Methodology For Characterization Research Articles

Optimization of dilution rate and mixed carbon feed for continuous production of recombinant plant sucrose:sucrose 1-fructosyltransferase in Komagataella phaffii.

The trisaccharide 1-kestose, a major constituent of commercial fructooligosaccharide (FOS) formulations, shows a superior prebiotic effect compared to higher-chain FOS. The plant sucrose:sucrose 1-fructosyltransferases (1-SST) are extensively used for selective synthesis of lower chain FOS. In this study, enhanced recombinant (r) 1-SST production was achieved in Komagataella phaffii (formerly Pichia pastoris) containing three copies of a codon-optimized Festuca arundinacea 1-SST gene. R1-SST production reached 47U/mL at the shake-flask level after a 96-h methanol induction phase. A chemostat-based strain characterization methodology was adopted to assess the influence of specific growth rate (µ) on cell-specific r1-SST productivity (Qp) and cell-specific oxygen uptake rate (Qo) under two different feeding strategies across dilution rates from 0.02 to 0.05h-1. The methanol-sorbitol co-feeding strategy significantly reduced Qo by 46 ± 2.4% compared to methanol-only feeding without compromising r1-SST productivity. Based on the data, a dilution rate of 0.025h-1 was applied for continuous cultivation of recombinant cells to achieve a sustained r1-SST productivity of 5000 ± 64.4U/L/h for 15days.

SpChar: Characterizing the sparse puzzle via decision trees

Sparse matrix computation is crucial in various modern applications, including large-scale graph analytics, deep learning, and recommender systems. The performance of sparse kernels varies greatly depending on the structure of the input matrix, making it difficult to gain a comprehensive understanding of sparse computation and its relationship to inputs, algorithms, and target machine architecture. Despite extensive research on certain sparse kernels, such as Sparse Matrix-Vector Multiplication (SpMV), the overall family of sparse algorithms has yet to be investigated as a whole. This paper introduces SpChar, a workload characterization methodology for general sparse computation. SpChar employs tree-based models to identify the most relevant hardware and input characteristics, starting from hardware and input-related metrics gathered from Performance Monitoring Counters (PMCs) and matrices. Our analysis enables the creation of a characterization loop that facilitates the optimization of sparse computation by mapping the impact of architectural features to inputs and algorithmic choices. We apply SpChar to more than 600 matrices from the SuiteSparse Matrix collection and three state-of-the-art Arm Central Processing Units (CPUs) to determine the critical hardware and software characteristics that affect sparse computation. In our analysis, we determine that the biggest limiting factors for high-performance sparse computation are (1) the latency of the memory system, (2) the pipeline flush overhead resulting from branch misprediction, and (3) the poor reuse of cached elements. Additionally, we propose software and hardware optimizations that designers can implement to create a platform suitable for sparse computation. We then investigate these optimizations using the gem5 simulator to achieve a significant speedup of up to 2.63× compared to a CPU where the optimizations are not applied.

Exploring the Potential of Recycled Polymers for 3D Printing Applications: A Review

The integration of recycled polymers into additive manufacturing (AM) processes offers a promising opportunity for advancing sustainability within the manufacturing industry. This review paper summarizes existing research and developments related to the use of recycled materials in AM, focusing on distinct polymers, such as polylactic acid (PLA), polyethylene terephthalate (PET), and acrylonitrile butadiene styrene (ABS), among others. Key topics explored include the availability of recycled filaments on the market, challenges associated with material variability and traceability, and efforts toward establishing ethical product standards and sustainability characterization methodologies. Regulatory considerations and standards development by organizations such as ASTM and ISO are discussed, along with recommendations for future advancements in improving the sustainability of filament recycling and achieving net-zero emissions in AM processes. The collective efforts outlined in this paper underscore the potential of recycled polymers in AM to foster a more sustainable and environmentally friendly manufacturing industry.

Scrutinizing the influence of vanadium (V5+) in Gd:MgO nanoparticles in their physicochemical properties and photocatalytic properties

Using a simple precipitation technique the preparation of V doped Gd:MgO nanoparticles are successfully achieved. Using various conventional characterization methodologies the microscopic structure, morphological and physicochemical characteristics of the synthesized particles were analyzed. Observed optical bandgap of the material lays in UV region hence photocatalytic experiments were carried out using UV light illumination. Toxic textile dye namely methyl orange (MO) and methylene blue (MB) was used as model pollutant. Among the synthesized nanoparticles 5 wt% V doped Gd:MgO performed well in photocatalytic degradation of MO and MB dye. Surface charge of the prepared photocatalyst (point of zero charge PZC) was analyzed by salt titration method. pH influence in the degradation process was scrutinized by maintaining different pH values.

Emphasizing the Potential of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) Spectroscopy Combined with Chemometrics, for Classification of Greek Grape Marc Spirits

Grape marc spirits, such as the Greek tsipouro/tsikoudia, reflect the cultural heritage of winemaking traditions worldwide. This study explored the application of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy combined with chemometrics for its potential as a fast classification methodology for spirit characterization. ATR-FTIR spectra from thirty-nine products revealed distinctive bands corresponding to various chemical constituents, such as alcohols, organic acids, water, carbohydrates, and phenols. Principal Component Analysis (PCA) was performed on all acquired ATR-FTIR data and 78.50% of the total variance in the data was explained. Also, partial least squares–discriminant analysis (PLS-DA), used for the classification of products based on their major geographic origin, gave a correct classification of 89.5% for the north and 83.3% for the south of Greece. Classification of the type of distillations used was with 74.36% accuracy. Significant markers were identified through analysis, such as those associated with the O-H bending vibrations of phenols or alcohols, contributing to the discrimination of grape marc spirits from Crete when compared with the other four main geographical origin designations. By combining ATR-FTIR spectroscopy with chemometrics, this research gave insights into the origins and compositional variations of the spirits, providing an opportunity for a quality control assessment tool.

Comparative study of experimental assessment methodologies for the dynamic characterization of elastic elements

Comparative study of experimental assessment methodologies for the dynamic characterization of elastic elements

Review of Ti3C2Tx MXene Nanofluids: Synthesis, Characterization, and Applications

MXene-based nanofluids are important because of their thermal and rheological properties, influencing scientific and industrial applications. MXenes, made of titanium carbides and nitrides, are investigated for nanofluid enhancement. This review covers MXene nanofluid creation, characterization, and application. To produce nanoscale MXene particles, two-dimensional materials are dissolved and dispersed in a base fluid. The stability and efficacy of MXene nanofluids depend on production methods, such as chemical exfoliation, electrochemical etching, and mechanical delamination. Improved heat transfer coefficients and thermal conductivity from MXene nanofluids help resolve heat transfer, energy efficiency, and thermal control problems. This extensive review also addresses long-term safety and the necessity for standardized characterization methodologies, helping researchers optimize MXene-based nanofluids in many technological fields

Artificial Intelligence Approach for Bio-Based Materials’ Characterization and Explanation

This paper introduces a numerical methodology for classifying and identifying types of bio-based materials through experimental thermal characterization. In contrast to prevailing approaches that primarily focus on thermal conductivity, our characterization methodology encompasses several thermal parameters. In this paper, the physical characteristics of seven types of bio-based concrete were analyzed, focusing on the thermal properties of palm- and esparto-fiber-reinforced concrete. The proposed method uses artificial intelligence techniques, specifically the k-means clustering approach, to segregate data into homogeneous groups with shared thermal characteristics. This enables the elucidation of insights and recommendations regarding the utilization of bio-based insulation in building applications. The results show that the k-means algorithm is able to efficiently classify the reference concrete (RC) with a performance of up to 71%. Additionally, the technique is more accurate when retaining only six centroids, which, among other things, allows all the characteristics associated with each type of concrete to be grouped and identified. Indeed, whether for k clusters k = 7 or k = 5, the technique was not able to predict the typical characteristics of 2% or 3% esparto concrete (EC).

Surface Enhancement of Titanium-Based Coatings on Commercial Hard Steel Cutting Tools

This study investigates the mechanical properties, surface integrity, and chemical configuration of PVD-coated high-speed steel (HSS) cutting tools, with a particular focus on titanium nitride (TiN) and titanium aluminium nitride (TiAlN) coatings. A range of characterisation methodologies were employed to examine the impact of pre-coating surface conditions on the resulting coatings. This impact includes the effects of gas bubble production and unequal distribution of elements, which are two unwanted occurrences. Notwithstanding these difficulties, coatings applied on surfaces that were highly polished exhibited more consistency in their mechanical and elemental characteristics, with a thickness ranging from 2 to 4 µm. The study of mechanical characteristics confirms a significant increase in hardness, from an initial value of roughly 1000 HV0.5 for untreated tools to 1300 HV0.5 for tools with physical vapour deposition (PVD) coatings. Although PVD coatings produced on an industrial scale might not exceed the quality of coatings manufactured in a laboratory, they do offer substantial enhancements in terms of hardness. This study highlights the significant importance of thorough surface preparation in achieving enhanced coating performance, hence contributing to the efforts to prolong the lifespan of tools and enhance their performance even under demanding operational circumstances.

Using Capillary Electrophoresis to Investigate Protein Conformational and Compositional Heterogeneity.

Detailed insights into protein structure/function relationships require robust characterization methodologies. Free-solution capillary electrophoresis (CE) is a unique separation technique which is sensitive to the conformation and/or composition of proteins, and therefore provides information on the heterogeneity of these properties. Three unrelated, conformationally/compositionally-altered proteins were separated by CE. An electrophoretic mobility distribution was determined for each protein along with its conformational and/or compositional heterogeneity. The CE results were compared with molar mass distributions obtained from size-exclusion chromatography coupled to light scattering (SEC-MALS). Bovine serum albumin multimers and two monomeric species were separated, highlighting variations in conformational/compositional heterogeneity among the multimers. Analysis of yeast alcohol dehydrogenase resolved two monomeric conformers and various tetrameric species, illustrating the impact of zinc ion removal and disulfide bond reduction on the protein's heterogeneity. The apo (calcium-free) and holo forms of bovine α-lactalbumin were separated and differences in the species' heterogeneity were measured; by contrast, the SEC-MALS profiles were identical. Comparative analysis of these structurally unrelated proteins provided novel insights into the interplay between molar mass and conformational/compositional heterogeneity. Overall, this study expands the utility of CE by demonstrating its capacity to discern protein species and their heterogeneity, properties which are not readily accessible by other analytical techniques.

An Enhanced Approach for High-Strain Plasticity in Flat Anisotropic Specimens with Progressively Distorting Neck Sections

An Enhanced Approach for High-Strain Plasticity in Flat Anisotropic Specimens with Progressively Distorting Neck Sections

A methodology for phase characterization in pellet feed using digital microscopy and deep learning

This work proposes a new method for characterizing pellet feed, employing Deep Learning (DL) and Convolutional Neural Networks (CNNs). The main minerals in the composition of the studied pellet feed are hematite, magnetite, goethite, and quartz. Over time, several characterization methodologies have been developed that use Digital Microscopy and Image Analysis tools. The greatest difficulties in this characterization lie in differentiating the textures of hematite particles, the different shapes of their crystals, or discriminating between quartz and resin in reflected light optical microscopy images. This work proposes a mineral characterization methodology based on the Mask R-CNN algorithm. The goal is to perform instance segmentation, that is, to identify, classify, and segment objects in the images. Two DL models were combined: the BF Model performs instance segmentation for the compact, porous, martite, and goethite classes in images obtained in Bright Field mode, and the CPOL Model uses images acquired in Circularly Polarized Light to segment the monocrystalline, polycrystalline, and martite classes. An F1-score of around 80% was obtained for the BF Model and around 90% for the CPOL Model. The results were promising and can be improved as the training image database increases.

Integrated Approach of Historical Landscape Characterisation Techniques and Remote Sensing for the Definition of Predictive Models and Scenario Analysis in the Planning of Archaeological Areas

This study explores the synergistic integration of remote sensing (RS) and Historical Landscape Characterisation (HLC) methodology as an innovative, multi-scalar and holistic approach to enhance archaeological planning. The goal is to maximize the effectiveness of the investigations, optimizing data collection and improving the contextual understanding of the sites. In fact, these methodologies can significantly contribute to the documentation, conservation, planning and valorisation of archaeological areas. By integrating RS data with features detected by HLC, a complete picture is obtained that facilitates a deeper understanding of the landscape and historical dynamics. This article will explain the combined approach of RS and HLC, presenting some methodologies key to improving the precision and effectiveness of archaeological planning. This integration facilitates the sustainable preservation of archaeological resources and contributes to the conscious management of cultural heritage in the context of contemporary development. The paper demonstrates, through a case study, how the application of the two methodologies (RS and HLC) in an integrated form can provide an exhaustive interpretation of the territory in which the archaeological area is located, which can represent an exhaustive knowledge base on which to set up effective processes for the strategic territorial planning of archaeological areas.

Functionalized Binders Boost High‐Capacity Anode Materials

AbstractThe burgeoning field of energy storage battery innovation has sparked a relentless pursuit of high‐capacity anode materials to meet the escalating demand for improved energy density. Typically, these materials for batteries experience significant volume changes during cycles, which severely test the structural integrity and lifespan of electrode configurations. High‐performance binders have emerged as a critical component in addressing this challenge. Although they represent a small proportion of the battery's composition, binders play a pivotal role in enhancing electrochemical efficiency, safety, and cost‐effectiveness of batteries. The advancement of high‐capacity anode materials has rendered traditional binders inadequate, prompting the development of functional binders that are increasingly being refined to meet these requirements. This article began by outlining the role and requirements of binders within electrodes, examining cutting‐edge characterization methodologies, and discussing the “structure‐function” paradigm that underpins binder selection. It then showcased the research advancements in identifying suitable binders for high‐capacity anode materials, including silicon (Si), phosphorus (P), tin (Sn), antimony (Sb), and germanium (Ge). In summary, the article contemplated the future direction of binder development and application in high‐capacity electrode materials. The aim is to facilitate the progression of high‐performance, high‐capacity anodes, thereby accelerating the development of high‐energy‐density lithium‐ion and sodium‐ion batteries.

Characterization of Freezing Processes in Drug Substance Bottles by Ice Core Sampling

Freezing of biological drug substance (DS) is a critical unit operation that may impact product quality, potentially leading to protein aggregation and sub-visible particle formation. Cryo-concentration has been identified as a critical parameter to impact protein stability during freezing and should therefore be minimized. The macroscopic cryo-concentration, in the following only referred to as cryo-concentration, is majorly influenced by the freezing rate, which is in turn impacted by product independent process parameters such as the DS container, its size and fill level, and the freezing equipment. (At-scale) process characterization studies are crucial to understand and optimize freezing processes. However, evaluating cryo-concentration requires sampling of the frozen bulk, which is typically performed by cutting the ice block into pieces for subsequent analysis. Also, the large amount of product requirement for these studies is a major limitation. In this study, we report the development of a simple methodology for experimental characterization of frozen DS in bottles at relevant scale using a surrogate solution. The novel ice core sampling technique identifies the axial ice core in the center to be indicative for cryo-concentration, which was measured by osmolality, and concentrations of histidine and polysorbate 80 (PS80), whereas osmolality revealed to be a sensitive read-out. Finally, we exemplify the suitability of the method to study cryo-concentration in DS bottles by comparing cryo-concentrations from different freezing protocols (-80°C vs -40°C). Prolonged stress times during freezing correlated to a higher extent of cryo-concentration quantified by osmolality in the axial center of a 2 L DS bottle.Graphical

Colouring solutions for building integrated photovoltaic modules: A review

As global decarbonisation requires the widespread adoption of solar photovoltaic (PV) electricity, addressing challenges related to land use has become relevant. The conflict between PV installations and other land uses, such as forestry or agriculture, highlights the urgency for alternative solutions. Integrating PV technology into the built environment is a compelling strategy to mitigate these challenges, enabling electricity generation precisely where it is needed. In the context of buildings integrated photovoltaics (BIPV), PV modules serve a dual purpose, functioning both as electricity generators and integral components of the architectural design. Therefore, the architecture requirements — specifically in terms of shape, size, and colour— become relevant for BIPV modules. This paper offers a general overview of the diverse colouring technologies employed for BIPV modules, describing their functioning, challenges, and advantages. An examination of the current landscape of coloured PV products involving considerations of pricing and power output is presented. Additionally, this work addresses the critical topics of reliability and stability in colour solutions, outlining methodologies for quantitative colour characterization. It provides foresight into the potential challenges facing installations in the future and explores the multifaceted social, economic, and environmental implications of this evolving technology.

Extraction of bioactive compounds from Vitex megapotamica: A study and selection of variables

AbstractFruits are widely used to obtain and study bioactive compounds. Among them, the tarumã (Vitex megapotamica) is still understudied. The extraction of bioactive compounds from the powdered pulp of the ripe fruit of the tarumã was studied from the selection of several variables of the extraction process through the experimental design Plackett–Burman: the pH, the solid:liquid ratio, agitation, and temperature in an extraction time of 3 h. The extracts obtained were evaluated for antioxidant activity by 2,2′‐azino‐bis‐(3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS), 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH), and for total phenolic compounds, as well as the presence of flavonoids, anthocyanins, carotenoids, and identification of bioactive compounds was assessed by high‐performance liquid chromatography (HPLC). Using the experimental design, the best extraction condition was defined with a pH of 5, solid:liquid ratio of 1:30, stirring at 100 rpm, with a temperature of 80°C, obtaining 104.21 mg Gallic Acid Equivalent (GAE) 100 g−1 for phenolic compounds total, 742.71 μmol Trolox g−1 for ABTS, and EC50 of 2884.98 mg L−1 for DPPH. From HPLC, the presence of fumaric acid, gallic acid, p‐coumaric acid, and caffeic acid in the extracts was detected. Regarding flavonoids, anthocyanins, and carotenoids, the values obtained were 6.38 mg ECG g−1, 1.67 mg ECG g−1, and 2.89 mg 100 g−1, respectively. The selection of extraction conditions allowed obtaining better levels of bioactive compounds in the powdered pulp of tarumã extract, even with the use of water as a solvent, to avoid the presence of chemical residues in the extract, with antioxidant potential and viability for application in food products.Practical applicationsRecent research suggests a change in perspective regarding the consumption of healthier foods from plants and fruits that have important health properties. In this regard, tarumã (Vitex megapotamica) fruit has been standing out as a potential source of bioactive compounds with significant medicinal properties. The extracts obtained have a significant amount of phenolic compounds, as well as the presence of flavonoids, anthocyanins, and carotenoids, in which all of these have great potential bioactive activities. Thus, a good methodology of extraction and characterization of tarumã extract becomes a crucial part of any food, chemical, or pharmaceutical industry sector. In this regard, the present study with experimental design Plackett–Burman extraction is the way ahead due to high bioactive retention and the cost implications of the process.

Rational Design of Amorphous Nanomaterials for Enhanced Electrochemical CO2 and Nitrate Reduction

Amorphous materials are distinguished by their exceptional attributes, notably their expansive surface area and the profusion of active sites they present. Consequently, the amorphization process stands as an efficacious strategy to augment the catalytic efficacy of electrocatalysts. This is achieved through the meticulous construction of the surface architecture and the precise modulation of the electronic configuration of these materials. Therefore, this review aims to offer a thorough examination of the latest progress in the application of amorphous materials for the enhancement of electrocatalytic processes, with a particular emphasis on the nitrate (NO3‐) reduction reaction (NITRR) and the carbon dioxide reduction reaction (CO2RR). Initially, we delve into the structural benefits inherent to amorphous materials, outlining the diverse synthesis techniques and characterization methodologies utilized in their development. Following this, we illustrate the utilization of various amorphous materials in NITRR and CO2RR, accentuating how the amorphous framework influences electrocatalytic activities. Concludingly, we encapsulate the merits and the obstacles encountered in the application of amorphous electrocatalysts for NITRR and CO2RR, whilst also forecasting the future direction for the creation of innovative amorphous electrocatalysts.

Effect of Quorum Sensing Molecules on the Quality of Bacterial Nanocellulose Materials.

Bacterial nanocellulose (BNC) biofilms, produced by various bacterial species, such as Gluconacetobacter xylinus, represent a highly promising multifunctional material characterized by distinctive physiochemical properties. These biofilms have demonstrated remarkable versatility as nano biomaterials, finding extensive applications across medical, defense, electronics, optics, and food industries. In contrast to plant cellulose, BNC biofilms exhibit numerous advantages, including elevated purity and crystallinity, expansive surface area, robustness, and excellent biocompatibility, making them exceptional multifunctional materials. However, their production with consistent morphological properties and their transformation into practical forms present challenges. This difficulty often arises from the heterogeneity in cell density, which is influenced by the presence of N-acyl-homoserine lactones (AHLs) serving as quorum sensing signaling molecules during the biosynthesis of BNC biofilms. In this study, we employed surface characterization methodologies including scanning electron microscopy, energy-dispersive spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy, and atomic force microscopy to characterize BNC biofilms derived from growth media supplemented with varying concentrations of distinct N-acyl-homoserine lactone signaling molecules. The data obtained through these analytical techniques elucidated that the morphological properties of the BNC biofilms were influenced by the specific AHLs, signaling molecules, introduced into the growth media. These findings lay the groundwork for future exploration of leveraging synthetic biology and biomimetic methods for tailoring BNC with predetermined morphological properties.

Challenges and Advances in Wide‐Temperature Electrolytes for Lithium‐Ion Batteries

AbstractLithium‐ion batteries (LIBs) have gained widespread attention due to their numerous advantages, including high energy density, prolonged cycle life, and environmental friendliness. Nevertheless, their electrochemical performance deteriorates rapidly under extreme temperature conditions, accompanied by a series of safety issues. Electrolyte optimization has emerged as a crucial and feasible strategy to expand the operational temperature range of LIBs. This review comprehensively summarizes the challenges, advances, and characterization methodologies of electrolytes at both subzero and elevated temperatures. Initially, it discusses the degradation mechanisms of different types of electrolytes at extreme temperatures, integrates recent advances, and offers insights into future research directions. Subsequently, various experimental techniques are systematically presented to evaluate the fundamental physical properties, stability, and dynamic behaviors of electrolytes in non‐ambient environments. Finally, it also provides relevant computational methods across the electronic, molecular, and macroscopic scales, and explores the application of high‐throughput techniques in this field. This review offers valuable guidance for breaking the working temperature limits of electrolytes and promoting the development of next‐generation LIBs.