-)catalysts, and functional materials. Recent breakthroughs in machine learning (ML) provide unique opportunities, but only joint interdisciplinary research between the ML and chemical engineering (CE) communities will unfold the full potential. We identify six challenges that will open new methods for CE and formulate new types of problems for ML: (1) optimal decision making, (2) introducing and enforcing physics in ML, (3) information and knowledge representation, (4) heterogeneity of data, (5) safety and trust in ML applications, and (6) creativity. Under the umbrella of these challenges, we discuss perspectives for future interdisciplinary research that will enable the transformation of CE.