Search Results (175)

With rising demand for clean energy and uncertainty surrounding large-scale renewable deployment, ammonia has emerged as a viable carrier for hydrogen storage and transportation. This study conducts a global patent-based analysis of ammonia-to-hydrogen production technologies to determine technological maturity, dominant design pathways, and emerging innovation trends. A statistically robust retrieval, screening, and classification process, based on the PRISMA guidelines, was employed to screen, sort, and analyze 708 relevant patent families systematically. Patent families were categorized according to synthesis processes, catalyst types, and technological fields. The findings indicate that electrochemical, plasma-based, photocatalytic, and hybrid systems are being increasingly investigated as alternatives to low-temperature processes. At the same time, thermal catalytic cracking remains the most established and widely used method. Significant advances in reactor engineering, system integration, and catalyst design have been observed, especially in Asia. While national hydrogen initiatives, such as those in Brunei, highlight the policy importance of ammonia-based hydrogen systems, the findings primarily provide a global overview of technological maturity and innovation trajectories, thereby facilitating long-term transitions to cleaner hydrogen pathways. Full article

The economic and legal framework is transforming with the change in the globalization paradigm, accompanied by structural and quantitative changes in intellectual property assessment. This study aims to justify commercialization and analyze the innovation management of intellectual property as a fundamental socio-economic institution and improve theoretical perspectives on its current development processes. This study surveyed 100 companies to identify the factors determining intellectual property use and its commercialization. The analysis of the structure of intellectual property revealed a 14% decrease in trademark applications and a 2% increase in patent applications. This research highlights the specifics of intellectual property generation through machine learning: mass creation of new objects, reduction in innovation product development cycles, increased accuracy of market demand forecasting, and adaptive problem solving. An analysis of budget expenditures on intellectual property in the EU based on the specific value of patent activity identified five classification groups (ranging from 0.17 to 0.23% to 1.23–2.26% of GDP), each exhibiting different economic activities and innovation intensity. Full article

Background/Objectives: Periodontal disease is a condition marked by the destruction of tooth-supporting tissues, driven by an exaggerated immune response to an unbalanced dental biofilm. Conventional treatments struggle due to antimicrobial resistance and the biofilm’s protective extracellular matrix. This study evaluates the potential of bacteriophages as an innovative strategy for managing periodontal disease. Methods: This research employed a qualitative approach using Discursive Textual Analysis, with IRAMUTEQ version 0.8 alpha 7 (Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires) software. The search was conducted in the Orbit Intelligence and PubMed databases, for patents and scholarly articles, respectively. The textual data underwent Descending Hierarchical Classification, Correspondence Factor Analysis, and Similarity Analysis to identify core themes and relationships between words. Results: The analysis revealed an increase in research and patent filings concerning phage therapy for periodontal disease since 2017, emphasizing its market potential. The primary centers for intellectual property activity were identified as China and the United States. The study identified five focus areas: Genomic/Structural Characterization, Patent Formulations, Etiology, Therapeutic Efficacy, and Ecology/Phage Interactions. Lytic phages were shown to be effective against prominent pathogens such as Fusobacterium nucleatum and Enterococcus faecalis. Conversely, the lysogenic phages poses a potential risk, as they may transfer resistance and virulence factors, enhancing pathogenicity. Conclusions: Phage therapy is a promising approach to address antimicrobial resistance and biofilm challenges in periodontitis management. Key challenges include the need for the clinical validation of formulations and stable delivery systems for the subgingival area. Future strategies, such as phage genetic engineering and data-driven cocktail design, are crucial for enhancing efficacy and overcoming regulatory hurdles. Full article

Solar energy enhances the energy and environmental performance of coal gasification by lowering carbon emissions and increasing the yield and quality of synthesis gas. This patent review surveys recent global advances in solar thermochemical reactors for coal gasification, focusing on key innovations disclosed in patent applications and grants, with particular attention to technologies that improve process efficiency and sustainability. The novelty of the review is that unlike most patent reviews that focus primarily on statistical indicators such as application counts, geography, and classification, this work integrates qualitative analysis of specific technical solutions alongside statistical evaluation. This combined approach enables a deeper assessment of technological maturity and practical applicability. Fifteen patents from different countries were reviewed. The largest number (8, 53%) belongs to the United States. China has the second place with 4 (27%). The remaining countries (the EU, Korea, and Russia) hold 1 patent (7% each). The present work emphasises the technological and engineering solutions associated with the integration of solar energy into gasification processes. The author’s design is free of the disadvantages of its counterparts and is a simplified design with a high degree of adaptability to various types of fuel, including brown coal, biomass, and other carbon-containing materials. Full article

Patent foramen ovale (PFO) is present in roughly one quarter of adults and is over-represented among younger patients with cryptogenic ischemic stroke. The past decade has produced compelling evidence from randomized trials showing that PFO closure is beneficial than medical therapy in preventing recurrent ischemic stroke in appropriately selected patients. Despite this, anticoagulation continues to be used when closure is not feasible, declined, contraindicated, or considered after recurrent events. The observation that some patients experience “breakthrough” stroke or transient ischemic attack (TIA) despite therapeutic anticoagulation raises a critical question: why does medical therapy fail in PFO-associated stroke, and why does closure appear superior? This narrative review synthesizes the latest evidence on the pathophysiology of PFO-associated stroke, with attention to mechanisms that remain incompletely addressed by anticoagulation. It analyzes randomized trial data comparing antiplatelet therapy, anticoagulation, and transcatheter closure. It examines the role of high-risk PFO anatomical characteristics, the Risk of Paradoxical Embolism (RoPE) score, and the PFO-Associated Stroke Causal Likelihood (PASCAL) classification in understanding medical therapy failure. Additionally, the review explores whether PFO “type” predicts anticoagulation failure and highlights future research directions needed to further optimize therapy. In conclusion, in appropriately selected patients with high-risk PFO features, closure provides greater stroke risk reduction than medical therapy alone, albeit with small absolute risk differences and a procedural risk of atrial fibrillation. Full article

Electrospinning, Forcespinning^®, and melt electrowriting are becoming increasingly important fiber-based fabrication technologies for tissue engineering and drug delivery applications. Despite their scientific and industrial relevance, their patent landscape has not been systematically examined, which limits the understanding of technological dynamics and translational applications. This study addresses this gap through a patentometric analysis conducted within a Competitive Technology Intelligence framework. A total of 3557 active and granted Extended Patent Families from 2020 to 2024 were analyzed to identify temporal patterns, geographic distribution, key innovators, industrial sectors, and primary application areas. The results showed that the overall patent activity increased until 2022 before experiencing a slight decline. China dominates the landscape, accounting for approximately 62% of applications filed, largely driven by academic institutions such as Shanghai University. Leading industries include special-purpose machinery, medical and dental technology, and textiles. According to International Patent Classification codes, filament formation (D01D5/00) is prevalent, while electrospinning—specifically IPC D04H1/728—represents the most active and influential of the three technologies. These findings exhibit the technological dynamics shaping fiber-based fabrication platforms and underscore their growing relevance in pharmaceutical innovation. The identified trends position these technologies as foundational for next-generation biomaterial design, offering valuable insights for researchers, industry stakeholders, and policymakers. Full article

This study employs an industry-specific patent classification methodology (ISPCM) and conducts complex network analysis across temporal, industrial, and spatial dimensions to examine China’s new energy vehicle (NEV) patent collaboration network and to uncover the mechanisms underlying China’s global rise in the NEV sector. The results demonstrate the effectiveness of the ISPCM and reveal a three-phase growth pattern that is driven by policy initiatives and market expansion. Domestic entities dominate the patent landscape, with a noticeable shift from invention patents to utility model patents, which reflects a focus on application-oriented innovation. The collaboration network exhibits a heavy-tailed characteristic, and it forms an oligopolistic structure in which state-owned enterprises (SOEs) act as “innovation orchestrators,” while private firms concentrate on specialized R&D. Across the industrial chain, the component segment forms the largest network, the complete vehicle segment comprises the smallest network, and the aftermarket is clustered around battery recycling. A clear divide between domestic and foreign entities suggests potential decoupling risks. The findings reveal a dual-circulation innovation model that combines state-led coordinated research with market-driven independent research, offering valuable insights for sustainable industrial transformation. Full article

The integration of digital technologies with the physical economy has emerged as a crucial driver of sustainable and high-quality development. Drawing on a patent co-classification framework, this study constructs a provincial-level indicator of digital–real integration in China to evaluate its influence on carbon productivity and the underlying mechanisms. The empirical findings show that digital–real integration exerts a clear and statistically significant positive impact on carbon productivity. Moreover, the improvement in carbon productivity occurs mainly through three channels: green technological innovation, adjustments in industrial structure toward upgrading, and enhancements in resource allocation efficiency. Industrial upgrading is reflected in the gradual shift toward more advanced and low-carbon industrial configurations, whereas the allocation channel captures the coordinated optimization of traditional and emerging production factors. Regarding the nonlinearity, a threshold pattern is identified between digital–real integration and carbon productivity, shaped by the degree of biased technological progress. When the technological bias remains low, the productivity gains are modest; once the bias surpasses a certain critical level, the positive effect of integration intensifies substantially. The magnitude of this threshold effect also varies by bias type, with capital-biased technological progress producing the strongest influence. Overall, the results provide theoretical and policy implications for advancing digital–real integration and supporting a green and low-carbon transition. Full article

Effective patent recommendation plays a crucial role in bridging the gap between enterprise technological demands and patent supply. However, semantic mismatches and incomplete demand expressions often hinder accurate supply–demand matching. This research proposes a demand-driven patent recommendation method. First, content analysis and topic clustering were used to construct an enterprise demand element system, dividing the demand content into five elements: materials, methods, efficacy, products, and applications. Based on the completeness of these elements, enterprise demands were further classified into explicit and implicit types. Second, an enterprise technical problem space and a patent solution space were established, identifying ten types of enterprise technical problems and fifteen types of patent solution categories. These were connected through supply–demand elements to build corresponding correlation systems for explicit and implicit demands. Finally, according to different types of supply–demand correlations and demand characteristics, differentiated patent recommendation methods were designed. Taking various demands in the lithium battery industry as empirical cases, the results show that the proposed method based on demand classification and supply–demand element association effectively achieves accurate patent matching and addresses the challenges caused by incomplete demand information. The study provides an intelligent, content-based recommendation pathway for enterprise technology acquisition and patent transformation, offering theoretical and practical significance for enhancing patent commercialization and improving the efficiency of technological achievement transformation. Full article

Recently, the state of the art of aerogels (AGs) has been reviewed, reporting first on their classification, based on the chemical origin of their precursors and the different methods existing to prepare them. Additionally, AGs of inorganic origin (IAGs) were contemplated, deeply discussing the properties, specific synthesis, and possible uses of silica and metal oxide-based AGs, since they are the most experimented and patented AGs already commercialized in several sectors. In this second part review, IAGs are examined again, but chalcogenide and metals AGs (CAGs and MAGs) are debated, since they are still too little studied, patented, and marketed, despite their nonpareil properties and vast range of possible applications. First, to give readers unaware of the previous work on AGs, a background about IAGs, all their main subclasses have been reported and their synthesis, including sol–gel, epoxide addition (EA), and dispersed inorganic (DIS) methods, as well as procedures involving the use of pre-synthesized nanoparticles as building blocks, have been discussed. Morphology and microstructure images of materials prepared by such synthetic method have been supplied. Conversely, the methods needed to prepare CAGs and MAGs, topics of this study, have been debated separately in the related sections, with illustrative SEM images. Their possible uses, properties, and some comparisons of their performance with that of other AGs and not AG materials traditionally tested for the same scopes, have also been disserted, reporting several case studies in reader-friendly tables. Full article

Blood glucose monitoring is essential for the treatment of diabetes, a chronic disease that affects millions of people worldwide. Non-electrochemical blood glucose sensors often lack sensitivity and selectivity, especially in complex biological fluids, and are not suitable for wearable point-of-care devices. Electrochemical blood glucose sensors, on the other hand, are easy to handle, inexpensive, and offer high sensitivity and selectivity even in the presence of interfering molecules. They can also be seamlessly integrated into wearable devices. This review explores the key blood glucose technologies, emphasizing the operating principle and classification of electrochemical glucose sensors. It also highlights the role of functional solid–liquid interfaces in optimizing sensor performance. Recent developments in solid–liquid interfacial materials, including metal-based, metal oxide-based, carbon-based, nanoparticle-based, conductive polymer, and graphene-based interfaces, are systematically analyzed for their sensing potential. Furthermore, this review highlights existing patents, the evolving market landscape, and data from clinical studies that bridge the gap between laboratory research and commercial application. Finally, we present future perspectives and highlight the need for next-generation wearable and enzyme-free glucose sensors for continuous and non-invasive glucose monitoring. Full article

Increasing macroeconomic uncertainty necessitates that firms optimize their R&D investment and commercialization strategies. Patents, as crucial outcomes of R&D with legal protection, impose significant costs due to progressively increasing maintenance fees. Predicting patent life accurately thus becomes critical for effective patent management. Previous studies have often and primarily employed classification models for patent life prediction, while limiting practical utility due to coarse granularity. This study proposes a robust ensemble regression model combining multiple machine learning techniques, such as Random Forest and deep neural networks, to directly predict patent life. The proposed model achieved superior performance, surpassing individual baseline models, and recorded a Mean Absolute Error (MAE) of approximately 852.81. Additional validation with active patents further demonstrated the model’s practical feasibility, showing its potential to support sustainable intellectual property management by accurately predicting longer life for high-quality patents currently maintained. Consequently, the proposed model provides ongoing firms and brand-new startups with a decision support tool for strategic patent maintenance and commercialization decisions. By promoting efficient allocation of R&D resources and reducing unnecessary maintenance of low-value patents, the approach fosters sustainable management of innovation assets, enhancing predictive accuracy and long-term applicability. Full article

Several reviews have been published addressing the challenges of waste collection and recycling across various sectors, including municipal, industrial, construction, and agricultural domains. These studies often emphasize the role of existing technologies in addressing recycling-related issues. Among the diverse range of waste materials, glass remains a significant component, frequently grouped with other multi-class waste types (such as plastic, cardboard, and metal) for segregation and classification processes. The primary aim of this review is to examine the technologies specifically involved in the collection and separation stages of waste in which glass represents a major or exclusive fraction. The second objective is to present the main technologies and computer vision sensors currently used in managing glass waste. This study not only references laboratory developments or experiments on standard datasets, but also includes projects, patents, and real-world implementations that are already delivering measurable results. The review discusses the technological possibilities, gaps, and challenges faced in this specialized field of research. Full article

Objective: False lumen (FL) thrombosis plays a key role in aortic remodeling after Frozen Elephant Trunk (FET) surgery, yet current imaging assessments are limited to categorical classifications. This study aimed to evaluate an unsupervised artificial intelligence (AI) algorithm based on a variational autoencoder (VAE) for automated, continuous quantification of FL thrombosis using serial computed tomography angiography (CTA). Methods: In this retrospective study, a VAE model was applied to axial CTA slices from 30 patients with aortic dissection who underwent FET surgery. The model encoded each image into a structured latent space, from which a continuous “thrombus score” was developed and derived to quantify the extent of FL thrombosis. Thrombus scores were compared between postoperative and follow-up scans to assess individual remodeling trajectories. Results: The VAE successfully encoded anatomical features of the false lumen into a structured latent space, enabling unsupervised classification of thrombus states. A continuous thrombus score was derived from this space, allowing slice-by-slice quantification of thrombus burden across the aorta. The algorithm demonstrated robust reconstruction accuracy and consistent separation of fully patent, partially thrombosed, and completely thrombosed lumen states without the need for manual annotation. Across the cohort, 50% of patients demonstrated an increase in thrombus score over time, 40% a decrease, and 10% remained unchanged. Despite these individual differences, no statistically significant change in overall thrombus burden was observed at the group level (p = 0.82), emphasizing the importance of individualized longitudinal assessment. Conclusions: The VAE-based method enables reproducible, annotation-free quantification of FL thrombosis and captures patient-specific remodeling patterns. This approach may enhance post-FET surveillance and supports the integration of AI-driven tools into personalized aortic imaging workflows. Full article

Aerogels (AGs) are highly porous, low-density, disordered, ultralight macroscopic materials with immense surface areas. Traditionally synthesized using aqueous sol–gel chemistry, starting by molecular precursors, the nanoparticles (NPs) dispersions gelation method is nowadays the most used procedure to obtain AGs with improved crystallinity and broader structural, morphological and compositional complexity. The Sol–gel process consists of preparing a solution by hydrolysis of different precursors, followed by gelation, ageing and a drying phase, via supercritical, freeze-drying or ambient evaporation. AGs can be classified based on various factors, such as appearance, synthetic methods, chemical origin, drying methods, microstructure, etc. Due to their nonpareil characteristics, AGs are completely different from common NPs, thus covering different and more extensive applications. AGs can be applied in supercapacitors, acoustic devices, drug delivery, thermal insulation, catalysis, electrocatalysis, gas absorption, gas separation, organic and inorganic xenobiotics removal from water and air and radionucleotides management. This review provides first an analysis on AGs according to data found in CAS Content Collection. Then, an AGs’ classification based on the chemical origin of their precursors, as well as the different methods existing to prepare AGs and the current optimization strategies are discussed. Following, focusing on AGs of inorganic origin, silica and metal oxide-based AGs are reviewed, deeply discussing their properties, specific synthesis and possible uses. These classes were chosen based on the evidence that they are the most experimented, patented and marketed AGs. Several related case studies are reported, some of which have been presented in reader-friendly tables and discussed. Full article