Key Experimental Parameters Research Articles

Experimental and numerical study of microbubble-enhanced separation of aged microplastics in a slurry flow

Microplastics (MPs) are widespread in aquatic environments, causing ecological issues worldwide. Microbubble (MB) technology has been extensively used in various industries due to its high efficiency, low cost, and sustainability, particularly in separation processes. However, its application in slurry flows containing solid particles, such as slurries with sands, remains underexplored. This study develops microbubble (MB)-enhanced separation of microplastics (MPs) in slurry flow containing 10 % sands in a pipeline. Key experimental parameters, including particle density, size and surface wettability of MPs, and bubble volume fraction, were systematically examined at the flow velocity of 2 m/s to compare the removal efficiency of MPs. As the volume fraction of bubbles in the flow varied from 0 to 0.5 %, the removal efficiency of aged polystyrene (PS) MPs was increased by 95 %. Computational fluid dynamics (CFD) simulations were performed to reveal the influence of MBs on the distribution of MPs in the slurry flow. The validated models predict that microbubbles promote accumulation of MPs near the pipe top by 7 times. Such localized accumulation of MPs in the slurry may be attributed to high removal efficiency by MBs. This work presents an innovative and efficient method for MB generated in-situ for markedly improved separation efficiency of MPs from slurry flows.

Ultrathin Copper Monosulfide Films for an Optically Semitransparent, Highly Selective Ammonia Chemosensor.

Transition-metal sulfides are emerging as promising materials for chemiresistive gas sensors─a field still dominated by semiconducting metal oxides. Despite the availability of materials with tunable electronic, optical, physical, and chemical properties, few studies have moved beyond synthesis to provide strategies for enhancing gas sensing performance through material modification. Here, we present a simple, scalable synthetic strategy for developing an optically semitransparent, flexible NH3 gas sensor with a highly uniform, ultrathin CuS (covellite) active sensing layer. The optical and chemical properties of the CuS were precisely controlled near the percolation threshold of thin-film formation by varying key experimental parameters such as the Cu film thickness (<10 nm) and the sulfurization time (∼90 s) under ambient conditions. Experimental and computational studies of CuS and its NH3 sensing characteristics identify key physicochemical properties. The controlled surface chemistry and morphology of the ultrathin CuS layer demonstrate its effectiveness in functional NH3 sensing devices, which achieve a calculated detection limit of 1.38 ppm for NH3 gas at 150 °C, along with exceptional mechanical robustness and optical semitransparency in the visible-light spectrum.

Efficiency and mechanistic insights of photocatalytic degradation and sterilization utilizing g-C3N4/WO3-x Z-scheme heterojunction under full-spectrum light

Designing highly efficient full-spectrum responsive Z-scheme heterojunction for wastewater decontamination and disinfection is urgently essential. Herein, a novel Z-scheme g-C3N4/WO3-x heterojunction was successfully synthesized by a facile wet impregnation method for the highly efficient photocatalytic degradation and sterilization. Benefiting from the accelerated charge separation, broadened light absorption to near infrared region, and appropriate band energy, optimized g-C3N4/WO3-x heterojunction exhibited photocatalytic degradation of 86.3 % and 97.4 % tetracycline in 2 h under visible light and full-spectrum light, respectively. Meanwhile, 6.5-log of Escherichia coli strains could also be inactivated by optimized g-C3N4/WO3-x heterojunction within 45 min and 15 min under visible light and full-spectrum light, respectively. Impressively, it also exhibited desirable anti-interference ability and satisfying photocatalytic degradation capacity with various key experimental parameters. The plausible degradation pathways of TC and the main active species involved in the photocatalysis were investigated based on liquid chromatography-mass spectrometer (LC-MS) and electron paramagnetic resonance (EPR) analysis. Mineralization process of TC was further confirmed by three-dimensional fluorescence spectra (3D EMMs). Besides, Toxicity Estimation Software Tool (T.E.S.T.) and Ecological Structure-Activity Relationships (ECOSAR) program were applied to predict the noxiousness of TC and its potential intermediates. The results suggested that the excitotoxicity of intermediates generally decreased relative to the pristine TC. Finally, we propose a plausible enhancement mechanism of photocatalytic degradation and sterilization. This work sheds a new light on the design of novel full-spectrum responsive Z-scheme heterojunction for environmental remediation.

Experimental and numerical study on polypropylene fibers reinforced concrete slabs with corroded reinforcement under monotonic loading

The degradation of structural performance due to reinforcement corrosion in reinforced concrete (RC) structures and the subsequent measures to improve the mechanical properties of corroded RC structures have garnered significant interest. This study investigates the structural performance of corroded polypropylene fiber RC slabs through both experimental and numerical approaches. Specimens were subjected to accelerated corrosion via electrochemical methods to simulate rebar corrosion. Key experimental parameters include polypropylene fiber volume fractions of 0% and 3%, design corrosion levels of 0%, 5%, and 10%, and both one-way and two-way constraints. The Digital Image Correlation (DIC) technique was employed for data acquisition. Load, deflection, strain, and crack morphology data were collected during loading. Results indicate that reinforcement corrosion increases the maximum crack width during loading, while a 3% polypropylene fiber volume fraction reduces this width by 20% to 48% at the same load level. Polypropylene fibers also enhance the peak loads and corresponding deflections of unidirectional and bidirectional specimens, with a more pronounced increase in unidirectional specimens of 11.3% and 15.4%, respectively. Although corrosion reduces the load-carrying capacity of the specimens, the inclusion of 3% polypropylene fibers significantly mitigates this reduction. A numerical model, incorporating rebar corrosion and polypropylene fibers through appropriate material constitutive models, was developed and validated against experimental results. The model accurately simulates the mechanical behavior of polypropylene fiber RC slabs with corroded reinforcement.

Line-field confocal optical coherence tomography based on tandem interferometry with a focus-tunable lens.

This article introduces an innovative line-field confocal optical coherence tomography (LC-OCT) system based on tandem interferometry, featuring a focus-tunable lens for dynamic focusing. The principle of tandem interferometry is first recalled, and an analytical expression of the interferometric signal detected is established in order to identify the influence of key experimental parameters. The LC-OCT system is based on a Linnik-type imaging interferometer with a focus-tunable lens for focus scanning, coupled to a Michelson-type compensating interferometer using a piezoelectric linear translation stage for coherence plane scanning. The system achieves axial and lateral image resolutions of approximately 1 µm over the entire imaging depth (400 µm), in line with conventional LC-OCT. Vertical section images (B-scans) of skin acquired at 14.3 fps reveal distinguishable structures within the epidermis and dermis. Using refocusing and stitching, images of a tissue phantom were obtained with an imaging depth superior to 1.4 mm. The system holds promise for LC-OCT miniaturization, along with enhanced imaging speed and extended imaging depth.

Removal of Pb(II) pollution by algae-Fe-Ni magnetic nanocomposite

A magnetic nanocomposite material was synthesized by combining Chaetomorpha Algae with a Fe–Ni alloy. The dry algae, Fe, and Ni were mechanically alloyed using a ball milling technique in an argon atmosphere. The resulting Algae-Fe-Ni Magnetic Nanocomposite (AFNMN) was characterized using various analytical techniques, including particle size distribution (PSD) analysis, Brunauer-Emmett-Teller (BET) surface area analysis, scanning electron microscopy (SEM), differential scanning calorimetry (DSC), vibrating sample magnetometry (VSM), atomic absorption spectroscopy (AAS), and Fourier transform infrared (FTIR) spectroscopy. Multiple isotherm models were employed to study the adsorption of Pb(II) ions onto the AFNMN material. Density functional theory (DFT) was applied to predict the most stable amino acids for the removal of Pb(II) pollutants from a set of 14 amino acids. To optimize the Pb(II) uptake performance, three key experimental parameters were fine-tuned: pH, temperature, and reactor vessel geometry. Four different optimization methods were utilized, including response surface methodology (RSM), fuzzy logic, adaptive network-based fuzzy inference system (ANFIS), and artificial neural network genetic algorithms (ANN-GA). Additionally, a heat transfer simulation was conducted to determine the optimal vessel positions for achieving the desired temperature variations within the reactor during the adsorption process.

Heavy metal removal performance of capacitive deionization technology studied by machine learning

Capacitive deionization (CDI) technology is utilized for efficient treatment of industrial wastewater, characterized by low energy consumption and environmental protection. In order to comprehend the correlation between key experimental parameters and the electrosorption capacity (EC) of heavy metals in CDI technology, this paper employs a genetic algorithm (GA) to optimize a backpropagation artificial neural network (BPANN) for predicting the EC of CDI technology for heavy metal ions, with the characteristics of electrode materials converted into numerical characteristics for further analysis. Compared to the BPANN, the optimized GABPANN model demonstrates superior predictive accuracy. It achieves automatic adjustment of the hidden layer structure, neuron count, and transfer functions. Furthermore, the grey relational analysis indicates that the electrode material and the initial pH value of the solution are pivotal in determining the EC of heavy metal ions. This underscores the efficacy of machine learning (ML) algorithms in forecasting the nonlinear dynamics of CDI systems and elucidates the influence of individual parameters on the efficacy of heavy metal removal.

Investigation of europium(III) uptake from highly sulphate solution via cloud point extraction by mono-Schiff base combined with Triton X-100

ABSTRACT Owing to its unique physico-chemical properties, europium is one of the most precious and sought-after rare earth elements in the field of high technology. The major economic and commercial importance of such an element, combined with the pollution risks associated with its intensive use, require the development of efficient and eco-compatible recovery and recycling processes. This study focuses on the recovery of europium from highly saline sulphate media (0.5 mol/L) using an environmentally friendly two-phase aqueous extraction technique (known as cloud point extraction (CPE)), using 2((phenylimino)methyl)phenol mono-Schiff base (HPIMP) as the extractant and Triton X-100 as the non-ionic surfactant. The influence of key experimental parameters such as pH, extractant concentration, surfactant concentration and separation temperature on the europium extraction process was systematically studied and optimized. Under optimum experimental conditions, a quasi-quantitative extraction with a minimal volume fraction of surfactant-rich phase (φs = 0.025), and concentration factor of (CF = 38) was achieved at pH 9.8, in one stage. The analysis of the extraction data revealed that the CPE of europium(III) takes place by a cation exchange-solvation mechanism. The stoichiometry of the complex extracted into the surfactant-rich phase was ascertained to have a composition of 1:2 [Eu:HPIMP] with the slope analysis method. A higher extraction constant was obtained for CPE compared with conventional solvent extraction, confirming the feasibility and usefulness of CPE for Eu(III) recovery. On the other hand, this new HPIMP/Triton X-100 chelating system showed superior extractability for Eu(III) in the CPE process relative to other systems reported previously.

Improving azo dyes degradation by CoFe2O4-activated peroxymonosulfate: Performance, degradation mechanism, and ecotoxicity assessment

Development of an effective catalyst is essential to eliminate the risks to ecological environment and human health caused by the accumulation of azo dyes in environmental water. Herein, the cobalt ferrite (CoFe2O4) nanoparticles (NPs), facilely prepared by a one-pot hydrothermal procedure, were developed for peroxymonosulfate (PMS) activation towards Congo red (CR) degradations. The key experimental parameters were comprehensively investigated to optimize the degradation performance for CR in CoFe2O4/PMS system. Under optimal conditions, the CoFe2O4 NPs exhibited an excellent capability for PMS activation to degrade CR with the degradation efficiency of nearly 100 % in a wide range of pH values (3.0–9.0). The electron paramagnetic resonance (EPR) and quenching experiments confirmed that the entire CR degradation process was dominantly by the non-radical (1O2) and surface-bound SO4·−and ·OH. CoFe2O4 NPs displayed the remarkable stability and reusability, with degradation efficiency of 85.5 % even after six recycles. The possible degradation pathway in CR degradation process was proposed, and the qualitative analysis and ecotoxicity of the degradation intermediates were investigated. This work provided a facile and green strategy to prepare a prospective catalyst for the efficient removal of azo dyes by PMS activation.

Nanohybrid layered clay composite decorated with polyaniline for intensified Cr(VI) removal through enhanced Cr(VI) reduction

Hexavalent chromium (Cr(VI)) is mainly detected as a harmful anion in aquatic ecosystems. In this study, a novel nanohybrid layered clay composite decorated with polyaniline (PANI) (PANI/LDH@MMt) was successfully synthesized by a layer-by-layer assembly strategy and utilized for Cr(VI) removal. Layered double hydroxide (LDH) and montmorillonite (MMt) in nanohybrid layered clay (LDH@MMt) can facilitate Cr(VI) elimination through reinforced Cr(VI) reduction. Some key experimental parameters were evaluated in detail for their potential impact on Cr(VI) removal. The experimental results illustrated that PANI/LDH@MMt displayed high Cr(VI) removal efficiency (>99 %) at most appropriate conditions and maintained over 95 % performance even in ionic coexistence and natural water environments. Kinetic models, isothermal models, and thermodynamic analyses were also employed to explore the Cr(VI) removal behavior on PANI/LDH@MMt. Finally, the mechanism analysis suggested that Cr(VI) could be captured by electrostatic interaction of -NH-+, -N=+, and –OH2+, and anion exchange of LDH, and reduced to Cr(III) by -NH-. Subsequently, Cr(III) could chelate with -N=, −NH−, and −OH, complex with OH-, and be immobilized by MMt through cation exchange. This study presents a new insight into the reasonable construction of highly efficient adsorbents with low cost for Cr(VI) removal.

Efficient extraction methods and callus culture of quercetin from Indian white radish: yield analysis via HPLC quantification and assessment of cytotoxic activity

SummaryIndian white radish Co. 1 (Raphanus sativus L.) contains medicinal quercetin, and its commercial value supports large‐scale quercetin isolation. Various extraction methods, including ultra‐assisted extraction (UAE), maceration extraction (ME), Soxhlet extraction (SE), conventional extraction (CSE) and serial maceration extraction (SME), were employed to extract quercetin from radish leaf sections. RP‐HPLC‐optimising key experimental parameters yielded a linear response for the individual target compounds in the concentration range, with a limit of quantification (LOQ) of 2.2 μg mL−1 (r2 = 0.9995), a limit of detection (LOD) of 2.2 μg per 1.0 g of crushed leaves and repeatability within the relative standard deviation (RSD) of 0.23–0.37%. For in vitro callus cultures, 2,4‐dichlorophenoxyacetic acid (2,4‐D), 6‐benzylaminopurine (BAP) and zeatin were used for callus induction from in vitro leaf segments of radish. MS medium enriched with 2,4‐D (0.5 mg) induced the highest percentage of callus at 4 weeks. Among the extraction methods, the SME method yielded the highest recovery of quercetin (96.9%; 1.92 mg g−1 DW), phenolic (26.07 mg g−1 DW) and flavonoid (34.03 mg g−1 DW), compared to other methods and solvents. The callus extract included 0.5 mg of 2,4‐D, 32.07 mg of phenolic, 42.03 mg of flavonoid and 6.46 mg of quercetin. The presence of phytocompounds and quercetin was confirmed by GC–MS/MS and RP‐HPLC. The isolated quercetin (57.9 μg) also showed lethal effects on HT‐29 human colon cancer cells. This method may be effective for evaluating quercetin in radish extracts.

Sub-Doppler spectroscopy of the Cs atom 6S1/2-7P1/2 transition at 459 nm in a microfabricated vapor cell.

We report on the characterization of sub-Doppler resonances detected by probing the 6S1/2 - 7P1/2 transition of the Cs atom at 459 nm in a microfabricated vapor cell. The dependence of the sub-Doppler resonance (linewidth, amplitude) on some key experimental parameters, including the laser intensity and the cell temperature, is investigated. These narrow atomic resonances are of interest for high-resolution spectroscopy and instrumentation and may constitute the basis of a high-stability microcell optical standard.

Recycling and reusing potential of disposable low-density polyethylene plastic waste for flexible paver tile construction for outdoor application

Plastic waste disposal has escalated into a serious global concern due to the non-biodegradable nature of plastics, which are composed of high-molecular-mass organic polymers along with other ingredients. Therefore, this study focuses on reusing and recycling LDPE plastic waste as a binding agent in paver tile production. This aligns with global sustainability goals by promoting resource efficiency and reducing waste generation. The investigation aims to address the environmental impact of plastic waste by finding sustainable solutions for its management. This includes exploring the feasibility and viability of using LDPE plastic waste in paver tile production as a means of recycling and reusing locally collected waste. The LDPE waste plastic collection, identification, milling, and melting at 170 °C. Subsequently, the sampled sand, sieved to a size of ≤0.75 mm, was blended with molten plastic in a specified proportion and then molded to create paving tiles using a hydraulic press machine. The researchers utilized response surface methodology (RSM) combined with Box-Benken designs (BBD) to optimize three key experimental parameters (plastic-to-sand ratio: 10 %, 25 %, 40 %; time: 2, 5, 8 min, pressure: 1, 3, 5 MPa) influencing mechanical properties of paver tiles, including water absorption (WA), flexural strength (FS), and compressive strength (CS). The result revealed that the optimal combination of 25 % waste plastic, 5 min, and 3 MPa of pressure resulted in a maximum flexural strength (FS) of 3.689 MPa and compressive strength (CS) of 4.141 MPa, with an average water absorption (WA) of 0.322 %. Therefore, the mechanical properties of the developed tiles met the desired standard. In conclusion, the mechanical qualities of the tiles were promising, indicating that reusing waste LDPE plastic to create paver tiles presents an appealing option for plastic waste disposal. The composite paver tiles exhibited promising attributes for outdoor applications, such as park pavement and outdoor public spaces, owing to their favorable mechanical properties and low water absorption.

Systematic Optimization of Automated Phosphopeptide Enrichment for High-Sensitivity Phosphoproteomics

Improving coverage, robustness, and sensitivity is crucial for routine phosphoproteomics analysis by single-shot liquid chromatography-tandem mass spectrometry (LC-MS/MS) from minimal peptide inputs. Here, we systematically optimized key experimental parameters for automated on-bead phosphoproteomics sample preparation with a focus on low-input samples. Assessing the number of identified phosphopeptides, enrichment efficiency, site localization scores, and relative enrichment of multiply-phosphorylated peptides pinpointed critical variables influencing the resulting phosphoproteome. Optimizing glycolic acid concentration in the loading buffer, percentage of ammonium hydroxide in the elution buffer, peptide-to-beads ratio, binding time, sample, and loading buffer volumes allowed us to confidently identify >16,000 phosphopeptides in half-an-hour LC-MS/MS on an Orbitrap Exploris 480 using 30 μg of peptides as starting material. Furthermore, we evaluated how sequential enrichment can boost phosphoproteome coverage and showed that pooling fractions into a single LC-MS/MS analysis increased the depth. We also present an alternative phosphopeptide enrichment strategy based on stepwise addition of beads thereby boosting phosphoproteome coverage by 20%. Finally, we applied our optimized strategy to evaluate phosphoproteome depth with the Orbitrap Astral MS using a cell dilution series and were able to identify >32,000 phosphopeptides from 0.5 million HeLa cells in half-an-hour LC-MS/MS using narrow-window data-independent acquisition (nDIA).

Biogas Production through Anaerobic Codigestion of Distillery Wastewater Sludge and Disposable Spent Yeast

The ongoing industrial transformation in developing countries, including Ethiopia, has resulted in a significant increase in harmful pollutants in the environment. Various industrial activities release toxic wastewater sludge and spent yeast into the surrounding ecosystem, posing risks to public health and the environment. However, these waste materials have the potential for energy extraction and recycling. This study aimed to investigate and harness the biogas potential through anaerobic codigestion of distillery wastewater sludge and waste yeast. The researchers employed a response surface approach utilizing Box–Behnken experimental designs (BBD) to assess the three key experimental parameters influencing biogas yield: pH levels (6, 7, and 8), volume ratio (85, 92, and 99%), and temperature (33, 36.5, and 40°C). Before and after the digestion process, the researchers measured the total solids (TS), biological oxygen demand (BOD5), chemical oxygen demand (COD), and pH of all substrates. Additionally, measurements of temperature, total nitrate, and total phosphate were taken before digestion. The methane yield was modeled using a second-order polynomial through the BBD method in Design Expert software, with a p value threshold of ≤5%. The results showed that the maximum methane yield of 61.18% was achieved at a pH of 7, a temperature of 36.5°C, and a volume ratio of 92%. Conversely, the lowest methane yield of 40.13% was obtained at a pH of 6, a temperature of 33°C, and a volume ratio of 92%. The linear and quadratic values of the model (A, B, C, A2, B2, and C2) were determined to be significant terms, with p values ≤5%. Overall, the biogas yields obtained from the anaerobic codigestion of distillery wastewater and waste yeast were promising. This process has the potential to effectively remove BOD5, COD, and TS from distillery spent wash and sludge. The findings suggest that anaerobic codigestion could be a viable approach for both energy production and waste management in the setting of distillery waste.

Deep eutectic solvent-based ferrofluid for highly efficient preconcentration and determination of metronidazole by vortex-assisted liquid-phase microextraction under experimental design optimization

To determine metronidazole in water samples, we developed an environmentally friendly, efficient, and straightforward ferrofluid-based liquid-liquid microextraction sample pretreatment technique. It is coupled with a high-performance liquid chromatography-ultraviolet analytical technique known for its sensitivity, speed, and precision. The magnetic separation of metronidazole-containing ferrofluid from the matrix was effortlessly achieved through the application of an external magnetic field, eliminating the need for centrifugation. Response surface optimization was employed to systematically determine the key experimental parameters influencing extraction efficiency, including pH, NaCl concentration, ferrofluid volume, and vortex duration. With a low detection limit (0.116 ng mL−1), a broad linear range between 0.5 and 700 ng mL−1 was achieved at optimal conditions. Additionally, acceptable spiking recoveries (94.3–97.3 %) and RSD values (≤3.7 %) for intra- and inter-day precision were attained in water samples. In conclusion, the effectiveness of the vortex and ferrofluid combination, along with the convenience of collection and elimination of the need for centrifugation, bestows a highly valuable technique for determining metronidazole in water samples.

Review of Smog Chamber Experiments for Secondary Organic Aerosol Formation

In this study, we reviewed smog chamber systems and methodologies used in secondary organic aerosol (SOA) formation studies. Many important chambers across the world have been reviewed, including 18 American, 24 European, and 8 Asian chambers. The characteristics of the chambers (location, reactor size, wall materials, and light sources), measurement systems (popular equipment and working principles), and methodologies (SOA yield calculation and wall-loss correction) are summarized. This review discussed key experimental parameters such as surface-to-volume ratio (S/V), temperature, relative humidity, light intensity, and wall effect that influence the results of the experiment, and how the methodologies have evolved for more accurate simulation of atmospheric processes. In addition, this review identifies the sources of uncertainties in finding SOA yields that are originated from experimental systems and methodologies used in previous studies. The intensity of the installed artificial lights (photolysis rate of NO2 varied from 0.1/min to 0.40/min), SOA density assumption (varied from 1 g/cm3 to 1.45 g/cm3), wall-loss management, and background contaminants were identified as important sources of uncertainty. The methodologies developed in previous studies to minimize those uncertainties are also discussed.

Assessment of the Purity of IMM-H014 and Its Related Substances for the Treatment of Metabolic-Associated Fatty Liver Disease Using Quantitative Nuclear Magnetic Resonance Spectroscopy.

An accurate, rapid, and selective quantitative nuclear magnetic resonance method was developed and validated to assess the purity of IMM-H014, a novel drug for the treatment of metabolic-associated fatty liver disease (MAFLD), and four related substances (impurities I, II, III, and IV). In this study, we obtained spectra of IMM--H014 and related substances in deuterated chloroform using dimethyl terephthalate (DMT) as the internal standard reference. Quantification was performed using the 1H resonance signals at δ 8.13 ppm for DMT and δ 6.5-7.5 ppm for IMM-H014 and its related substances. Several key experimental parameters were investigated and optimized, such as pulse angle and relaxation delay. Methodology validation was conducted based on the International Council for Harmonization guidelines and verified with satisfactory specificity, precision, linearity, accuracy, robustness, and stability. In addition, the calibration results of the samples were consistent with those obtained from the mass balance method. Thus, this research provides a reliable and practical protocol for purity analysis of IMM-H014 and its critical impurities and contributes to subsequent clinical quality control research.

A comprehensive assessment of exome capture methods for RNA sequencing of formalin-fixed and paraffin-embedded samples

RNA-Seq analysis of Formalin-Fixed and Paraffin-Embedded (FFPE) samples has emerged as a highly effective approach and is increasingly being used in clinical research and drug development. However, the processing and storage of FFPE samples are known to cause extensive degradation of RNAs, which limits the discovery of gene expression or gene fusion-based biomarkers using RNA sequencing, particularly methods reliant on Poly(A) enrichment. Recently, researchers have developed an exome targeted RNA-Seq methodology that utilizes biotinylated oligonucleotide probes to enrich RNA transcripts of interest, which could overcome these limitations. Nevertheless, the standardization of this experimental framework, including probe designs, sample multiplexing, sequencing read length, and bioinformatic pipelines, remains an essential requirement. In this study, we conducted a comprehensive comparison of three main commercially available exome capture kits and evaluated key experimental parameters, to provide the overview of the advantages and limitations associated with the selection of library preparation protocols and sequencing platforms. The results provide valuable insights into the best practices for obtaining high-quality data from FFPE samples.

Optimizing the use of a gas diffusion electrode setup for CO2 electrolysis imitating a zero-gap MEA design

The lack of a robust and standardized experimental test bed to investigate the performance of catalyst materials for the electrochemical CO2 reduction reaction (ECO2RR) is one of the major challenges in this field of research. To best reproduce and mimic commercially relevant conditions for catalyst screening and testing, gas diffusion electrode (GDE) setups attract rising attention as an alternative to conventional aqueous-based setups such as the H-cell configuration. Zero-gap electrolyzer designs show promising features for upscaling to the commercial scale. In this study, we scrutinize further our recently introduced “zero-gap GDE” setup or more correct half-cell MEA design for the CO2RR. Using an Au electrocatalyst as a model system we simulate the anode conditions in a zero-gap electrolyzer and identify/report the key experimental parameters to control the catalyst layer preparation to optimize the activity and selectivity of the catalyst. Among others, it is demonstrated that supported Au nanoparticles (NPs) result in significantly higher current densities when compared to unsupported counterparts, however, the supporting also renders the NPs prone to agglomeration during electrolysis.