Scalable Process Research Articles

Synthesis of Resorcinol and Chlorophenol from Irradiation of 1,3-Dichlorobenzene in a Water Ice Environment by Low-Energy Electrons

Dichlorobenzene is beneficial to industries, however, the release of this compound into the environment causes significant damage to ecosystems and human health, as it exhibits resistance to biodegradation. Here, we show that chlorophenol and resorcinol are synthesized from 1,3-dichlorobenzene in a water ice environment (1) directly on a poly-crystalline gold surface and (2) after low-energy (<12 eV) electron irradiation of admixture films. For the latter, at energies below 5.5 eV, the electrons solely decompose the chlorinated compound into radicals that further undergo reaction with surrounding water molecules. At higher energies (i.e., >5.5 eV) additional fragments, e.g., hydroxyl radicals, produced from the dissociation of water molecules, may also be involved in the chemistry. The present results may suggest strategies for potential eco-friendly, sustainable, and scalable processes for the mitigation of these halogenated compounds such as cold plasma and radiation, in which low-energy (<10 eV) electrons are predominantly produced.

Advances in Blade-Coated Organic Photovoltaics

Organic photovoltaics (OPVs) are a type of solar cell technology that uses organic semiconducting materials to convert sunlight into electricity. Unlike traditional silicon-based solar cells, OPVs are lightweight, flexible, and can be fabricated using cost-effective solution-processing techniques such as blade coating, enabling large-area device fabrication and is compatible with roll-to-roll manufacturing, making it ideal for OPV production. However, key challenges for OPVs, such as achieving high efficiency and scalability, maintaining film uniformity, enhancing material stability, optimizing processing techniques, mitigating environmental and health impacts, improving charge transport and reducing recombination losses, and overcoming performance degradation in large-area production are still under investigation. Recent developments include high-efficiency copolymer donors, ternary additives for optimized morphology, and the integration of novel interlayers and electrodes. Scalable processes such as accelerated blade coating and green solvents like o-methylanisole are also explored, highlighting their role in enhancing efficiency, stability, and sustainability. Additionally, insights into nanoparticle additives, solvent engineering, and molecular design underscore the potential for blade-coated OPVs to achieve high performance while maintaining environmental compatibility. These advancements collectively address challenges in efficiency and scalability, paving the way for OPVs to meet industrial demands and contribute to a greener energy landscape.

Toward Higher Energy Density All‐Solid‐State Batteries by Production of Freestanding Thin Solid Sulfidic Electrolyte Membranes in a Roll‐to‐Roll Process

AbstractAll‐solid‐state batteries (SSB) show great promise for the advancement of high‐energy batteries. To maximize the energy density, a key research interest lies in the development of ultrathin and highly conductive solid electrolyte (SE) layers. In this work, thin and flexible sulfide solid electrolyte membranes are fabricated and laminated onto a non‐woven fabric using a scalable and solvent‐free, continuous roll‐to‐roll process (DRYtraec). These membranes show significantly improved tensile strength compared to unsupported sheets, which facilitates cell assembly and allows a continuous component production using a single‐step calendering process. By tuning the thickness, densified membranes with thicknesses ranging from 40 to 160 µm are obtained after a compression step. The resulting SE membranes retain a high ionic conductivity (1.6 mS cm−1) at room temperature. An excellent rate capability is demonstrated in a SSB pouch cell with a Li2O–ZrO2‐coated LiNi0.9C0.05Mn0.05O2 cathode, a 55 µm thin SE membrane, and a columnar silicon anode fabricated by a scalable physical vapor deposition process. At stack level, a promising energy density of 673 Wh L−1 (and specific energy of 247 Wh kg−1) is achieved, showcasing the potential for high energy densities by reducing the SE membrane thickness while retaining good mechanical properties.

Highly Self-Adhesive and Biodegradable Silk Bioelectronics for All-In-One Imperceptible Long-Term Electrophysiological Biosignals Monitoring.

Skin-like bioelectronics offer a transformative technological frontier, catering to continuous and real-time yet highly imperceptible and socially discreet digital healthcare. The key technological breakthrough enabling these innovations stems from advancements in novel material synthesis, with unparalleled possibilities such as conformability, miniature footprint, and elasticity. However, existing solutions still lack desirable properties like self-adhesivity, breathability, biodegradability, transparency, and fail to offer a streamlined and scalable fabrication process. By addressing these challenges, inkjet-patterned protein-based skin-like silk bioelectronics (Silk-BioE) are presented, that integrate all the desirable material features that have been individually present in existing devices but never combined into a single embodiment. The all-in-one solution possesses excellent self-adhesiveness (300 N m-1) without synthetic adhesives, high breathability (1263g h-1 m-2) as well as swift biodegradability in soil within a mere 2 days. In addition, with an elastic modulus of ≈5kPa and a stretchability surpassing 600%, the soft electronics seamlessly replicate the mechanics of epidermis and form a conformal skin/electrode interface even on hairy regions of the body under severe perspiration. Therefore, coupled with a flexible readout circuitry, Silk-BioE can non-invasively monitor biosignals (i.e., ECG, EEG, EOG) in real-time for up to 12 h with benchmarking results against Ag/AgCl electrodes.

Asymmetric Transformations of Levulinic Acid to γ-Valerolactone and 5-Methylpyrrolidin-2-one Derivatives: Chiral Compounds with Biological Potential

Levulinic acid is a key platform molecule derived from biomass and readily available from natural sources, making it an attractive starting material for the synthesis of high-value chiral compounds. Among them, γ-valerolactone and 5-methylpyrrolidin-2-one derivatives are notable for their widespread occurrence and biological importance. This review paper highlights the importance of γ-valerolactone and 5-methylpyrrolidin-2-one derivatives as frameworks found in biologically active compounds and pharmaceuticals. It focuses on the asymmetric synthesis of these chiral building blocks from levulinic acid, highlighting recent advances in catalytic transformations that allow for efficient and selective transformations. The potential applications of these chiral molecules in medicine and industry underscore the importance of developing sustainable and scalable processes for their production. This review also examines future directions in the field, given the growing demand for green chemistry approaches and the increasing importance of chiral molecules in drug development.

Bio-derived graphitic carbon microspheres: A green approach for high-frequency microwave absorption

Bio-derived carbon materials have emerged as a sustainable alternative to non-renewable petroleum-based carbon sources, thanks to their reproducibility and environmental benefits. There is a strong demand for developing and efficiently utilizing carbon-based microwave absorbing materials (MAMs) that are lightweight, require low filler loading, and offer broadband absorption for electromagnetic wave (EM) applications. In this context, we successfully synthesized uniform carbon microspheres from the natural precursor turpentine oil using the chemical vapor deposition (CVD) technique at various temperatures. The sample prepared at 1000 °C (GC-1000) exhibited a uniform carbon microsphere morphology, as confirmed by XRD and Raman spectroscopy, and demonstrated extremely good microwave absorption properties. With a low filler loading of just 5 wt%, the GC-1000 sample achieved a minimum reflection loss (RL) of −39.77 dB at 10.21 GHz and an effective absorption bandwidth of 2.51 GHz at a matching thickness of only 2.8 mm. Additionally, this sample showed a total shielding effectiveness (SET) of −44.74 dB, surpassing the threshold required for commercial applications. The graphitic phase formation, confirmed by XRD and Raman analysis, acts as a conductive trap for electromagnetic radiation, and the high surface area of the uniform carbon microspheres facilitates multiple internal reflections, enhancing overall microwave absorption performance in the X-band region. Our lightweight, durable, bioderived carbon microspheres, synthesized through a cost-effective and scalable process, show significant potential for EM wave absorption in military and electromagnetic compatibility (EMC) devices.

Development of 3D-printed conducting microneedle-based electrochemical point-of-care device for transdermal sensing of chlorpromazine.

Despite the various benefits of chlorpromazine, its misuse and overdose may lead to severe side effects, therefore, creating a user-friendly point-of-care device for monitoring the levels of chlorpromazine drug to manage the potential side effects and ensure the effective and safe use of the medication is highly desired. In this report, we have demonstrated a simple and scalable manufacturing process for the development of a 3D-printed conducting microneedle array-based electrochemical point-of-care device for the minimally invasive sensing of chlorpromazine. We used an inkjet printer to print the carbon and silver ink onto a customized 3D-printed ultrasharp microneedle array for the preparation of counter, working, and reference electrodes. After physical characterization and electrochemical parameter optimization, the developed microneedle array-based three-electrode system was explored for the detection of chlorpromazine. The analytical results showed high sensitivity and selectivity toward chlorpromazine with a good linearity range from 5-120 μM and a low detection limit (0.09 μM). The proof-of-concept study results obtained from the skin-mimicking model indicated that the developed conductive microneedle array-based sensor can easily monitor the micromolar levels of chlorpromazine in artificial interstitial fluid; this type of system can be further explored for the development of other minimally invasive electrochemical biosensors.

CFD-Based Determination of Optimal Design and Operating Conditions of a Fermentation Reactor Using Bayesian Optimization.

The efficiency of fermentation reactors is significantly impacted by gas dispersion and concentration distribution, which are influenced by the reactor's design and operating conditions. As the process scales up, optimizing these parameters becomes crucial due to the pronounced concentration gradients that can arise. This study integrates the kinetics of the fermentation process with hydrodynamic analysis using Bayesian optimization to efficiently determine the optimal reactor design and operating conditions. By utilizing computational fluid dynamics (CFD) simulations, the study provides a comprehensive assessment of distributions ranging from gas supply to cell growth. The results demonstrate that a combination of wide baffle width, narrow impeller gap, slow gas flow rate, and high agitation speed significantly enhances reactor performance by improving gas distribution and minimizing stagnant zones. These findings underscore the importance of considering both kinetic and hydrodynamic factors to achieve more precise and scalable fermentation processes, offering valuable insights for industrial applications.

Nonspherical Particle Stabilized Emulsions Formed through Destabilization and Arrested Coalescence.

To form nonspherical emulsion droplets, the interfacial tension driving droplet sphericity must be overcome. This can be achieved through interfacial particle jamming; however, careful control of particle coverage is required. In this work, we present a scalable novel batch process to form nonspherical particle-stabilized emulsions. This is achieved by concurrently forming interfacially active particles and drastically accelerating emulsion destabilization through addition of electrolyte. To achieve this, surfactant-stabilized oil-in-water emulsions in the presence of dopamine were first produced. These emulsions were then treated with tris(hydroxymethyl)aminomethane hydrochloride buffer to both simultaneously initiate polymerization of dopamine in the emulsion continuous phase and reduce the Debye length of the system, thus accelerating droplet coalescence while forming surface-active particles. The concentration of buffer and imposed shear was then systematically varied, and the behavior at the interface was studied using pendent drop tensiometry and interfacial shear rheology. It was found that polydopamine nanoparticles formed in the emulsion continuous phase adsorbed to the reducing interface during coalescence, resulting in anisotropic droplets formed via arrested coalescence. Greater shear rates resulted in accelerated coalescence and formation of secondary droplets, whereas lower shear rates resulted in thicker interfacial films. The efficacy of this method was further demonstrated with a second system consisting of sodium dodecyl sulfate as the surfactant and polypyrrole particles, which also resulted in nonspherical droplets for optimized conditions.

Scalable Process Development of Ceritinib: Application of Statistical Design of Experiments

Scalable Process Development of Ceritinib: Application of Statistical Design of Experiments

Molybdenum Disulfide/Diselenide-Laser-Induced Graphene-Glycine Oxidase Composite for Electrochemical Sensing of Glyphosate.

The widespread use of the pesticide glyphosate has raised concerns regarding its potential health and environmental impacts. Consequently, there is an increasing demand for monitoring glyphosate levels in surface waters and food products. Currently, there is no commercially available rapid, field-deployable sensor capable of quantifying glyphosate concentrations in environmental samples. This study presents the development of a biosensor based on laser-induced graphene (LIG) that is functionalized with transition metal dichalcogenides (TMDs) and the enzyme glycine oxidase. The LIG is created through a scalable process using a CO2 laser to convert polyimide into a porous, nano/microstructured graphene architecture. The high surface area of LIG acts as a conductive scaffold for subsequent functionalization of both molybdenum disulfide (MoS2) and molybdenum diselenide (MoSe2) to further improve the electroactive surface area of the electrode. The resultant sensors, functionalizesd with the enzyme, demonstrate linear sensing ranges from 10 to 90 μM for glyphosate with detection limits of 4.0 and 6.1 μM for LIG electrodes modified with MoS2 and MoSe2, respectively. Furthermore, the sensors detect glyphosphate at negative working potentials, helping to minimize interference from endogeneous electroactive species and to provide consistent glyphosphate monitoring in actual food products (i.e., soybeans and pinto beans). Overall, the biosensors integrate scalable manufacturing with cost-effective TMDs and LIG, eliminating the need for costly noble metals in the biosensor design, and offering a reliable method for assessing glyphosate in food products.

Desorption of Cadmium from Cocoa Waste Using Organic Acids

This study evaluated the desorption of cadmium (Cd) from cocoa waste-derived flour using organic acids. Cocoa pods were collected from Antioquia and Casanare, Colombia, to analyze the geographical Cd content and its distribution within the pod tissues. Acid selection was performed using a multi-criteria decision-making (MCDM) matrix, and Cd desorption was assessed through a full factorial 23 experimental design, considering acid concentration, pulp density, and agitation speed. Additionally, the oxidation–reduction potential (ORP) was monitored as an indicator of the electrochemical dynamics of the process. The results indicated that pods from Casanare exhibited higher Cd concentrations (1.63 ± 0.20 ppm) compared with those from Antioquia (0.87 ± 0.22 ppm), with 49.31% of the metal being accumulated in the pod. Parameters of citric acid at 0.5 M, 5 g/L pulp density, and 120 rpm were found to be optimal for the Cd desorption process, achieving over 95% efficiency. Based on ORP monitoring, a heuristic was proposed to determine the contact time during leaching. This work outlines a scalable process for Cd desorption, adding value to cocoa industry waste for potential applications.

Concave Microwell Formation Induced by PDMS Water Vapor Permeability for Spheroid Generation.

This study introduces a novel method for the fabrication of concave microwells involving water vapor permeation through polydimethylsiloxane (PDMS). This method leverages the exceptional water vapor permeability of PDMS to enable a scalable and cost-effective fabrication process, addressing the limitations of existing techniques such as photolithography that are resource-intensive and complex. PDMS is more permeable to water vapor than to other gas molecules, resulting in the formation of microwells. Smooth-sloped concave microwells are formed by depositing droplets of 10% ethylene glycol on a PDMS substrate followed by curing at 70 °C and evaporation of water vapor. These microwells exhibit a unique structural gradient that is highly conducive for biological applications. Concave microwells were further used as a platform to generate animal cell spheroids, demonstrating their potential for three-dimensional cell culture. Unlike conventional methods, this approach allows precise control over microwell morphology by simply adjusting droplet size and curing conditions, offering enhanced tunability and reproducibility. The formation yield of these microwells is dependent on the volume of the water droplets, demonstrating the importance of droplet size in controlling microwell morphology. This approach provides a simple and effective method for creating microwells without complex lithographic processes, making it a highly promising tool for a range of biomedical applications, including tissue engineering, cancer research, and high-throughput drug screening.

Designing a Prototype Platform for Real-Time Event Extraction: A Scalable Natural Language Processing and Data Mining Approach

In this paper, we present a modular, high-performance prototype platform for real-time event extraction, designed to address key challenges in processing large volumes of unstructured data across applications like crisis management, social media monitoring and news aggregation. The prototype integrates advanced natural language processing (NLP) techniques (Term Frequency–Inverse Document Frequency (TF-IDF), Latent Semantic Indexing (LSI), Named Entity Recognition (NER)) with data mining strategies to improve precision in relevance scoring, clustering and entity extraction. The platform is designed to handle real-time constraints in an efficient manner, by combining TF-IDF, LSI and NER into a hybrid pipeline. Unlike the transformer-based architectures that often struggle with latency, our prototype is scalable and flexible enough to support various domains like disaster management and social media monitoring. The initial quantitative and qualitative evaluations demonstrate the platform’s efficiency, accuracy, scalability, and are validated by metrics like F1-score, response time, and user satisfaction. Its design has a balance between fast computation and precise semantic analysis, and this can make it effective for applications that necessitate rapid processing. This prototype offers a robust foundation for high-frequency data processing, adaptable and scalable for real-time scenarios. In our future work, we will further explore contextual understanding, scalability through microservices and cross-platform data fusion for expanded event coverage.

Development of an Inherently Safe and Scalable Nickel-Catalyzed Borylation Process of an Aryl Sulfamate

Development of an Inherently Safe and Scalable Nickel-Catalyzed Borylation Process of an Aryl Sulfamate

Microfabrication of Organic Electrochemical Transistors for High‐Performance Integrated Bioelectronics

AbstractIn bioelectronics, organic electrochemical transistors (OECTs) are pivotal in bridging electronic devices and biological systems, especially in sensing, neuromorphic interfacing, and biological monitoring. Current OECT fabrication methods face challenges due to conductive polymers incompatibility with photoresist solvents and the complexity of multi‐step parylene‐C coatings. This work introduces a scalable photolithographic fabrication process for high‐performance OECTs using the prototypical conductive polymer poly(3,4‐ethylenedioxythiophene) doped with poly(styrene sulfonate) (PEDOT:PSS). The method employs a two‐layer photoresist approach with controlled cross‐linking, incorporating (3‐glycidyloxypropyl)trimethoxysilane to pattern polymeric channel and encapsulate electrodes. This process yields high‐performance OECTs with highly reproducible characteristics, typical ON/OFF current modulation of 5 103, and transconductance normalized to channel thickness > 200 S cm−1. To avoid cytotoxic Ag/AgCl pellets, the impact of scaling polarizable gates is analyzed on device performance, including bare Au, protein‐functionalized, and PEDOT:PSS gates. The analysis provides design rules to tailor OECT performance for diverse applications. The effectiveness of the approach is demonstrated by integrating OECTs with polarizable gates in current‐driven circuit configuration, allowing ion detection at a supply voltage as low as 0.4 V with a sensitivity of up to 2620 mV dec−1, the highest ever reported. These advancements open opportunities for next‐generation integrated bioelectronics and neuromorphic biosensing.

IPSC-Derived Biological Pacemaker-From Bench to Bedside.

Induced pluripotent stem cell (iPSC)-derived biological pacemakers have emerged as an alternative to traditional electronic pacemakers for managing cardiac arrhythmias. While effective, electronic pacemakers face challenges such as device failure, lead complications, and surgical risks, particularly in children. iPSC-derived pacemakers offer a promising solution by mimicking the sinoatrial node's natural pacemaking function, providing a more physiological approach to rhythm control. These cells can differentiate into cardiomyocytes capable of autonomous electrical activity, integrating into heart tissue. However, challenges such as achieving cellular maturity, long-term functionality, and immune response remain significant barriers to clinical translation. Future research should focus on refining gene-editing techniques, optimizing differentiation, and developing scalable production processes to enhance the safety and effectiveness of these biological pacemakers. With further advancements, iPSC-derived pacemakers could offer a patient-specific, durable alternative for cardiac rhythm management. This review discusses key advancements in differentiation protocols and preclinical studies, demonstrating their potential in treating dysrhythmias.

Fully Aqueous‐Processed Li‐Ion Electrodes with Ultra‐High Loading and Potential for Roll‐to‐Roll Processing

AbstractIn this study, high‐ and ultra‐high‐loading NMC622‐based cathodes (7.0 and 18.0 mAh/cm2) and graphite‐based anodes (9.0 and 22.5 mAh/cm2) were prepared by using a porous carbon structure as current collector. All electrodes in this work were prepared by an NMP‐free, PFAS‐free and scalable process. Full cells with areal capacities of 7 mAh/cm2 and 18 mAh/cm2 were assembled and tested. The results show an excellent cycling stability, reaching up to 950 cycles at 10 mA/cm2 for the cells with ultra‐high‐loading electrodes (capacity 18 mAh/cm2) and 650 cycles at 8 mA/cm2 for the cells with high‐loading electrodes (capacity of 7 mAh/cm2). The influence of cathode porosity on the electrochemical performance in cells capacity of 7 mAh/cm2 showed that a lower porosity leads to a poorer rate capability as well as a worse cycling capability (400 cycles at 6 mA/cm2). Post‐mortem analysis reveal that the anode aging is more pronounced during full cell cycling. Further the scalability of the production process was demonstrated by using a padder tool. With that, cathodes with a loading of 5 mAh/cm2 were produced in a roll‐to‐roll process.

BDLT-IoMT—a novel architecture: SVM machine learning for robust and secure data processing in Internet of Medical Things with blockchain cybersecurity

The integration of artificial intelligence (AI) has caused information and communication technology (ICT) to undergo a number of recent rapid fluctuations. These changes have primarily affected the areas of management, end-to-end device interconnectivity, resource organization, communication, networking, and application-related aspects of ICT. Owing to the complex structure of applicational connectedness, evaluating each of the aforementioned opportunities concurrently reflects the idea of heterogeneity. The association of multiple end devices, particularly in interoperable space, integrity, privacy protection, security, provenance, and the massive volume of everyday media data generated in the modern healthcare setting could also provide significant issues. To address these issues, decentralized, secure, economical resource optimization, and intelligent network activities and organization are necessary. Blockchain technology plays a crucial role in providing distributed storage data organization, sharing, and exchange for automated decision-making, privacy, and security in AI-enabled machine learning (ML) models. However, machine learning models—support vector machine, in particular—have a significant impact on the growth of distributed consortium networks and the exchange of information among connected nodes, resolving issues with resource management, scalability, and data processing. By resolving the three main problems of seamless data integrity, peer-to-peer communication between nodes, and infrastructure security, we provide a novel interoperable technique in this proposed architecture. The approach is unique, as demonstrated by the simulation-based results, which display huge differences of 1.37%, 1.56%, and 1.87%, respectively. The background for the evaluation consists of the following three areas: (i) infrastructure security to protect automated decision-making; (ii) integrity between smooth data sharing and exchange; and (iii) network resource optimization to enable smooth communication across heterogeneous devices.

Tackling Heterogeneous Light Detection and Ranging-Camera Alignment Challenges in Dynamic Environments: A Review for Object Detection.

Object detection is an essential computer vision task that identifies and locates objects within images or videos and is crucial for applications such as autonomous driving, robotics, and augmented reality. Light Detection and Ranging (LiDAR) and camera sensors are widely used for reliable object detection. These sensors produce heterogeneous data due to differences in data format, spatial resolution, and environmental responsiveness. Existing review articles on object detection predominantly focus on the statistical analysis of fusion algorithms, often overlooking the complexities of aligning data from these distinct modalities, especially dynamic environment data alignment. This paper addresses the challenges of heterogeneous LiDAR-camera alignment in dynamic environments by surveying over 20 alignment methods for three-dimensional (3D) object detection, focusing on research published between 2019 and 2024. This study introduces the core concepts of multimodal 3D object detection, emphasizing the importance of integrating data from different sensor modalities for accurate object recognition in dynamic environments. The survey then delves into a detailed comparison of recent heterogeneous alignment methods, analyzing critical approaches found in the literature, and identifying their strengths and limitations. A classification of methods for aligning heterogeneous data in 3D object detection is presented. This paper also highlights the critical challenges in aligning multimodal data, including dynamic environments, sensor fusion, scalability, and real-time processing. These limitations are thoroughly discussed, and potential future research directions are proposed to address current gaps and advance the state-of-the-art. By summarizing the latest advancements and highlighting open challenges, this survey aims to stimulate further research and innovation in heterogeneous alignment methods for multimodal 3D object detection, thereby pushing the boundaries of what is currently achievable in this rapidly evolving domain.