BINA

We would like to take this opportunity to thank all of Chemical Society Reviews’ reviewers, and in particular highlight the Outstanding Reviewers for the journal in 2020, as selected by the editorial team for their significant contribution to Chemical Society Reviews. We announce our Outstanding Reviewers annually and each receives a certificate to give recognition for their contribution. The reviewers have been chosen based on the number, timeliness and quality of the reports completed over the last 12 months.

MXenes are a large class of 2D materials that consist of few‐atoms‐thick layers of transition metal carbides, nitrides, or carbonitrides. The surface functionalization of MXenes has immense implications for their physical, chemical, and electronic properties. However, solution‐phase surface functionalization often leads to structural degradation of the MXene electrodes. Here, a non‐conventional, single‐step atomic surface reduction (ASR) technique is adopted for the surface functionalization of MXene (Ti3C2Tx) in an atomic layer deposition reactor using trimethyl aluminum as a volatile reducing precursor. The chemical nature of the modified surface is characterized by X‐ray photoelectron spectroscopy and nuclear magnetic resonance techniques. The electrochemical properties of the surface‐modified MXene are evaluated in acidic and neutral aqueous electrolyte solutions, as well as in conventional Li‐ion and …

Correction for ‘Thiadiazole containing N- and S-rich highly ordered periodic mesoporous organosilica for efficient removal of Hg(II) from polluted water’ by Asim Baumik et al., Chem. Commun., 2020, 56, 3963–3966, DOI 10.1039/D0CC00407C.

We report a facile and robust room-temperature NO₂ sensor fabricated using bi- and multi-layered 2H variant of tungsten di-selenide (2H-WSe₂) nanosheets, exhibiting high sensing characteristics. A simple liquid-assisted exfoliation of 2H-WSe₂, prepared using ambient pressure chemical vapor deposition, allows smooth integration of these nanosheets on transducers. Three sensor batches are fabricated by modulating the total number of layers (L) obtained from the total number of droplets from a homogeneous 2H-WSe₂ dispersion, such as ∼2L, ∼5–6L, and ∼13–17L, respectively. The gas-sensing attributes of 2H-WSe₂ nanosheets are investigated thoroughly. Room temperature (RT) experiments show that these devices are specifically tailored for NO₂ detection. 2L WSe₂ nanosheets deliver the best rapid response compared to ∼5–6L or ∼13–17L. The response of 2L WSe₂ at RT is 250, 328, and 361% to 2, 4, and 6 ppm NO₂, respectively. The sensor showed nearly the same response toward low NO₂ concentration even after 9 months of testing, confirming its remarkable long-term stability. A selectivity study, performed at three working temperatures (RT, 100, and 150 °C), shows high selectivity at 150 and 100 °C. Full selectivity toward NO₂ at RT confirms that 2H-WSe₂ nanosheet-based sensors are ideal candidates for NO₂ gas detection.

Ni-rich layered oxide LiNi₁ – ₓ – yCoₓMnyO₂ (1 – x – y > 0.5) materials are favorable cathode materials in advanced Li-ion batteries for electromobility applications because of their high initial discharge capacity. However, they suffer from poor cycling stability because of the formation of cracks in their particles during operation. Here, we present improved structural stability, electrochemical performance, and thermal durability of LiNi₀.₈₅Co₀.₁Mn₀.₀₅O₂(NCM85). The Nb-doped cathode material, Li(Ni₀.₈₅Co₀.₁Mn₀.₀₅)₀.₉₉₇Nb₀.₀₀₃O₂, has enhanced cycling stability at different temperatures, outstanding capacity retention, improved performance at high discharge rates, and a better thermal stability compared to the undoped cathode material. The high electrochemical performance of the doped material is directly related to the structural stability of the cathode particles. We further propose that Nb-doping in NCM85 improves material stability because of partial reduction of the amount of Jahn–Teller active Ni³⁺ ions and formation of strong bonds between the dopant and the oxygen ions, based on density functional theory calculations. Structural studies of the cycled cathodes reveal that doping with niobium suppresses the formation of cracks during cycling, which are abundant in the undoped cycled material particles. The Nb-doped NCM85 cathode material also displayed superior thermal characteristics. The coherence between the improved electrochemical, structural, and thermal properties of the doped material is discussed and emphasized.

mediaTUM - Medien- und Publikationsserver mediaTUM Universitätsbibliothek Technische Universität München Logo Benutzer: Gast Login de en mediaTUM Gesamtbestand Hochschulbibliographie Elektronische Prüfungsarbeiten Open Access Publikationen Forschungsdaten TUM.University Press Sammlungen Projekte Einrichtungen Forschungszentren Hochschulpräsidium Partnerschaftliche Einrichtungen Schools und Fakultäten Fakultät für Chemie Fakultät für Elektrotechnik und Informationstechnik Prüfungsarbeiten (1447) Bildarchiv Lehrstühle und Professuren Audio-Signalverarbeitung (Prof. Seeber) (383) Bioanaloge Informationsverarbeitung (Prof. Hemmert) (304) Biomedizinische Elektronik (Prof. Hayden) (301) Codierung und Kryptographie (Prof. Wachter-Zeh) (342) Computational Neuroengineering (Prof. Cheng komm.) (69) Computational Photonics (W3TT) (Prof. Jirauschek) (234) Control and …

A fundamental understanding of the hydrogen oxidation reaction (HOR) mechanism requires the synthesis of model catalysts with designed surfaces, and advanced characterization techniques of the active sites. Although HOR are fast under acidic conditions, HOR kinetics are sluggish under alkaline conditions, even on platinum group metals (PGMs). Herein, we propose the use of an effective high-surface-area carbon supported Pd/γ-NiOOH HOR electrocatalyst, made from organometallic precursors. The enhanced activity, provided by nickel oxy-hydroxide (γ-NiOOH) 2 nm nanocubes, was confirmed experimentally in an alkaline exchange membrane fuel cell. Contrary to previous reports, the phase and crystallographic orientation of the γ-NiOOH nanocubes (<2 nm in size) were fully ascribed through high-resolution transmission electron microscopy. Operando X-ray absorption spectroscopy revealed a redox …

Ni-rich layered oxide LiNi₁ – ₓ – yCoₓMnyO₂ (1 – x – y > 0.5) materials are favorable cathode materials in advanced Li-ion batteries for electromobility applications because of their high initial discharge capacity. However, they suffer from poor cycling stability because of the formation of cracks in their particles during operation. Here, we present improved structural stability, electrochemical performance, and thermal durability of LiNi₀.₈₅Co₀.₁Mn₀.₀₅O₂(NCM85). The Nb-doped cathode material, Li(Ni₀.₈₅Co₀.₁Mn₀.₀₅)₀.₉₉₇Nb₀.₀₀₃O₂, has enhanced cycling stability at different temperatures, outstanding capacity retention, improved performance at high discharge rates, and a better thermal stability compared to the undoped cathode material. The high electrochemical performance of the doped material is directly related to the structural stability of the cathode particles. We further propose that Nb-doping in NCM85 improves material stability because of partial reduction of the amount of Jahn–Teller active Ni³⁺ ions and formation of strong bonds between the dopant and the oxygen ions, based on density functional theory calculations. Structural studies of the cycled cathodes reveal that doping with niobium suppresses the formation of cracks during cycling, which are abundant in the undoped cycled material particles. The Nb-doped NCM85 cathode material also displayed superior thermal characteristics. The coherence between the improved electrochemical, structural, and thermal properties of the doped material is discussed and emphasized.

Capturing the dynamic 3D atomic-scale structure of a macromolecular machine while it performs its biological function remains an outstanding goal of biology. Here we provide an update on our project to combine (prior) information from multiple existing static structures of stable states with dynamic datasets of inter-atomic distances obtained by high-throughput non-equilibrium single-molecule FRET (smFRET) measurements in a microfluidic mixer using novel time-resolved multi-pixel single-photon avalanche diode detector. These measurements, performed on libraries of molecular constructs, will sample multiple inter-atomic distances as function of reaction time. The measured distance distributions, together with additional information provided by cross-linking experiments analyzed by mass spectrometry, will then serve as multiple intra-and inter-domain distance constraints which, together with prior information from available structures, will enable large-scale computational energy optimization-based refinement of time-resolved ‘snap shots’ of complex structures with improved accuracy. These time-resolved computational structures, together with intermediary molecular dynamics simulations, will allow solving the 3D atomic-level structure of the macromolecule for each sampled reaction time point, eventually producing a 3D structural dynamic movie of the macromolecule in action. To demonstrate the utility of the proposed method, we study on one hand the dynamic structure of RNA polymerase during transcription initiation (promoter binding, bubble opening, abortive initiation, promoter clearance) and, on the other hand, a pair of intrinsically …

Plan recognition deals with reasoning about the goals and execution process of an actor, given observations of its actions. It is one of the fundamental problems of AI, applicable to many domains, from user interfaces to cyber-security. Despite the prevalence of these approaches, they lack a standard representation, and have not been compared using a common testbed. This paper provides a first step towards bridging this gap by providing a standard plan library representation that can be used by hierarchical, discrete-space plan recognition and evaluation criteria to consider when comparing plan recognition algorithms. This representation is comprehensive enough to describe a variety of known plan recognition problems and can be easily used by existing algorithms in this class. We use this common representation to thoroughly compare two known approaches, represented by two algorithms, SBR and …

Recently, we are seeing the emergence of plan-and goal-recognition algorithms which are based on the principle of rationality. These avoid the use of a plan library that compactly encodes all possible observable plans, and instead generate plans dynamically to match the observations. However, recent experiments by Berkovitz (Berkovitz, The effect of spatial cognition and context on robot movement legibility in human-robot collaboration, 2018) show that in many cases, humans seem to have reached quick (correct) decisions when observing motions which were far from rational (optimal), while optimal motions were slower to be recognized. Intrigued by these findings, we experimented with a variety of rationality-based recognition algorithms on the same data. The results clearly show that none of the algorithms reported in the literature accounts for human subject decisions, even in this simple task. This is our first …

The current work presents the fabrication of micrometer‐thick single‐side‐coated surface‐engineered polypropylene (PP) film for versatile flexible electronics applications. Herein, the authors report, for the first time, photopolymerized thin coating of graphene nanofibers (GNFs) and iron oxide nanoparticles (IONPs) onto non‐polar plastic via surface chemistry. The fabrication is achieved by adopting three consecutive steps; initially corona treated PP films are treated with silane for thin layer silica coating. Then, the silylated PP films are brushed up by pyrrole/GNFs/IONPs mixture, followed by UV exposure. The coated films show surface conductivity in the range of ≈20 S cm−1 at room temperature. Moreover, ≈15 microns of the coated film is tested against electromagnetic waves in the X‐band region (8.2–12.4 GHz) and its shielding behavior (≈24 dB) is confirmed. To demonstrate its wide range of versatility, the …

Nanoparticles having magnetic and fluorescent properties could be considered as a gift to materials scientists due to their unique magneto-optical qualities. Multiple component particles can overcome challenges related with a single component and unveil bifunctional/multifunctional features that can enlarge their applications in diagnostic imaging agents and therapeutic delivery vehicles. Bifunctional nanoparticles that have both luminescent and magnetic features are termed as magnetic nanolights. Herein, we present recent progress of magneto-fluorescent nanoparticles (quantum dots based magnetic nanoparticles, Janus particles, and heterocrystalline fluorescent magnetic materials), comprehensively describing fabrication strategies, types, and biomedical applications. In this review, our aim is not only to encompass the preparation strategies of these special types of magneto-fluorescent nanomaterials but …

Hydrogen bromine redox flow batteries (RFB) are considered to be one of the most promising storage alternatives, as this technology offers both high energy and high-power density. In this work a printed circuit board type of segmented current collector for the measurement of locally resolved current density was developed. This analytical tool was inserted as hydrogen anode current collector in a hydrogen-bromine test cell. Charging and discharging operation was monitored under different stoichiometric flow conditions and the impact on current distribution is presented. This technique offers the possibility to prove cell limiting conditions with spatial resolution, improving our understanding and determining optimal operating conditions for a given design.

Wastewater reclamation is becoming a top global interest as population growth and rapid industrialization pose a major challenge that requires development of sustainable cost-effective technologies and strategies for wastewater treatment. Carbon nanomembranes (CNMs)—synthetic 2D carbon sheets—can be tailored chemically with specific surface functions and/or physically with nanopores of well-defined size as a strategy for multifunctional membrane design. Here, we explore a bifunctional design for combined secondary wastewater effluent treatment with dual action of membrane separation and advanced oxidation processes (AOP), exploiting dissolved oxygen. The bifunctional membrane consists of a CNM layer on top of a commercial ultrafiltration membrane (Microlon™) and a spray-coated reduced graphene oxide (rGO) thin film as the bottom layer. The CNM/support/rGO membrane was characterized …

For many years, significant research efforts have been spent on investigating methodologies, tools, models and technologies for engineering autonomous agents software. Research into agent architectures and their structure, programming languages specialized for building agents, formal models and their implementation, development methodologies, middleware software, have been discussed in the literature, encompassing multiple communities of researchers, with at least partial overlaps in interests and approaches. The fundamental assumption underlying these research efforts is that such specialization is needed, because autonomous agent software poses engineering requirements that may not be easily met by more general (and more familiar) software engineering and programming paradigms. Specialized tools, models, programming languages, code architectures and abstractions make sense, if the software engineering problem is specialized. A broad overview of the literature reveals that for the most part, the truth of this assumption has been supported by qualitative arguments and anecdotal evidence. Agent-oriented programming [1] is by now a familiar and accepted programming paradigm, and countless discussions of its merits and its distinctiveness with respect to other programming paradigms (eg, object-oriented programming, aspect-oriented programming) are commonly found on the internet. Agent architectures are commercially available as development platforms and are incorporated into products. Indeed, agent-oriented software development methodologies are taught and utilized in and out of academic circles [2–5].

Prophages are bacteriophages in the lysogenic state, where the viral genome is inserted within the bacterial chromosome. They contribute to strain genetic variability and can influence bacterial phenotypes. Prophages are highly abundant among the strains of the opportunistic pathogen Pseudomonas aeruginosa and were shown to confer specific traits that can promote strain pathogenicity. The main difficulty of studying those regions is the lack of a simple prophage-curing method for P. aeruginosa strains. In this study, we developed a novel, targeted-curing approach for prophages in P. aeruginosa. In the first step, we tagged the prophage for curing with an ampicillin resistance cassette (ampR) and further used this strain for the sacB counter-selection marker's temporal insertion into the prophage region. The sucrose counter-selection resulted in different variants when the prophage-cured mutant is the sole variant that lost the ampR cassette. Next, we validated the targeted-curing with local PCR amplification and Whole Genome Sequencing. The application of the strategy resulted in high efficiency both for curing the Pf4 prophage of the laboratory wildtype (WT) strain PAO1 and for PR2 prophage from the clinical, hard to genetically manipulate, 39016 strain. We believe this method can support the research and growing interest in prophage biology in P. aeruginosa as well as additional Gram-negative bacteria.

A detailed investigation is presented for the solvent-free mechanochemical synthesis of zinc oxide nanoparticles from ε-Zn (OH) 2 crystals by high-energy ball milling. Only a few works have ever explored the dry synthetic route from ε-Zn (OH) 2 to ZnO. The milling process of ε-Zn (OH) 2 was done in ambient conditions with a 1: 100 powder/ball mass ratio, and it produced uniform ZnO nanoparticles with sizes of 10–30 nm, based on the milling duration. The process was carefully monitored and the effect of the milling duration on the powder composition, nanoparticle size and strain, optical properties, aggregate size, and material activity was examined using XRD, TEM, DLS, UV-Vis, and FTIR. The mechanism for the transformation of ε-Zn (OH) 2 to ZnO was studied by TGA and XPS analysis. The study gave proof for a reaction mechanism starting with a phase transition of crystalline ε-Zn (OH) 2 to amorphous Zn (OH …

One of the greatest challenges toward rechargeable magnesium batteries is the development of noncorrosive electrolyte solutions with high anodic stability that can support reversible Mg deposition/dissolution. In the last few years, magnesium electrolyte solutions based on Cl-free fluorinated alkoxyborates were investigated for Mg batteries due to their high anodic stability and ionic conductivity and the possibility of reversible deposition/dissolution in ethereal solvents. Here, the electrochemical performance of Mg[B(hexafluoroisopropanol)₄]₂/dimethoxyethane (Mg[B(HFIP)₄]₂/DME) solutions was examined. These electrolyte solutions require a special “conditioning” pretreatment that removes undesirable active moieties. Such a process was developed and explored, and basic scientific issues related to the mechanism by which it affects Mg deposition/dissolution were addressed. The chemical changes that occur during the conditioning process were examined. Mg[B(HFIP)₄]₂/DME solutions were found to enable reversible Mg deposition, albeit with a relatively low Coulombic efficiency of 95% during the first cycles. Prolonged deposition/dissolution cycling tests demonstrate a stable behavior of magnesium electrodes. Overall, this system presents a reasonable electrolyte solution and can serve as a basis for future efforts to develop chlorine-free alternatives for secondary magnesium batteries. It is clear that such a conditioning process is mandatory, as it removes reactive contaminants that lead to unavoidable passivation and deactivation of Mg electrodes from the solution.

The adaptive branch of the immune system learns pathogenic patterns and remembers them for future encounters. It does so through dynamic and diverse repertoires of T- and B- cell receptors (TCR and BCRs, respectively). These huge immune repertoires in each individual present investigators with the challenge of extracting meaningful biological information from multi-dimensional data. The ability to embed these DNA and amino acid textual sequences in a vector-space is an important step towards developing effective analysis methods. Here we present Immune2vec, an adaptation of a natural language processing (NLP)-based embedding technique for BCR repertoire sequencing data. We validate Immune2vec on amino acid 3-gram sequences, continuing to longer BCR sequences, and finally to entire repertoires. Our work demonstrates Immune2vec to be a reliable low-dimensional representation that preserves relevant information of immune sequencing data, such as n-gram properties and IGHV gene family classification. Applying Immune2vec along with machine learning approaches to patient data exemplifies how distinct clinical conditions can be effectively stratified, indicating that the embedding space can be used for feature extraction and exploratory data analysis.