Low Selectivity Research Articles

Ultrafine AuCu nanowires for electrocatalytic nitrogen fixation

We report a simple strategy to synthesize one-dimensional ultrafine AuCu nanowires for highly efficient electrocatalytic reduction of nitrogen to ammonia.

Visible-light-mediated metal-free regioselective oxidative C-C bond cleavage of lignin dimers to aromatic acids.

The upgrading of lignin is a sustainable and promising pathway for fossil-based aromatic compounds but always faces low selectivity. Herein, a metal-free photocatalyst, 2,4,6-triphenylpyrylium tetrafluoroborate (TPP), was illustrated to remarkably facilitate the regioselective oxidative Cα-Cβ bond cleavage of β-1 and β-O-4 lignin alcohol/ketone models into aromatic acids (92-99% yields) under visible-light irradiation at room temperature without any additive/co-catalyst, which was enabled by the synergistic effect of Cβ-H⋯C(TPP) interaction and·˙O2-/1O2 species. The synergy of the catalyst-substrate interaction and active species offers a reference for the enhancive and selective transformation of polymeric biomass and complex molecules.

3D Oleophilic Sorbent Films Based on Recycled Low-Density Polyethylene.

Recycling low-end, one-time-use plastics-such as low-density polyethylene (LDPE)-is of paramount importance to combat plastic pollution and promote sustainability in the modern green economy. This study valorizes LDPE waste by transforming it into 3D oleophilic swellable thin films through a process involving dissolution, phase separation, and extraction. These films are subsequently layered using a customized polypropylene (PP) based nonwoven fabric separator and securely sealed in a zigzag pattern. The zigzag-shaped seal enhances the adhesion of pollutants to the sorbent by providing wire curvatures that increase retention time and uptake capacity. As a result, the sorbent exhibits impressive oil uptake capacities, with immediate and equilibrium values of 120 g/g and 85 g/g, respectively. Notably, the as-prepared sorbent demonstrates low water retention and high selectivity for oil, outperforming commercially available oil sorbents. The unique design involving a 3D-film structure, superposed films, and a zigzag-shaped seal offers a sustainable and value-added solution to the issues of LDPE waste and oil spills on water surfaces.

Enhanced methanol selectivity and synthesis in a non-catalytic dielectric barrier discharge (DBD) plasma reactor

Direct utilisation of CO2 to methanol via environmentally friendly gas-to-liquid processes with plasma poses various challenges, such as low methanol selectivity. This study explores the non-catalytic hydrogenation of CO2 and CO gas mixtures in a self-cooling dielectric barrier discharge (DBD) plasma at atmospheric pressure and temperature. Small amounts of N2 and argon were input as auxiliary gases to investigate their effect on methanol production and a probable reaction mechanism was suggested. A H2 + CO2 + CO + N2 mixture minimised methanation and the reverse water–gas shift competitive reactions, thus enhancing methanol selectivity and yield to 86 % and 22.5 %, respectively. Furthermore, N2 helped reduce plasma power requirements, stabilised the discharge, and displayed suitable third-body properties able to tune up plasma reactions yielding a better methanol production rate than argon. Our findings reveal that plasma performance can be enhanced using a suitable reactant composition in combination with gas additives (in this case, N2) to improve methanol synthesis.

Vanadium doped B5N3 and B7N5 monolayer as single atom catalyst for nitrogen reduction reaction – a first-principles study

The Haber-Bosch process, commonly used for ammonia synthesis, can be replaced by the electrochemical nitrogen reduction reaction (NRR), which offers a more environmentally conscious and sustainable approach. However, developing electrocatalysts with low potential, high selectivity, and fast reaction kinetics remains challenging. In the current work, we have theoretically calculated the potential of V@B5N3 and V@B7N5 (V = Vanadium) material which serves as an electrocatalyst for NRR using density functional theory (DFT) simulations. Our results reveal that the monolayer of V@B7N5 exhibits remarkable catalytic activity and effectively suppresses the hydrogen evolution reaction at an overpotential of 0.13 V. Furthermore, the potential-determining step involving the conversion of *N2-*N2H demonstrates a favourable energy barrier, indicating facile kinetics. The V@B7N5 monolayer shows promising selectivity, with an anticipated ammonia production efficiency of 99%. These findings open avenues for employing single-atom catalysts under ambient conditions to synthesise ammonia, offering a potential solution for sustainable ammonia production.

Rhein/carbon nanotube derived carbon materials with quinone group for hydrogen peroxide electrosynthesis

Oxygen-doped carbon materials (OC) have been studied as the electrocatalysts of two-electron oxygen reduction reaction (2-e ORR) to synthesize H2O2 due to their low cost and high selectivity. In this study, quinone group contained OC (OC-R/CNT) were prepared using the mixture of rhein with quinone group and carbon nanotube (CNT) as the precursor via one-step pyrolysis. The RRDE test showed that the OC-R/CNT gave a H2O2 selectivity of 94 % at 0.20 V in neutral medium. During the H-cell test, the H2O2 yield of OC-R/CNT can be up to 170 mmol gcat−1 h−1 at 0 V vs. RHE and the OC-R/CNT catalyst exhibited good long-term stability and reusability. The H2O2 solution produced at 0 V vs. RHE for 1 hour showed good bactericidal properties. For comparison, the OC without quinone group (OC-G/CNT) were also prepared with glucose and CNT as the precursor under the same condition, which showed poorer 2-e ORR catalytic performance. This study not only provides a feasible method to prepare quinone group contained carbon materials but also verifies the important role of quinone group in 2-e ORR.

Highly active Co1-N3-O1 single-atom catalyst for boosting catalytic synthesis of unsaturated benzylamines and arylamines

Unsaturated benzylamines and arylamines are the key building blocks for the synthesis of organic pharmaceutical molecules, but their synthetic processes always suffer from low selectivity as a result of the excessive hydrogenation of unsaturated groups. Herein, the cobalt single-atom catalyst with an asymmetric Co1-N3-O1 structure was designed and constructed on porous carbon nanospheres. It is found that the Co1-N3-O1 catalyst showed excellent catalytic activity toward the synthesis of unsaturated benzylamines and arylamines. The results of characterization analysis and density functional theory (DFT) calculation further clarify that introducing oxygen into the Co single-atom coordination environment of Co1-N3-O1 increased hydrogenation energy barrier of the terminal C=C double bond, which is beneficial to suppress competing hydrogenation reactions. Meanwhile, the Co1-N3-O1 catalyst had the lower energy barrier for reduction of the C=N bond to amino group, boosting the yields of unsaturated benzylamines and arylamines. This study offers an attracting strategy for efficient and selective reductive amination reaction by making use of the asymmetrically structured Co single-atom catalyst.

Gold nanoparticles supported on reduced graphene oxide as green catalyst for solventless hydrosilylation process

The hydrosilylation reaction is a versatile process that is used to synthesize a variety of organosilicon compounds. However, the traditional metal oxide catalysts used for this reaction suffer from low activity and selectivity. In this study, we synthesized and characterized a gold nanoparticles (AuNPs)-reduced graphene oxide (rGO) catalyst for the hydrosilylation reaction. The AuNPs-rGO catalyst was synthesized by a one-pot method using trisodium citrate (Na3C6H5O7) as a reducing and capping agent. The catalyst was characterized by XRD, FESEM, and FTIR. The hydrosilylation reaction was carried out under solventless conditions using dimethylphenylsilane as the substrate. The AuNPs-rGO catalyst was found to be highly active and selective for the hydrosilylation reaction, yielding a 100% conversion of the substrate to disiloxane in 3 hours. The results of this study demonstrate the potential of AuNPs-rGO catalysts for the hydrosilylation reaction and suggest that they could be used to develop more efficient and sustainable processes for the synthesis of organosilicon compounds.

New cyclophilin D inhibitor rescues mitochondrial and cognitive function in Alzheimer's disease.

Mitochondrial dysfunction is an early pathological feature of Alzheimer disease and plays a crucial role in the development and progression of Alzheimer's disease. Strategies to rescue mitochondrial function and cognition remain to be explored. Cyclophilin D (CypD), the peptidylprolyl isomerase F (PPIase), is a key component in opening the mitochondrial membrane permeability transition pore, leading to mitochondrial dysfunction and cell death. Blocking membrane permeability transition pore opening by inhibiting CypD activity is a promising therapeutic approach for Alzheimer's disease. However, there is currently no effective CypD inhibitor for Alzheimer's disease, with previous candidates demonstrating high toxicity, poor ability to cross the blood-brain barrier, compromised biocompatibility and low selectivity. Here, we report a new class of non-toxic and biocompatible CypD inhibitor, ebselen, using a conventional PPIase assay to screen a library of ∼2000 FDA-approved drugs with crystallographic analysis of the CypD-ebselen crystal structure (PDB code: 8EJX). More importantly, we assessed the effects of genetic and pharmacological blockade of CypD on Alzheimer's disease mitochondrial and glycolytic bioenergetics in Alzheimer's disease-derived mitochondrial cybrid cells, an ex vivo human sporadic Alzheimer's disease mitochondrial model, and on synaptic function, inflammatory response and learning and memory in Alzheimer's disease mouse models. Inhibition of CypD by ebselen protects against sporadic Alzheimer's disease- and amyloid-β-induced mitochondrial and glycolytic perturbation, synaptic and cognitive dysfunction, together with suppressing neuroinflammation in the brain of Alzheimer's disease mouse models, which is linked to CypD-related membrane permeability transition pore formation. Thus, CypD inhibitors have the potential to slow the progression of neurodegenerative diseases, including Alzheimer's disease, by boosting mitochondrial bioenergetics and improving synaptic and cognitive function.

Bis(triethoxysilyl)ethane (BTESE)-Organosilica Membranes for H2O/DMF Separation in Reverse Osmosis (RO): Evaluation and Correlation of Subnanopores via Nanopermporometry (NPP), Modified Gas Translation (mGT) and RO Performance.

A 40 cm length Bis(triethoxysilyl)ethane (BTESE) membrane having different pore sizes was successfully prepared by changing the number of coating times for gas permeation (GP) and organic solvent reverse osmosis (OSRO) separation study. It was found that BTESE-6 membranes prepared through six-time coating consisted of small-sized pores in the range 0.56 to 0.64 nm estimated using modified Gas Translation (mGT) method and 0.59 to 0.67 nm estimated by nanopermporometry (NPP) method, respectively. These membranes demonstrated a high DMF rejection, RDMF > 95% with total flux, Jv total > 5 kg m-2 h-1 at operating condition feed pressure, Pf: 8 MPa; feed temperature, Tf : 50 °C; and feed flowrate, Qf : 30 mL/min; and they exhibited a high degree selectivity of He/SF6 in the range of ~ 260-3400 at a permeation temperature 200 °C. On the other hand, the larger pore sizes of the BTESE-4 membranes (pore size estimates > 0.76 nm to 1.02 nm) exhibited low DMF rejection and a low degree selectivity of He/SF6 around ~30% and 25, respectively, at the same operating condition as BTESE-6. Both GT and NPP methods can be considered as an indicator of the measurement membrane pore size. From this study, it was found that He and SF6 gases can be some of the potential predictors for water and DMF permeance. Furthermore, by comparing our OSRO membrane with other PV membranes for DMF/H2O separation, our BTESE-6 membranes still exhibited high flux in the range of 3-6 kg m-2 h-1 with a separation factor H2O/DMF in the range of 80-120.

Standardizing process in acute biliary disease.

The perioperative management of biliary disease (BD) is variable across institutions with suboptimal outcomes for patients and health care systems. This results in inefficient utilization of limited resources. The aim of the current study was to identify modifiable factors impacting patients' time to theater, intraoperative time, and time to discharge as the constituents of length of stay to guide creation of a perioperative management protocol to address this variability. Data were prospectively captured at Christchurch Hospital for all adult patients presenting for cholecystectomy between May 2015 and May 2022. Pre, post, and intraoperative factors were assessed for their impact on time to theater, operative time, and postoperative hours to discharge. Four thousand five hundred seventy-seven patients underwent cholecystectomy during the study period, of which 2807 (61%) were acute presentations and made up the cohort for analysis. Time to theater was significantly impacted by preoperative imaging type, while operative grade and the procedure type had the most clinically significant impact on operative time. Postoperatively time to discharge was significantly impacted by drain placement. Standardizing management of BD would likely result in significant savings for the health care system and improved outcomes for patients. The data seen here evidence the importance of appropriate imaging selection, intraoperative difficulty operative grade identification, and low suction drain selection. These data have been incorporated in a perioperative management protocol as standardization of care across the patient workflow in BD is a sensible approach for ensuring optimal use of scarce resources.

Amide and Multihydroxyl Complementary Tailored Metal-Organic Framework with Enhanced Glycan Affinity for Efficient Glycoproteomic Analysis.

Protein glycosylation is ubiquitous and crucial for regulating biological processes in organisms. Given the heterogeneity and low abundance of glycoproteins, efficient and specific enrichment procedures are required for the mass spectrometry analysis of glycopeptides. Hydrophilic interaction liquid chromatography (HILIC) has emerged as an effective strategy for glycopeptide enrichment. However, the relatively weak hydrophilic affinity restricts the achievement of a satisfactory enrichment performance. Here, we presented a rational design of an amide and multihydroxyl complementary tailored metal-organic framework, denoted as U6N/Pv@Glc, which exhibited ultrahydrophilicity and enhanced glycan affinity. Our results demonstrated a significant increase in glycopeptide coverage after enrichment, accompanied by extremely low detection limits (0.05 fmol μL-1) and high selectivity (IgG/BSA, 1:4000) as evaluated using trypsin-digested standard glycoproteins. A total of 379 glycopeptides and 247 intact glycopeptides (containing a total of 1577 site-specific N-glycans) were identified and characterized within human serum samples from individuals with type 2 diabetes in-depth. Additionally, we extended the application of this material to capture undigested glycoproteins, demonstrating potential compatibility with top-down MS analysis. These results highlight the promising potential of this novel material for comprehensive glycoproteomic analysis of every potential aspect.

Pattern recognition system for rapid detection of gases using microfluidic olfaction detector: A case study using methane and ethane

Two significant shortcomings of metal oxide semiconductor (MOS) sensors are their low selectivity and prolonged recovery time after exposure to target gases. Microfluidic olfaction detectors (MFOD), having an embedded MOS at the distal end of a microchannel, improve MOS selectivity but further prolong the recovery time due to the delay in the gas movement as the result of diffusion through the microchannel. This paper aims to reduce the sampling time of a single MFOD. Such reduction is achieved here by developing a pattern recognition system involving: (i) an ensemble of four heterogeneous base machine learning models, (ii) a Long-Short Term Memory Neural Network (LSTM) to construct a portion of the transient response, (iii) features from an additional fast response sensor, and (iv) detachment of MOS from the microchannel for accelerated recovery. Using data collected from methane and ethane as a case study, the results of classification and regression demonstrate the need for only 17.5% of the previously used response time without any loss in accuracy. This reduces the total testing cycle of an MFOD by 60%, further enhancing the ability of selective MFODs by enabling faster detection of gases.

Disentangling pH Effects on Electrocatalytic Reactions

Electrocatalysis is the key discipline to enable breakthrough advances in electrochemical energy technology and in the conversion of CO2 into renewable fuels and value-added chemicals. However, crucial electrocatalytic reactions are afflicted with sluggish kinetics and low selectivity. The electrolyte plays a vital role for the course of an electrocatalytic reactions and, in this realm, understanding the impact of the local pH is crucial for electrocatalyst development and design. The high interest in this topic in the research community is well-reflected in the recent literature, cf., e.g., Science 2022, 375 (6579). Explanations of pH effects remain controversial, even for the simplest model reactions, i.e., the hydrogen evolution/oxidation reaction and the formic acid oxidation reaction (FAOR), since a complex interplay of multiple interacting factors, centered around the local reaction environment and kinetic effects, must be disentangled. Theory and modeling are indispensable in this context. We will present a hierarchical framework that self-consistently couples the impacts of the microkinetics, mass transport and double layer charging effects (going beyond Frumkin corrections).1,2 In our modelling work, we will assess the role of distinct phenomena and parameters at play in a step-by-step fashion. The developed framework will be demonstrated for the FAOR and other electrocatalytic reactions.

Electrochemical Ammonia Production from Wastewater in a Flow Cell Reactor

Although its high carbon footprint, the Haber-Bosh (HB) process mainly dominates the NH3 production market. Indeed, H2 is mainly produced by fossil fuels steam reforming processes and the catalytic reaction between N2 and H2 requires high energy input, being carried out at high temperatures and pressures. Moreover, it should be considered that HB plants are not evenly distributed in the world, thus NH3 and its derivates transportation to the final user is a large portion of the overall environmental impact.1 Moreover, as the population is growing, the NH3 demand is increasing fast to sustain the massive fertilizer utilization.For these reasons, in the last years, the research has focused on the possibility of producing ammonia from direct nitrogen electrochemical reduction (NRR) in aqueous electrolytes under ambient conditions exploiting renewable energy. This process is limited by low selectivity at high current densities and low yield, due to the high dissociation energy of the N2 triple bond and the unavoidable hydrogen evolution reaction (HER).2 On the other hand, NO3 - can be easily converted into NH3 thanks to the lower activation energy, which makes the reaction thermodynamically favoured compared to N2 reduction.3 Due to the massive agriculture, NO3 - is one of the most abundant contaminants of underground waters and high levels in the human body can cause many diseases. Thus, the use of NO3 - to produce NH3 under ambient conditions can be carried out with lower energy consumption, but can also address the water pollution issue.4 The aim of our work is to assess the catalytic activity of commercial MoS2 and a synthesised Bi-based catalyst in a gas-diffusion electrode flow cell of 10 cm2 geometrical area. Such a setup has the advantage of guaranteeing a better mass transport of the active species and of being scaled up. The electrodes are mainly made by airbrush deposition of a catalyst ink on a carbon paper support, which allows obtaining a high electrochemical active surface as a result of its high porosity. Catalyst loading and NO3 - concentration was varied to find the optimal condition in terms of Faraday efficiency (FE) and yield. MoS2 catalyst showed good catalytic activity towards NH3, with a FE between 62%-77% and yield between 2.9-13 mmol g-1 h-1. On the other hand, synthesised Bi material showed 21% FE and 0.41 mmol h-1 g-1, probably due to Bi final oxidation state, which is not so active towards NH3 production. NH3 quantification has been carried out through UV-vis colourimetric method, using both Nessler’s and Berthelot’s reagents. Even if the concentration of NH3 is high enough to exclude that it can derive from contamination, more sensitive quantification is needed for these experiments, together with the quantification of side products, such as NO2 -, H2 and N2.

Computational Design of Durable and Selective Double Atom Catalysts Toward the Electrochemical NH3 Production: Role of Carbon Defects

Electrochemical NH3 production through nitrogen reduction reaction (N2RR) has received much attention as an energy-efficient way to produce ammonia, which is one of CO2-free hydrogen carriers. Note that electrochemical N2RR is carried out under mild temperature and pressure conditions, unlike the conventional Haber-Bosch process for chemical NH3 production, which requires a lot of energy due to the high temperature and pressure conditions. In recent years, the concept of double atom catalysts (indicated DAC) has been proposed to improve the reactivity of catalyst owing to the maximized utilization and 100% dispersion of active sites. The main problems in the development of DACs are the poor stability [the dissolution of double atoms into electrolyte and agglomeration of double atoms] and the low selectivity [lower onset potential for N2RR than HER (hydrogen evolution reaction)]. In this study, by using density functional theory (DFT) calculations, we examined the role of carbon defects (di, tri, quad vacancies) in graphene in enhancing the stability and selectivity in single and double atom catalysts (Ru, RuRu, and RuFe) and screened the novel double atom catalysts which have high selectivity to NH3 and durability at reaction conditions by ligand and support engineering. First, we found the optimal carbon defect structure to suppress the dissolution and agglomeration of double atoms and unraveled the factors to enhance the selectivity to N2RR over HER. Second, we developed the multiscale model to design the selective and durable double atom catalysts by identifying the descriptors to represent the durability and selectivity of double atoms catalysts. Next, we computationally screened the novel DACs (consisting of transition metals) by using the developed multiscale model. Finally, through the electronic structure calculation, we elucidated the underlying mechanism of defect in determining the durability and selectivity of double atom catalyst. Our study can provide the design factors to efficiently engineer the carbon defect and double atom in the development of NH3 production catalyst.

High-Sensitivity Hydrogen Sulfide Electrochemical Gas Sensor Based on CNT/Pt Cluster Electrode

Recently, due to the development of industrial technology, harmful gases discharged from industrial sites are gradually increasing, and as a result, inconvenience and civil complaints due to odor in the community are rapidly increasing. Among several types of harmful gases, hydrogen sulfide (H2S) is a colorless representative harmful gas that can cause pain through irritation of the mucous membranes of the eyes and respiratory tract, and can cause central nerve paralysis and suffocation at the same time when exposed to high concentrations. In addition, H2S is not only harmful to the human body, but also can create an unpleasant feeling by causing an odor even in a very small amount. Therefore, in order to manage H2S, research on a gas sensor capable of quickly and stably detecting H2S has been actively conducted. Most of the sensors that have been studied in the past are metal oxide-based semiconductor H2S gas sensors, which have high sensitivity, but have disadvantages in that low selectivity and high-temperature operating conditions are required. On the other hand, the electrochemical gas sensor can measure H2S gas with high selectivity because a chemical reaction occurs with respect to a specific gas depending on the type of electrolyte and electrode, and a potential difference due to electrons generated thereby is measured. Therefore, in this study, a CNT/Pt-based electrochemical H2S gas sensor capable of detecting at room temperature with high selectivity for H2S was developed. After forming a CNT thin film on a PTFE membrane, Pt was deposited through an E-beam to fabricate a working electrode capable of selectively detecting only H2S, and applied to an electrochemical H2S gas sensor using sulfuric acid (H2SO4) electrolyte. H2S was measured at a concentration of 100 to 10 ppm in units of 10 ppm using the manufactured CNT/Pt-based electrochemical H2S gas sensor. As a result, the amount of current change was confirmed to be 100uA at a concentration of 100 ppm, and the response time and recovery time were confirmed to be about 10 seconds.This work was supported by the Korea Innovation Foundation(INNOPOLIS) grant funded by the Korea government(MSIT) (2020-DD-UP-0348). This study has been conducted with the support of the Korea Institute of Industrial Technology as "Development of a thermal convection-type flow sensor with high-sensitivity for emergency patients breathing monitoring in real-time" (Kitech UI-23-0012).

A Novel Circuit-Based Model of a Bipolar Membrane Electrodialysis Reactor for Offshore Chemical Synthesis

Bipolar membrane electrodialysis (BPMED) is a sustainable and highly tuneable electrocatalytic technology used to efficiently manipulate the pH of liquid streams through the electrosynthesis of H+ and OH- ions from water. This emerging reactor technology employs a repeating stack of cation selective, anion selective, and bipolar membranes placed between two electrodes to create a repeating pattern of acid, base, and diluting flow chambers. The applied electric field induces water splitting at the bipolar interface, due to the presence of an electrocatalyst, the products of which are transported to the adjacent channels. The salient benefits of BPMED arise from its fundamental design, as it consumes electricity alone to correct stream pH, resulting in greater sustainability and tunability. However, current barriers to implementation of BPMED stem from a high energy consumption resulting from a high membrane electrical resistance or a low selectivity.A robust mathematical model of BPMED would be invaluable to identify situations where BPMED is commercially viable and the aspects in which technological advancements which would have the greatest effect. Due to the highly multifaceted and confounding nature of BPMED, the relationship between manipulated variables and process performance is unintuitive. The proposed model will thus have stark implications for process intensification.In this work, a novel circuit-based model of BPMED has been developed. The repeating unit cell is represented as a system of resistors in series, with membranes and electrolytes comprising the resistive elements. The water splitting potential is computed using Wein’s second law, Ohm’s law is used to relate the cell voltage to a current density on a differential volume, and Faraday’s law translates the current density to an ion flux. Ion speciation is computed in these differential volumes as well. Delayed differential material balances are then used to calculate the distribution of ionic species in time and space.A critical feature implemented is a novel model for the current efficiency, which is calculated as a function of the trans-membrane concentration difference. A single ‘innate current efficient’ experimental parameter is used, the value found when the trans-membrane concentrations are equal and is very often supplied by membrane manufactures.Experimental validation was conducted on a PC Cell BED 1-4 recirculating batch system. A stack of seven cell pairs of PC acid 60 (anion selective), PC SK (cation selective), and PC Bip (bipolar) membranes. Good agreement between the model and experimental results across a range of conditions and variables demonstrates the accuracy and robustness of the model.This model was subsequently used to investigate the power consumption of BPMED as a function of the desired outlet pH, and integrated into an Aspen Plus model. A process model was developed to simulate and optimise the electrosynthesis of concentrated sodium hydroxide and hydrochloric acid from seawater. The compact nature of BPMED and reliance on electricity only makes this a promising application for offshore drilling platforms. An economic analysis showed this to be a very preferable alternative to current technologies. Figure 1

(Invited) Selective and Efficient Electrochemical CO2 Reduction Reaction from Cu and Cu-M Binary Alloys

Electrochemical CO2 reduction reaction (CO2RR) has attracted a great deal of attention due to its potential to convert CO2 into valuable chemical fuels and feedstocks. The production of C2+ chemicals, such as ethylene and ethanol, from CO2RR is particularly important because of their large market demand. However, several challenges must be addressed before CO2RR can be commercially scaled up, including high overpotential, low selectivity, and poor CO2 solubility in aqueous solutions. In this presentation, I will discuss our recent efforts to overcome these challenges in CO2RR by using a gas diffusion electrode (GDE) to achieve a CO2RR current density of over 100 mA/cm2 in a flow reactor. First, I will highlight the crucial role of the local CO2RR environment in promoting C-C coupling on Cu surfaces, and I will present strategies for controlling this environment based on steady-state modeling and monodisperse Cu2O nanoparticles as a model catalyst system. Using this approach, we have been able to produce C2+ products, such as ethylene and ethanol, with a Faraday efficiency of over 70% at a current density of over 300 mA/cm2 in near-neutral electrolytes. Additionally, I will discuss the impact of alloying Cu with Ni and Zn on tailoring product selectivity. By introducing elements with different CO binding strengths, we can significantly alter the selectivity for hydrocarbons and alcohols. I will provide further details on these findings during the presentation.

Exploring the Mechanism of the Electrochemical Polymerization of CO2 over CeO2(110)

The reduction of CO2 is a promising route for the synthesis of renewable energy carriers and the removal of CO2 from the atmosphere to limit global warming. These negative emission technologies (NETs) require the conversion of carbon dioxide into a stable and easily storable form[1]. However, despite its potential, the development of suitable CO2 reduction catalysts is still in its infancy. Indeed state of the art catalysts suffer from high overpotentials, a low selectivity between possible products and a generally low yield of post CO products with two or more carbon atoms. Catalysts which even allow for the electrochemical polymerization of CO2 and thus, the direct formation of hard carbon were completely absent until the work of Esrafilzadeh et al.[2]. Using a liquid electrocatalyst consisting of Ga, In, Sn and Ce in a n,n-dimethylformamide (DMF) electrolyte they were able to polymerize CO2 electrochemically to a carbonaceous material. They hypothesized that the active catalyst consists of a cerium oxide which is reduced to metallic Ce in the process. However, no direct proof for this hypothesis was provided. Also a possible mechanism which could lead to the reported products is so far unknown.In this contribution we will explore the reaction mechanisms for the electrochemical polymerization of CO2 using density functional theory (DFT) modelling. In the initial step, the most likely active sites at Ce oxide are identified. This is then followed by a detailed analysis of the reaction route which is based on well known mechanisms in organic chemistry. We find that an oxygen defect rich CeO2(110) surface is most likely present under reaction conditions. [3] The reaction over this surface is initialized at oxygen defect sites. Chain propagation is then achieved through an electrochemical aldol condensation type mechanism (Figure 1). [3] References 1 J. Hilaire, J. C. Minx et al., Climatic Change, 2019, 157, 189.2 D. Esrafilzadeh, A. Zavabeti et al., Nature. Commun., 2019, 10, 865.3 F. Keller, J. Döhn, A. Groß, M. Busch, in preparation. Figure 1