Inventions

25 pages, 2154 KB

Open AccessArticle

A Multimodal Polygraph Framework with Optimized Machine Learning for Robust Deception Detection

by Omar Shalash, Ahmed Métwalli, Mohammed Sallam and Esraa Khatab

Inventions 2025, 10(6), 96; https://doi.org/10.3390/inventions10060096 (registering DOI) - 29 Oct 2025

Deception detection is considered a concern for all individuals in their everyday lives, as it greatly affects human interactions. While multiple automatic lie detection systems exist, their accuracy still needs to be improved. Additionally, the lack of adequate and realistic datasets hinders the [...] Read more.

Deception detection is considered a concern for all individuals in their everyday lives, as it greatly affects human interactions. While multiple automatic lie detection systems exist, their accuracy still needs to be improved. Additionally, the lack of adequate and realistic datasets hinders the development of reliable systems. This paper presents a new multimodal dataset with physiological data (heart rate, galvanic skin response, and body temperature), in addition to demographic data (age, weight, and height). The presented dataset was collected from 49 unique subjects. Moreover, this paper presents a polygraph-based lie detection system utilizing multimodal sensor fusion. Different machine learning algorithms are used and evaluated. Random Forest has achieved an accuracy of 97%, outperforming Logistic Regression (58%), Support Vector Machine (58% with perfect recall of 1.00), and k-Nearest Neighbor (83%). The model shows excellent precision and recall (0.97 each), making it effective for applications such as criminal investigations. With a computation time of 0.06 s, Random Forest has proven to be efficient for real-time use. Additionally, a robust k-fold cross-validation procedure was conducted, combined with Grid Search and Particle Swarm Optimization (PSO) for hyperparameter tuning, which substantially reduced the gap between training and validation accuracies from several percentage points to under 1%, underscoring the model’s enhanced generalization and reliability in real-world scenarios. Full article

(This article belongs to the Topic Next-Generation IoT and Smart Systems for Communication and Sensing)

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29 pages, 2947 KB

Open AccessReview

A Comparative Review of Vertical Axis Wind Turbine Designs: Savonius Rotor vs. Darrieus Rotor

by Alina Fazylova, Kuanysh Alipbayev, Alisher Aden, Fariza Oraz, Teodor Iliev and Ivaylo Stoyanov

Inventions 2025, 10(6), 95; https://doi.org/10.3390/inventions10060095 (registering DOI) - 27 Oct 2025

Abstract

This paper reviews and analyzes three types of vertical-axis wind rotors: the classic Savonius, spiral Savonius, and Darrieus designs. Using numerical modeling methods, including computational fluid dynamics (CFD), their aerodynamic characteristics, power output, and efficiency under different operating conditions are examined. Key parameters [...] Read more.

This paper reviews and analyzes three types of vertical-axis wind rotors: the classic Savonius, spiral Savonius, and Darrieus designs. Using numerical modeling methods, including computational fluid dynamics (CFD), their aerodynamic characteristics, power output, and efficiency under different operating conditions are examined. Key parameters such as lift, drag, torque, and power coefficient are compared to identify the strengths and weaknesses of each rotor. Results highlight that the Darrieus rotor demonstrates the highest efficiency at higher wind speeds due to lift-based operation, while the spiral Savonius offers improved stability, smoother torque characteristics, and adaptability in turbulent or low-wind environments. The classic Savonius, though less efficient, remains simple, cost-effective, and suitable for small-scale urban applications where reliability is prioritized over high performance. In addition, the study outlines the importance of blade geometry, tip speed ratio, and advanced materials in enhancing rotor durability and efficiency. The integration of modern optimization approaches, such as CFD-based design improvements and machine learning techniques, is emphasized as a promising pathway for developing more reliable and sustainable vertical-axis wind turbines. Although the primary analysis relies on numerical simulations, the observed performance trends are consistent with findings reported in experimental studies, indicating that the results are practically meaningful for design screening, technology selection, and siting decisions. Unlike prior studies that analyze Savonius and Darrieus rotors in isolation or under heterogeneous setups, this work (i) establishes a harmonized, fully specified CFD configuration (common domain, BCs, turbulence/near-wall treatment, time-stepping) enabling like-for-like comparison; (ii) couples the transient aerodynamic loads p(θ,t) into a dynamic FEA + fatigue pipeline (rainflow + Miner with mean-stress correction), going beyond static loading proxies; (iii) quantifies a prototype-stage materials choice rationale (aluminum) with a validated migration path to orthotropic composites; and (iv) reports reproducible wake/torque metrics that are cross-checked against mature models (DMST/actuator-cylinder), providing design-ready envelopes for small/medium VAWTs. Overall, the work provides recommendations for selecting rotor types under different wind conditions and operational scenarios to maximize energy conversion performance and long-term reliability. Full article

(This article belongs to the Section Inventions and Innovation in Energy and Thermal/Fluidic Science)

15 pages, 4162 KB

Open AccessArticle

Development of a Heating Block as an Aid for the DNA-Based Biosensing of Plant Pathogens

by Bertrand Michael L. Diola, Adrian A. Borja, Paolo Rommel P. Sanchez, Marynold V. Purificacion and Ralph Kristoffer B. Gallegos

Inventions 2025, 10(6), 94; https://doi.org/10.3390/inventions10060094 (registering DOI) - 26 Oct 2025

Abstract

Deoxyribonucleic acid (DNA)-based biosensors are rapid, cost-effective, and portable devices for monitoring crop pathogens. However, their on-field operations rely on a laboratory-bound heating block, which controls temperature during sample preparation. This study aimed to develop a field-deployable heating block to assist in the [...] Read more.

Deoxyribonucleic acid (DNA)-based biosensors are rapid, cost-effective, and portable devices for monitoring crop pathogens. However, their on-field operations rely on a laboratory-bound heating block, which controls temperature during sample preparation. This study aimed to develop a field-deployable heating block to assist in the DNA hybridization protocol of DNA-based biosensors. It should maintain

95 ° C

,

55 ° C

, and

20 ° C

for 5, 10, and 5 min, respectively. It had aluminum bars, positive thermal coefficient ceramic heaters, a Peltier thermoelectric module, and DS18B20 thermistors, serving twelve 0.2 mL polymerase chain reaction (PCR) tubes. An Arduino microcontroller employing a proportional–integral–derivative (PID) algorithm with a solid-state relay was utilized. Machine performance for distilled water-filled PCR tubes showed a maximum

10 ° C

thermal variation. The machine maintained

(96.00 \pm 0.97) ° C

,

(55.15 \pm 2.17) ° C

, and

(17.75 \pm 0.71) ° C

with root mean square errors (RMSEs) of

1.40 ° C

,

2.18 ° C

, and

2.36 ° C

, respectively. The average thermal rates were

(0.16 \pm 0.11) ° C / s

,

(0.29 \pm 0.11) ° C / s

, and

(0.14 \pm 0.07) ° C / s

from ambient to

95 ° C

,

95 ° C

to

55 ° C

, and

55 ° C

to

20 ° C

, respectively. Overall, the low standard deviations and RMSEs demonstrate thermostable results and robust temperature control. Full article

(This article belongs to the Special Issue Inventions and Innovation in Smart Sensing Technologies for Agriculture)

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33 pages, 4268 KB

Open AccessArticle

AI-Driven Digital Twin for Optimizing Solar Submersible Pumping Systems

by Yousef Salah, Omar Shalash, Esraa Khatab, Mostafa Hamad and Sherif Imam

Inventions 2025, 10(6), 93; https://doi.org/10.3390/inventions10060093 (registering DOI) - 25 Oct 2025

Abstract

Reliable water access in remote and desert-like regions remains a challenge, particularly in areas with limited infrastructure. Solar-powered submersible pumps offer a promising solution; however, optimizing their performance under variable environmental conditions remains a challenging task. This research presents an Artificial Intelligence (AI)-driven [...] Read more.

Reliable water access in remote and desert-like regions remains a challenge, particularly in areas with limited infrastructure. Solar-powered submersible pumps offer a promising solution; however, optimizing their performance under variable environmental conditions remains a challenging task. This research presents an Artificial Intelligence (AI)-driven digital twin framework for modeling and optimizing the performance of a solar-powered submersible pump system. The proposed system has three core components: (1) an AI model for predicting the inverter motor’s output frequency based on the current generated by the solar panels, (2) a predictive model for estimating the pump’s generated power based on the inverter motor’s output, and (3) a mathematical formulation for determining the volume of water lifted based on the system’s operational parameters. Moreover, a dataset comprising 6 months of environmental and system performance data was collected and utilized to train and evaluate multiple predictive models. Unlike previous works, this research integrates real-world data with a multi-phase AI modeling pipeline for real-time water output estimation. Performance assessments indicate that the Random Forest (RF) model outperformed alternative approaches, achieving the lowest error rates with a Mean Absolute Error (MAE) of 1.00 Hz for output frequency prediction and 1.39 kW for pump output power prediction. The framework successfully estimated annual water delivery of 166,132.77 m³, with peak monthly output of 18,276.96 m³ in July and minimum of 9784.20 m³ in January demonstrating practical applicability for agricultural water management planning in arid regions. Full article

(This article belongs to the Special Issue Advanced Technologies and Artificial Intelligence for Sustainable and Intelligent Transportation Systems: Second Edition)

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24 pages, 26148 KB

Open AccessArticle

An Open-Source 3D Bioprinter Using Direct Light Processing for Tissue Engineering Applications

by Daniel Sanchez-Garcia, Anuar Giménez-El-Amrani, Armando Gonzalez-Muñoz and Andres Sanz-Garcia

Inventions 2025, 10(5), 92; https://doi.org/10.3390/inventions10050092 - 17 Oct 2025

Abstract

The demand for organ transplantation continues to rise worldwide, intensifying the gap between supply and demand and driving research in tissue engineering (TE). Bioprinting, particularly light-based vat photopolymerization (VP) methods such as digital light processing (DLP), has emerged as a promising strategy to [...] Read more.

The demand for organ transplantation continues to rise worldwide, intensifying the gap between supply and demand and driving research in tissue engineering (TE). Bioprinting, particularly light-based vat photopolymerization (VP) methods such as digital light processing (DLP), has emerged as a promising strategy to fabricate complex, cell-compatible tissue constructs with high precision. In this study, we developed an open-source, bottom-up DLP bioprinter designed to provide a cost-effective and modular alternative to commercial systems. The device was built from commercially available components and custom-fabricated parts, with tolerance allocation and deviation analyses applied to ensure structural reliability. Mechanical and optical subsystems were modeled and validated, and the control architecture was implemented on the Arduino platform with a custom Python-based graphical interface. The system achieved a theoretical Z-axis resolution of 1

μ

m and a vertical travel range of 50 mm, with accuracy and repeatability comparable to research-grade bioprinters. Initial printing trials using polyethylene glycol diacrylate (PEGDA) hydrogels demonstrated high-fidelity microfluidic constructs with adequate dimensional precision. Collectively, these results validate the functionality of the proposed system and highlight its potential as a flexible, precise, and cost-effective platform that is also easy to customize to advance the democratization of biofabrication in TE. Full article

(This article belongs to the Section Inventions and Innovation in Advanced Manufacturing)

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17 pages, 1344 KB

Open AccessArticle

SolarFaultAttentionNet: Dual-Attention Framework for Enhanced Photovoltaic Fault Classification

by Mubarak Alanazi and Yassir A. Alamri

Inventions 2025, 10(5), 91; https://doi.org/10.3390/inventions10050091 - 9 Oct 2025

Abstract

Photovoltaic (PV) fault detection faces significant challenges in distinguishing subtle defects from complex backgrounds while maintaining reliability across diverse environmental conditions. Traditional approaches struggle with scalability and accuracy limitations, particularly when detecting electrical damage, physical defects, and environmental soiling in thermal imagery. This [...] Read more.

Photovoltaic (PV) fault detection faces significant challenges in distinguishing subtle defects from complex backgrounds while maintaining reliability across diverse environmental conditions. Traditional approaches struggle with scalability and accuracy limitations, particularly when detecting electrical damage, physical defects, and environmental soiling in thermal imagery. This paper presents SolarFaultAttentionNet, a novel dual-attention deep learning framework that integrates channel-wise and spatial attention mechanisms within a multi-path CNN architecture for enhanced PV fault classification. The approach combines comprehensive data augmentation strategies with targeted attention modules to improve feature discrimination across six fault categories: Electrical-Damage, Physical-Damage, Snow-Covered, Dusty, Bird-Drop, and Clean. Experimental validation on a dataset of 885 images demonstrates that SolarFaultAttentionNet achieves 99.14% classification accuracy, outperforming state-of-the-art models by 5.14%. The framework exhibits perfect detection for dust accumulation (100% across all metrics) and robust electrical damage detection (99.12% F1 score) while maintaining an optimal sensitivity (98.24%) and specificity (99.91%) balance. The computational efficiency (0.0160 s inference time) and systematic performance improvements establish SolarFaultAttentionNet as a practical solution for automated PV monitoring systems, enabling reliable fault detection critical for maximizing energy production and minimizing maintenance costs in large-scale solar installations. Full article

(This article belongs to the Section Inventions and Innovation in Electrical Engineering/Energy/Communications)

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24 pages, 3652 KB

Open AccessArticle

A Modern Ultrasonic Cleaning Tank Developed for the Jewelry Manufacturing Process and Its Cleaning Efficiency

by Chatchapat Chaiaiad, Pawantree Borthai and Jatuporn Thongsri

Inventions 2025, 10(5), 90; https://doi.org/10.3390/inventions10050090 - 7 Oct 2025

Abstract

This research details the development and evaluation of a Modern Ultrasonic Cleaning Tank (MUCT) designed to enhance cleaning efficiency in jewelry manufacturing, particularly for silver jewelry, replacing the traditional method, which was less efficient and had higher operating costs. The MUCT offers capabilities [...] Read more.

This research details the development and evaluation of a Modern Ultrasonic Cleaning Tank (MUCT) designed to enhance cleaning efficiency in jewelry manufacturing, particularly for silver jewelry, replacing the traditional method, which was less efficient and had higher operating costs. The MUCT offers capabilities of single- or dual-frequency ultrasonic operation (28 kHz and 40 kHz) and adjustable transducer positioning. An advanced method involving computer simulations, utilizing harmonic response analysis and transient dynamic analysis, was employed to determine the acoustic pressure inside the MUCT, thereby indicating the cavitation intensity required to achieve high cleaning efficiency. Simulation results confirm that this design can distribute acoustic pressure throughout the MUCT, as intended. A prototype MUCT was assembled, and its operation was validated through foil corrosion tests, ultrasonic power concentration (UPC) measurements, and jewelry cleaning tests. The results revealed that the MUCT’s center provided the maximum UPC of 28 W/L and an acoustic pressure of 30.43 MPa, effectively operating at single and dual frequencies, and achieving superior dirt removal. The highest cleaning efficiency of 100% was achieved using dual frequency with a 97% water and 3% dishwashing liquid mixture at 60 °C, exceeding the 23.52% obtained with water at 27 °C without ultrasonic treatment. The MUCT, successfully integrated into the manufacturing process, offers customizable features to meet various cleaning needs, providing flexibility, improved performance, and cost savings. Full article

(This article belongs to the Section Inventions and Innovation in Advanced Manufacturing)

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17 pages, 4289 KB

Open AccessPatent Summary

Manual Resin Gear Drive for Fine Adjustment of Schlieren Optical Elements

by Emilia Georgiana Prisăcariu and Iulian Vlăducă

Inventions 2025, 10(5), 89; https://doi.org/10.3390/inventions10050089 - 2 Oct 2025

Abstract

High-precision angular positioning mechanisms are essential across diverse scientific and industrial applications, from optical instrumentation to automated mechanical systems. Conventional bronze–steel gear reduction units, while reliable, are often heavy, costly, and unsuitable for chemically aggressive or vacuum environments, limiting their use in advanced [...] Read more.

High-precision angular positioning mechanisms are essential across diverse scientific and industrial applications, from optical instrumentation to automated mechanical systems. Conventional bronze–steel gear reduction units, while reliable, are often heavy, costly, and unsuitable for chemically aggressive or vacuum environments, limiting their use in advanced research setups. This work introduces a novel 1:360 gear reduction system manufactured by resin-based additive manufacturing, designed to overcome these limitations. The compact worm–gear assembly translates a single crank rotation into a precise one-degree indicator displacement, enabling fine and repeatable angular control. A primary application is the alignment of parabolic mirrors in schlieren systems, where accurate tilt adjustment is critical to correct optical alignment; however, the design is broadly adaptable to other precision positioning tasks in laboratory and industrial contexts. Compared with conventional assemblies, the resin-based reducer offers reduced weight, chemical and vacuum compatibility, and lower production cost. Its three-stage reduction design further enhances load-bearing capacity, achieving approximately double the theoretical torque transfer of equivalent commercial systems. These features establish the device as a robust, scalable, and automation-ready solution for high-accuracy angular adjustment, contributing both to specialized optical research and general-purpose precision engineering. Full article

(This article belongs to the Section Inventions and Innovation in Advanced Manufacturing)

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19 pages, 5546 KB

Open AccessArticle

Enhanced Frequency Regulation of Islanded Airport Microgrid Using IAE-Assisted Control with Reaction Curve-Based FOPDT Modeling

by Tarun Varshney, Naresh Patnana and Vinay Pratap Singh

Inventions 2025, 10(5), 88; https://doi.org/10.3390/inventions10050088 - 2 Oct 2025

Abstract

This paper investigates frequency regulation of an airport microgrid (AIM) through the application of an integral absolute error (IAE)-assisted control approach. The islanded AIM is initially captured using a linearized transfer function model to accurately reflect its dynamic characteristics. This model is then [...] Read more.

This paper investigates frequency regulation of an airport microgrid (AIM) through the application of an integral absolute error (IAE)-assisted control approach. The islanded AIM is initially captured using a linearized transfer function model to accurately reflect its dynamic characteristics. This model is then simplified using a first-order plus dead time (FOPDT) approximation derived via a reaction-curve-based method, which balances between model simplicity and accuracy. Two different proportional–integral–derivative (PID) controllers are designed to meet distinct objectives: one focuses on set-point tracking (SPT) to maintain the target frequency levels, while the other addresses load disturbance rejection (LDR) to reduce the effects of load fluctuations. A thorough comparison of these controllers demonstrates that the SPT-mode PID controller outperforms the LDR-mode controller by providing an improved transient response and notably lower error measures. The results underscore the effectiveness of combining IAE-based control with reaction curve modeling to tune PID controllers for islanded AIM systems, contributing to enhanced and reliable frequency regulation for microgrid operations. Full article

(This article belongs to the Section Inventions and Innovation in Electrical Engineering/Energy/Communications)

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19 pages, 2190 KB

Open AccessArticle

TRIZ-Based Conceptual Enhancement of a Multifunctional Rollator Walker Design Integrating Wheelchair, Pilates Chair, and Stepladder

by Elwin Nesan Selvanesan, Poh Kiat Ng, Kia Wai Liew, Jian Ai Yeow, Chai Hua Tay, Peng Lean Chong and Yu Jin Ng

Inventions 2025, 10(5), 87; https://doi.org/10.3390/inventions10050087 - 28 Sep 2025

Abstract

The development of a multifunctional invention requires several refinements for optimizing each function. This study presents a Theory of Inventive Problem Solving (TRIZ)-based conceptual framework for enhancing an innovative multifunctional assistive technology device that integrates the functionalities of a rollator walker, wheelchair, Pilates [...] Read more.

The development of a multifunctional invention requires several refinements for optimizing each function. This study presents a Theory of Inventive Problem Solving (TRIZ)-based conceptual framework for enhancing an innovative multifunctional assistive technology device that integrates the functionalities of a rollator walker, wheelchair, Pilates chair, and stepladder. The limitations of the multifunctional rollator walker were identified from the user feedback of a foundational work and were then addressed by identifying the engineering and physical contradictions and problem modeling using Su-field analysis. Through TRIZ Inventive Principles, the proposed design eliminates common trade-offs between portability, stability, and usability. The conceptual enhancement incorporates features such as deployable steps, the utilization of high strength–to–weight ratio material, foldability, a passive mechanical brake-locking system, retractable armrests, the incorporation of spring-assist hinges, and the use of large tires with vibration-dampening hubs. This study contributes a novel, user-focused, and space-saving mobility solution that aligns with the evolving demands of assistive technology, laying the groundwork for future iterations involving smart control, power assist, and modular enhancements. Full article

(This article belongs to the Section Inventions and Innovation in Design, Modeling and Computing Methods)

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15 pages, 2896 KB

Open AccessArticle

Platinum Atom-Functionalized Carbon Nanotubes as Efficient Sensors for CO and CO₂: A Theoretical Investigation

by Natalia P. Boroznina, Sergey V. Boroznin, Irina V. Zaporotskova, Pavel A. Zaporotskov, Dmitry F. Sergeev, Govindhasamy Murugadoss, Nachimuthu Venkatesh and Shaik Gouse Peera

Inventions 2025, 10(5), 86; https://doi.org/10.3390/inventions10050086 - 26 Sep 2025

Abstract

This study presents a theoretical investigation of platinum-modified single-wall carbon nanotubes (SWCNTs) of types (6.0) and (6.6) for their potential application as gas sensor materials. Quantum chemical calculations using density functional theory (DFT) were performed to evaluate the interaction mechanisms with carbon monoxide [...] Read more.

This study presents a theoretical investigation of platinum-modified single-wall carbon nanotubes (SWCNTs) of types (6.0) and (6.6) for their potential application as gas sensor materials. Quantum chemical calculations using density functional theory (DFT) were performed to evaluate the interaction mechanisms with carbon monoxide (CO) and carbon dioxide (CO₂) molecules. The results revealed that pristine SWCNTs exhibit weak and unstable interactions with CO and CO₂, indicating limited sensing capabilities. However, the modification with platinum atoms significantly enhanced their adsorption properties. The most energetically favorable configuration was found when the platinum atom was located at the center of a C–C bond on the SWCNT surface, ensuring the stability of the metal-functionalized system. The Pt-modified SWCNTs exhibited stable sorption interactions with CO and CO₂, characterized by weak van der Waals forces, enabling the reusability of the sensor without contamination. Additionally, the adsorption of these gas molecules induced changes in the band gap of the nanocomposite system, indicating a variation in conductivity upon gas exposure. The distinct band gap changes for the CO and CO₂ adsorption suggest the selectivity of the sensor towards each gas. Overall, the results demonstrate that platinum modification effectively enhances the sensing performance of SWCNTs, paving the way for the development of highly sensitive and selective nanosensors for CO and CO₂ detection based on changes in electronic properties upon gas adsorption. Full article

(This article belongs to the Special Issue Innovative Approaches for Fabricating Membrane Electrode Assemblies for Fuel Cells and Water Electrolysis Applicaions)

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30 pages, 10853 KB

Open AccessArticle

Addressing Development Challenges of the Emerging REEFS Wave Energy Converter

by José P. P. G. Lopes de Almeida and Vinícius G. Machado

Inventions 2025, 10(5), 85; https://doi.org/10.3390/inventions10050085 - 26 Sep 2025

Abstract

This article addresses the multifaceted challenges inherent in the development of the novel REEFS (Renewable Electric Energy From Sea) wave energy converter (WEC). Building on the submerged pressure differential principle, it frames similar WECs before focusing on REEFS that combines renewable energy generation [...] Read more.

This article addresses the multifaceted challenges inherent in the development of the novel REEFS (Renewable Electric Energy From Sea) wave energy converter (WEC). Building on the submerged pressure differential principle, it frames similar WECs before focusing on REEFS that combines renewable energy generation with coastal protection, functioning as an artificial reef. The review follows chronological criteria, encompassing experimental proof-of-concept, small-scale laboratory modeling, simplified and advanced computational fluid dynamics (CFD) simulations, and the design of a forthcoming real-sea model deployment. Key milestones include the validation of a passive variable porosity system, demonstration of wave-to-wire energy conversion, and quantification of wave attenuation for coastal defense. Additionally, the study introduces a second patent-protected REEFS configuration, isolating internal components from seawater via an elastic enveloping membrane. Challenges related to scaling, numerical modeling, and funding are thoroughly examined. The results highlight the importance of the proof-of-concept as the keystone of the development process, underscore the relevance of mixed laboratory-computational approaches and emphasize the need for a balanced equilibrium between intellectual property safeguard and scientific publishing. The REEFS development trajectory offers interesting insights for researchers and developers navigating the complex innovation seas of emerging wave energy technologies. Full article

(This article belongs to the Section Inventions and Innovation in Energy and Thermal/Fluidic Science)

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14 pages, 3250 KB

Open AccessArticle

An IoT-Enabled System for Monitoring and Predicting Physicochemical Parameters in Rosé Wine Storage Process

by Xu Zhang, Jihong Yang, Ruijie Zhao, Ziquan Qin and Zhuojun Xie

Inventions 2025, 10(5), 84; https://doi.org/10.3390/inventions10050084 - 24 Sep 2025

Abstract

The evolution of the winemaking industry towards intelligent and digitalized systems is crucial for precision winemaking and ensuring product safety. In this context, the Internet of Things (IoT) provides a key strategy for real-time monitoring and data management throughout the winemaking process. However, [...] Read more.

The evolution of the winemaking industry towards intelligent and digitalized systems is crucial for precision winemaking and ensuring product safety. In this context, the Internet of Things (IoT) provides a key strategy for real-time monitoring and data management throughout the winemaking process. However, comprehensive multi-parameter IoT-based monitoring and time-series prediction of physicochemical parameters during storage are currently lacking, limiting the ability to assess storage conditions and provide early warning of quality deterioration. To address these gaps, a multi-parameter IoT monitoring system was designed and developed to track conductivity, dissolved oxygen, and temperature in real time. Data were transmitted via a 4th-generation (4G) mobile communication module to the TLINK cloud platform for storage and visualization. An 80-day storage experiment confirmed the system’s reliability for long-term monitoring, and analysis of parameter trends demonstrated its effectiveness in assessing storage conditions and wine quality evolution. Furthermore, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Temporal Convolutional Network (TCN) models, and Autoregressive Integrated Moving Average (ARIMA) were implemented to predict physicochemical parameter trends. The TCN model achieved the highest predictive performance, with coefficients of determination (R²) of 0.955, 0.968, and 0.971 for conductivity, dissolved oxygen, and temperature, respectively, while LSTM and GRU showed comparable results. These results demonstrate that integrating IoT-based multi-parameter monitoring with deep learning time-series prediction enables real-time detection of abnormal storage and quality deterioration, providing a novel and practical framework for early warning throughout the wine storage process. Full article

(This article belongs to the Special Issue Inventions and Innovation in Smart Sensing Technologies for Agriculture)

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19 pages, 5120 KB

Open AccessArticle

Paving Integrated Photovoltaic Technology: Numerical Investigation of Fatigue Performance and Design Strategy

by Peichen Cai, Yutong Chai, Susan Tighe, Meng Wang and Shunde Yin

Inventions 2025, 10(5), 83; https://doi.org/10.3390/inventions10050083 - 24 Sep 2025

Abstract

To elucidate the fatigue damage evolution of solar road panels under long-term loading and enhance their structural durability, this study develops a particle-based discrete element model and simulates fatigue responses under different structural configurations and loading rates. A strength degradation index was established [...] Read more.

To elucidate the fatigue damage evolution of solar road panels under long-term loading and enhance their structural durability, this study develops a particle-based discrete element model and simulates fatigue responses under different structural configurations and loading rates. A strength degradation index was established by introducing peak stress and terminal stress, enabling quantitative evaluation of strength deterioration. Combined with fracture evolution, the dominant mesoscopic damage mechanisms were revealed. The results indicate that structural configuration strongly influences fatigue performance, with square panels showing the best resistance due to geometric symmetry and stable boundary constraints. Loading rate regulates damage evolution: lower rates promote structural coordination but may delay cumulative failure, while higher rates suppress overall deformation yet increase localized fracture risk. Based on these findings, a nonlinear predictive model of the strength degradation rate was constructed (R² = 0.935), offering reliable support for structural life prediction and design optimization. Finally, fatigue-resistant design strategies are proposed, including optimal structural configuration, controlled loading rates, bonding enhancement, and integration of online monitoring—providing both theoretical and technical guidance for high-performance, long-lifespan solar road systems. Full article

(This article belongs to the Section Inventions and Innovation in Electrical Engineering/Energy/Communications)

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20 pages, 3018 KB

Open AccessArticle

Biological Properties of a Composite Polymer Material Based on Polyurea and Submicron-Sized Selenium Particles

by Sergey A. Shumeyko, Dmitriy E. Burmistrov, Denis V. Yanykin, Ilya V. Baimler, Alexandr V. Simakin, Maxim E. Astashev, Mikhail V. Dubinin, Roman Y. Pishchalnikov, Ruslan M. Sarimov, Valeriy A. Kozlov, Alexey S. Dorokhov and Andrey Yu. Izmailov

Inventions 2025, 10(5), 82; https://doi.org/10.3390/inventions10050082 - 19 Sep 2025

Abstract

Using the method of laser ablation in liquid, submicron-sized particles of zero-valent amorphous selenium (Se SMPs) were created. A number of composite polymer materials were manufactured based on polyurea and Se SMPs at concentrations ranging 0.1–2.5 wt.%. The manufactured materials showed no significant [...] Read more.

Using the method of laser ablation in liquid, submicron-sized particles of zero-valent amorphous selenium (Se SMPs) were created. A number of composite polymer materials were manufactured based on polyurea and Se SMPs at concentrations ranging 0.1–2.5 wt.%. The manufactured materials showed no significant surface or internal defects at either the macro or micro level. It was found that the Se SMPs were not uniformly distributed inside the polymer, but formed ordered areas with slightly higher and lower concentrations of the particles. It was demonstrated that the manufactured materials did not generate a significant amount of active oxygen species, which could damage biological objects such as protein molecules and DNA, while also exhibiting pronounced bacteriostatic properties without significantly affecting the growth and reproduction of mammalian cells. Materials containing 0.25 and 1% Se SMPs, when added to soil, improved the morphometric parameters of radish plants (Raphanus sativus var. sativus). These polymer composite materials based on polyurea with the addition of Se SMPs are promising functional materials for agriculture due to their antibacterial activity. Full article

(This article belongs to the Section Inventions and Innovation in Biotechnology and Materials)

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15 pages, 2814 KB

Open AccessArticle

Functionalized Graphene Quantum Dots for Thin-Film Illuminator and Cell Dyeing Applications

by Ruey-Shin Juang, Yi-Ru Li, Chun-Chieh Fu and Chien-Te Hsieh

Inventions 2025, 10(5), 81; https://doi.org/10.3390/inventions10050081 - 3 Sep 2025

Abstract

Graphene quantum dots (GQDs) have emerged as promising nanomaterials due to their unique optical properties, high biocompatibility, and tunable surface functionalities. In this work, GQDs were synthesized via a one-pot hydrothermal method and further functionalized using polyethylene glycol (PEG) of various molecular weights [...] Read more.

Graphene quantum dots (GQDs) have emerged as promising nanomaterials due to their unique optical properties, high biocompatibility, and tunable surface functionalities. In this work, GQDs were synthesized via a one-pot hydrothermal method and further functionalized using polyethylene glycol (PEG) of various molecular weights and sodium hydroxide to tailor their photoluminescence (PL) behavior and enhance their applicability in thin-film illumination and biological staining. PEG-modified GQDs exhibited a pronounced red-shift and intensified fluorescence response due to aggregation-induced emission, with GQD-PEG (molecular weight: 300,000) achieving up to eight-fold enhancement in PL intensity compared to pristine GQDs. The influence of solvent environments on PL behavior was studied, revealing solvent-dependent shifts and emission intensities. Transmission electron microscopy confirmed the formation of core–shell GQD clusters, while Raman spectroscopy suggested improved structural ordering upon modification. The prepared GQD thin films demonstrated robust fluorescence stability under prolonged water immersion, indicating strong adhesion to glass substrates. Furthermore, the modified GQDs effectively labeled E. coli, Gram-positive, and Gram-negative bacteria, with GQD-PEG and GQD-NaOH displaying red and green emissions, respectively, at optimal concentrations. This study highlights the potential of surface-functionalized GQDs as versatile materials for optoelectronic devices and fluorescence-based bioimaging. Full article

(This article belongs to the Section Inventions and Innovation in Surface Science and Nanotechnology)

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15 pages, 2164 KB

Open AccessArticle

Coordinated Optimization of Multiple Reactive Power Sources for Transient Overvoltage Suppression for New Energy Sending-Out System

by Qinglei Zhang, Lei Luo, Xiaoping Wang, Dehai Zhang, Haibo Li, Zongxiang Lu and Ying Qiao

Inventions 2025, 10(5), 80; https://doi.org/10.3390/inventions10050080 - 1 Sep 2025

Abstract

With the implementation of China’s “dual carbon” strategy, the installed capacity of new energy has grown rapidly. Wind power and photovoltaic power have accounted for more than 40%, but the integration of power electronic apparatus into the grid has resulted in the manifestation [...] Read more.

With the implementation of China’s “dual carbon” strategy, the installed capacity of new energy has grown rapidly. Wind power and photovoltaic power have accounted for more than 40%, but the integration of power electronic apparatus into the grid has resulted in the manifestation of a system with “low inertia and weak damping”, which can easily lead to transient overvoltage problems at transmitters when high-voltage direct-current (HVDC) latching faults occur. Although a variety of dynamic reactive power optimization strategies have been proposed in the existing research, most of them are aimed at single equipment, and multi-reactive power source collaborative control schemes are lacking. In this paper, we innovatively establish a transient voltage analysis model for a new energy transmitter, derive the expression of overvoltage amplitude, and propose a method for the construction of a multi-reactive source collaborative optimization model, which can effectively suppress transient overvoltage through capacity and initial output configuration. We provide a new idea for the safe operation of a significant percentage of new energy grids. The case analysis shows that the co-optimization method outlined in this paper is an effective solution to suppress the transient overvoltage triggered by AC faults and has wide application value. Full article

(This article belongs to the Section Inventions and Innovation in Electrical Engineering/Energy/Communications)

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25 pages, 4045 KB

Open AccessArticle

Optimum Sizing of Solar Photovoltaic Panels at Optimum Tilt and Azimuth Angles Using Grey Wolf Optimization Algorithm for Distribution Systems

by Preetham Goli, Srinivasa Rao Gampa, Amarendra Alluri, Balaji Gutta, Kiran Jasthi and Debapriya Das

Inventions 2025, 10(5), 79; https://doi.org/10.3390/inventions10050079 - 30 Aug 2025

Abstract

This paper presents a novel methodology for the optimal sizing of solar photovoltaic (PV) systems in distribution networks by determining the monthly optimum tilt and azimuth angles to maximize solar energy capture. Using one year of solar irradiation data, the Grey Wolf Optimizer [...] Read more.

This paper presents a novel methodology for the optimal sizing of solar photovoltaic (PV) systems in distribution networks by determining the monthly optimum tilt and azimuth angles to maximize solar energy capture. Using one year of solar irradiation data, the Grey Wolf Optimizer (GWO) is employed to optimize the tilt and azimuth angles with the objective of maximizing monthly solar insolation. Unlike existing approaches that assume fixed azimuth angles, the proposed method calculates both tilt and azimuth angles for each month, allowing for a more precise alignment with solar trajectories. The optimized orientation parameters are subsequently utilized to determine the optimal number and placement of PV panels, as well as the optimal location and sizing of shunt capacitor (SC) banks, for the IEEE 69-bus distribution system. This optimization is performed under peak load conditions using the GWO, with the objectives of minimizing active power losses, enhancing voltage profile stability, and maximizing PV system penetration. The long-term impact of this approach is assessed through a 20-year energy and economic savings analysis, demonstrating substantial improvements in energy efficiency and cost-effectiveness. Full article

(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 2nd Edition)

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26 pages, 1692 KB

Open AccessReview

Comparative Assessment and Deployment of Zeolites, MOFs, and Activated Carbons for CO₂ Capture and Geological Sequestration Applications

by Mohamadou Hamadama Mouctar, Mohamed G Hassan, Nuno Bimbo, Syed Zaheer Abbas and Ihab Shigidi

Inventions 2025, 10(5), 78; https://doi.org/10.3390/inventions10050078 - 28 Aug 2025

Cited by 3

Abstract

The rising level of atmospheric carbon dioxide (CO₂) is a major driver of climate change, highlighting the need to develop carbon capture and storage (CCS) technologies quickly. This paper offers a comparative review of three main groups of porous adsorbent materials—zeolites, [...] Read more.

The rising level of atmospheric carbon dioxide (CO₂) is a major driver of climate change, highlighting the need to develop carbon capture and storage (CCS) technologies quickly. This paper offers a comparative review of three main groups of porous adsorbent materials—zeolites, metal–organic frameworks (MOFs), and activated carbons—for their roles in CO₂ capture and long-term storage. By examining their structural features, adsorption capacities, moisture stability, and economic viability, the strengths and weaknesses of each material are assessed. Additionally, five different methods for delivering these materials into depleted oil and gas reservoirs are discussed: direct suspension injection, polymer-assisted transport, foam-assisted delivery, encapsulation with controlled release, and preformed particle gels. The potential of hybrid systems, such as MOF–carbon composites and polymer-functionalized materials, is also examined for improved selectivity and durability in underground environments. This research aims to connect materials science with subsurface engineering, helping guide the selection and use of adsorbent materials in real-world CCS applications. The findings support the optimization of CCS deployment and contribute to broader climate change efforts and the goal of achieving net-zero emissions. Key findings include CO₂ adsorption capacities of 3.5–8.0 mmol/g and surface areas up to 7000 m²/g, with MOFs demonstrating the highest uptake and activated carbons offering cost-effective performance. Full article

(This article belongs to the Section Inventions and Innovation in Biotechnology and Materials)

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