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A Scalable, Biopolymer-Based Microenvironment for Electrochemical CO2 Conversion to Multicarbon Products with Current Densities Over 2 A/cm2
No full text<p>The electrochemical CO<sub>2</sub> reduction reaction (CO<sub>2</sub>RR) offers a sustainable approach for converting CO<sub>2</sub> into valuable fuels and chemicals. CO<sub>2</sub>RR relies on copper (Cu) catalysts to produce desirable multicarbon (C<sub>2+</sub>) products, but C<sub>2+</sub> yields rely heavily on the surrounding microenvironment. Moreover, controlling the microenvironment to achieve high C<sub>2+</sub> yields at industrially-relevant current densities remains a persistent challenge. To address this challenge, we show that biopolymer coatings on the Cu electrodes can tune the microenvironment, enabling a new strategy to achieve high yields of C<sub>2+</sub> products at ultra-high current densities. This approach achieves remarkable C<sub>2+</sub> Faradaic efficiencies (FE<sub>C2+</sub>) of 90±1.7% at 1.6 A cm<sup>-2</sup> and FE<sub>C2+</sub>=83±3.2% at 2.2 A cm<sup>-2</sup> with a formation rate of 5925.9 μmol h<sup>−1 </sup>cm<sup>−2</sup>. Furthermore, these biopolymers can even fully substitute traditional ionomers and binders, such as Nafion, within the cathode. Our findings challenge previous assumptions about the non-viability of hydrophilic materials for CO<sub>2</sub>RR and provide critical new insights into microenvironment design to enhance C-C coupling. Several complementary investigations reveal that biopolymer coatings increase local CO<sub>2</sub>/CO concentration, lower local water activity, and provide suitable ion conductivity and local pH. We anticipate that these molecular-level insights represent a paradigm shift in catalyst design to unlock new approaches to optimize the microenvironment for CO<sub>2</sub>RR to enable high rates of C-C coupling without the typical unwanted increase in hydrogen evolution. These abundant biopolymer coatings are environmentally benign, solution-processable, and highly accessible, which is expected to provide researchers with a facile route towards high-performance CO<sub>2</sub>RR at both laboratory and industrial scales.</p>
SEG-Y Multichannel seismic data collected during RV METEOR expedition M199 and used for publication by Micallef et al., in prep.
No full text<p><span>The dataset comprises 3 multichannel seismic profiles, which have been collected during RV METEOR expedition M199 in February 2024 by the University of Hamburg. Data format is SEG-Y. Trace headers follow SEG-Y Revision 1 standard.</span></p>
<p><span>The profiles are:</span></p>
<p><span>M199_MCS_HH24-03</span></p>
<p><span>M199_MCS_HH24-05</span></p>
<p><span>M199_MCS_HH24-29</span></p>
Data for Non-Equilibrium Sensing of Volatile Compounds Using Active and Passive Analyte Delivery
No full text<blockquote>
<p>Version 2: Added missing files to <code>sniffing_data.zip</code></p>
</blockquote>
<p>See GitHub repository for data processing functions and examples: <a href="https://github.com/soerenbrandt/sniffing-sensor">https://github.com/soerenbrandt/sniffing-sensor</a></p>
<p><strong>Abstract</strong>:<br>Sensor technologies have allowed us to outperform the human senses of sight, hearing, and touch; however, the development of artificial noses is significantly behind their biological counterparts. This is largely due to the complexity of natural olfaction, as it incorporates complex fluid dynamics within the nasal anatomy together with the response patterns of hundreds to thousands of unique molecular-scale receptors for odor interpretation. We designed a sensing approach to identify volatiles that exploits time-dependent information from a single sensor (here, the reflectance spectra from a mesoporous one-dimensional photonic crystal) by augmenting and accentuating differences in the non-equilibrium mass-transport dynamics of vapors stemming from their distinct physicochemical properties, thus obviating the need for a large sensor array. By training a machine learning algorithm on the sensor output, we clearly identify polar and nonpolar volatile organic compounds, determine the mixing ratios of binary mixtures, and accurately predict the boiling point, flash point, vapor pressure, and viscosity of several volatile liquids within those used for training as well as compounds unknown to the model. We further implement a bioinspired active sniffing approach, in which the fluid dynamics and patterns of analyte delivery are controlled, enabling an additional modality of differentiation and reducing the duration of data collection and analysis to seconds. These results outline a strategy to build accurate and rapid artificial noses for volatile liquids that can provide useful information on chemicals such as their composition and properties, and can be applied in a variety of fields, including disease diagnosis, hazardous waste management, and healthy building monitoring.</p>
Cooperative model predictive control for avoiding critical instants of energy resilience in networked microgrids
No full text<p>The recent international agreements signed by the majority of developed countries, such as those reached at the Climate Change Conferences in Paris’15 and Dubai’23, propose an increasingly rapid transition toward an energy ecosystem with a clear predominance of renewable energy in electrical power systems. The development of such ambitious energy programs should deal with the inherited stochasticity that renewable energy systems entail, which, when coupled with uncertainty about the capacity of the grid to maintain a power supply owing to increasing demands, decarbonization processes and the widespread closure of nuclear power plants, pose a serious threat to the normal functioning of energy systems. When combined with the escalation of armed conflicts that imply the loss of supply as a result of attacks or cyberattacks on power plants and<br>distribution networks, it becomes clear that the current energy paradigm in which there is a centralized grid supplying numerous consumers, many of whom do not have their own generation capacity, must shift toward increasing the deployment of renewable-energy-based self-consumption facilities. The continuous advances toward a decentralized energy system of this nature will also lead to more cooperation, increasing the presence of energy communities with a great need to strengthen internal resilience as a sustaining factor.<br>Considering the challenging framework of smart grids and energy transition, Microgrids would appear to be the key technology for the aggregation of generation, load and energy storage systems, and a cornerstone with which to provide the resilience and flexibility required for this new renewable-energy-based scenario. In addition to the complexity of the microgrid control problem, the issue of resilience energy management also<br>has to be considered, which refers to the ability to adapt and supply loads during a specified period after a disruptive event with a loss of grid supply.</p><p>Funding:</p>
<p>Spanish Ministry of Science, Innovation and Universities and the Spanish Centre for Industrial Technological Development under Grant MIG-20221009 (AD-GRHID)</p>
Broomcorn millet jinshu7 genome annotation
No full text<p>Broomcorn millet jinshu7 genome annotation</p>
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Comparing the Holy Liturgy between Copts and Hellēnes
No full textThis article evokes the liturgical connections between Coptic and Hellenic Orthodox (Byzantine) traditions. It starts with an introduction about the beginning of Christianity in Egypt. The next sections are an enumeration and a brief study of the contact places of such exchanges
Nuevas especies de la familia Columbellidae (Gasteropoda: Neogastropoda) para el litoral peruano
No full textThis article includes a total of 8 new species of Columbellidae for the Peruvian coast, grouped into 4 genera: Anachis mogolloni, Parvanachis bocapanensis, Parvanachis forcellii, Mitrella penai, Mitrella caboblanquensis, Mitrella humboldti, Mitrella salvadorae, including a new genus Urpiella and species Urpiella thorsson