Next Energy最新文献_第9页

Optimized model predictive control with gray-box modeling for PV-based DC/DC converters 基于pv的DC/DC变换器灰盒建模优化模型预测控制

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-23 DOI: 10.1016/j.nxener.2025.100468

Kerim Karabacak

This study presents an advanced model predictive control (MPC) framework integrated with a gray-box modeling approach for voltage stabilization in photovoltaic (PV) power systems utilizing a DC/DC boost converter. As a continuation of our previous research, where a gray-box model was developed to accurately represent the boost converter dynamics, this work extends the model's application by designing and implementing a predictive controller. The gray-box model, which combines theoretical equations with empirical system identification, serves as the foundation for the proposed MPC, ensuring precise control action under varying environmental and load conditions. Simulation results indicate that the MPC significantly outperforms conventional proportional-integral-derivative controllers, reducing output voltage ripple to near zero and achieving a settling time of 0.0002 s. Experimental validation confirms the controller’s robustness, maintaining stable voltage regulation under dynamic conditions with minimal transient effects. The findings demonstrate the effectiveness of gray-box-based MPC in enhancing the reliability and efficiency of PV power systems, paving the way for future advancements in intelligent control strategies for renewable energy applications.

本研究提出了一种先进的模型预测控制（MPC）框架，结合灰盒建模方法，用于利用DC/DC升压转换器实现光伏（PV）电力系统的电压稳定。作为我们之前研究的延续，我们开发了一个灰盒模型来准确地表示升压变换器的动力学，这项工作通过设计和实现一个预测控制器来扩展模型的应用。灰盒模型将理论方程与经验系统辨识相结合，作为所提出的MPC的基础，确保了在不同环境和负载条件下的精确控制动作。仿真结果表明，MPC显著优于传统的比例-积分-导数控制器，将输出电压纹波降低到接近零，并实现了0.0002 s的稳定时间。实验验证了控制器的鲁棒性，在动态条件下以最小的瞬态效应保持稳定的电压调节。研究结果证明了灰盒MPC在提高光伏发电系统的可靠性和效率方面的有效性，为可再生能源应用的智能控制策略的未来发展铺平了道路。

{"title":"Optimized model predictive control with gray-box modeling for PV-based DC/DC converters","authors":"Kerim Karabacak","doi":"10.1016/j.nxener.2025.100468","DOIUrl":"10.1016/j.nxener.2025.100468","url":null,"abstract":"<div><div>This study presents an advanced model predictive control (MPC) framework integrated with a gray-box modeling approach for voltage stabilization in photovoltaic (PV) power systems utilizing a DC/DC boost converter. As a continuation of our previous research, where a gray-box model was developed to accurately represent the boost converter dynamics, this work extends the model's application by designing and implementing a predictive controller. The gray-box model, which combines theoretical equations with empirical system identification, serves as the foundation for the proposed MPC, ensuring precise control action under varying environmental and load conditions. Simulation results indicate that the MPC significantly outperforms conventional proportional-integral-derivative controllers, reducing output voltage ripple to near zero and achieving a settling time of 0.0002 s. Experimental validation confirms the controller’s robustness, maintaining stable voltage regulation under dynamic conditions with minimal transient effects. The findings demonstrate the effectiveness of gray-box-based MPC in enhancing the reliability and efficiency of PV power systems, paving the way for future advancements in intelligent control strategies for renewable energy applications.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100468"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145361397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MXene-nanoflower composites as high-performance electrode materials toward solid-state lithium-ion batteries 纳米花复合材料作为固态锂离子电池的高性能电极材料

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-09-16 DOI: 10.1016/j.nxener.2025.100421

Savan K. Raj , Khushbu Sharma , Vartika Sharma , Takayuki Ichikawa , Ankur Jain , Vaibhav Kulshrestha

The design and synthesis of a silicon-integrated MXene-based nanoflower (Si@NFs) architecture using a simple hydrothermal method and thermal treatment are reported in this study. The resulting hierarchical structure creates a multidimensional conductive network by fusing the superior conductivity and mechanical stability of MXenes with the high capacity of nanosilicon. Due to effective ion transport, interfacial contact, and volume expansion buffering, Si@NFs exhibit better cycling stability, as demonstrated by structural and electrochemical characterisation. The strong interface and structural integrity of the nanoflowers indicate high promise for future integration into all-solid-state lithium-ion battery systems, even though solid-state electrolytes are not directly incorporated in this study.

本研究采用简单的水热法和热处理方法设计和合成了硅集成mxene纳米花（Si@NFs）结构。通过将MXenes优异的导电性和机械稳定性与纳米硅的高容量融合，由此产生的分层结构创建了一个多维导电网络。由于有效的离子传输，界面接触和体积膨胀缓冲，Si@NFs表现出更好的循环稳定性，如结构和电化学表征所示。纳米花的强界面和结构完整性表明，未来集成到全固态锂离子电池系统中有很大的希望，即使固态电解质没有直接纳入本研究。

引用次数: 0

Machine learning-optimized solar thermal pretreatment and low-energy ultrasonic disintegration for enhanced biogas production: Efficiency, carbon footprint, and comparative analysis 机器学习优化的太阳能热预处理和低能量超声波分解用于增强沼气生产：效率，碳足迹和比较分析

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-09-27 DOI: 10.1016/j.nxener.2025.100435

Hassan A. Hameed Al-Hamzawi , Ali S. Abed Al Sailawi , Ali Alhraishawi , Rasha Abed Hussein , Maad M. Mijwil

This experimental and modeling study explores the integration of renewable energy-based pretreatment methods (solar thermal and ultrasonic) with anaerobic digestion (AD) for sustainable sludge management and enhanced biogas production. Building on prior experimental work that utilized microwave pretreatment, the study employs machine learning (ML) to model and optimize AD performance under renewable energy pretreatment. Experimental validation was conducted using lab-scale continuously stirred tank reactors (CSTRs) with a comprehensive dataset of experimental runs. Key findings demonstrate that solar thermal and ultrasonic methods achieve 20.5% ± 1.8% and 18.7% ± 2.1% higher methane production (295 ± 22 and 285 ± 20 mL CH₄/g VS, respectively) and 30.9% ± 2.1% greater chemical oxygen demand (COD) solubilization compared to microwave pretreatment (245 ± 18 mL CH₄/g VS), while reducing energy consumption by 40.1% ± 3.2% and 35.6% ± 2.8%, respectively. ML models (Random Forest and Gradient Boosting) demonstrated high accuracy (R² = 0.952 ± 0.018 and 0.948 ± 0.022, respectively) in predicting biogas yield and identifying optimal pretreatment parameters. Comprehensive life cycle assessment including upstream emissions shows 49% and 37% carbon footprint reduction for solar thermal and ultrasonic systems, respectively, compared to microwave pretreatment. This work provides both experimental validation and theoretical framework for future large-scale implementation and highlights the potential of ML-driven optimization to advance sustainable sludge-to-energy conversion, offering significant implications for reducing operational costs.

这项实验和建模研究探索了基于可再生能源的预处理方法（太阳能热和超声波）与厌氧消化（AD）的整合，以实现可持续的污泥管理和提高沼气产量。在先前使用微波预处理的实验工作的基础上，该研究使用机器学习（ML）来建模和优化可再生能源预处理下的AD性能。利用实验室规模的连续搅拌槽式反应器（CSTRs）进行了实验验证，并进行了全面的实验运行数据集。主要研究结果表明，与微波预处理（245±18 mL CH₄/g VS）相比，光热和超声处理的甲烷产量（295±22 mL CH₄/g VS）分别提高20.5%±1.8%和18.7%±2.1%，化学需氧量（COD）增溶率提高30.9%±2.1%，能耗分别降低40.1%±3.2%和35.6%±2.8%。ML模型（随机森林和梯度增强）在预测沼气产量和确定最佳预处理参数方面具有较高的准确性（R²分别= 0.952±0.018和0.948±0.022）。包括上游排放在内的综合生命周期评估显示，与微波预处理相比，太阳能热和超声波系统的碳足迹分别减少了49%和37%。这项工作为未来的大规模实施提供了实验验证和理论框架，并强调了机器学习驱动的优化在推进可持续污泥转化为能源方面的潜力，为降低运营成本提供了重要意义。

{"title":"Machine learning-optimized solar thermal pretreatment and low-energy ultrasonic disintegration for enhanced biogas production: Efficiency, carbon footprint, and comparative analysis","authors":"Hassan A. Hameed Al-Hamzawi , Ali S. Abed Al Sailawi , Ali Alhraishawi , Rasha Abed Hussein , Maad M. Mijwil","doi":"10.1016/j.nxener.2025.100435","DOIUrl":"10.1016/j.nxener.2025.100435","url":null,"abstract":"<div><div>This experimental and modeling study explores the integration of renewable energy-based pretreatment methods (solar thermal and ultrasonic) with anaerobic digestion (AD) for sustainable sludge management and enhanced biogas production. Building on prior experimental work that utilized microwave pretreatment, the study employs machine learning (ML) to model and optimize AD performance under renewable energy pretreatment. Experimental validation was conducted using lab-scale continuously stirred tank reactors (CSTRs) with a comprehensive dataset of experimental runs. Key findings demonstrate that solar thermal and ultrasonic methods achieve 20.5% ± 1.8% and 18.7% ± 2.1% higher methane production (295 ± 22 and 285 ± 20 mL CH₄/g VS, respectively) and 30.9% ± 2.1% greater chemical oxygen demand (COD) solubilization compared to microwave pretreatment (245 ± 18 mL CH₄/g VS), while reducing energy consumption by 40.1% ± 3.2% and 35.6% ± 2.8%, respectively. ML models (Random Forest and Gradient Boosting) demonstrated high accuracy (<em>R</em>² = 0.952 ± 0.018 and 0.948 ± 0.022, respectively) in predicting biogas yield and identifying optimal pretreatment parameters. Comprehensive life cycle assessment including upstream emissions shows 49% and 37% carbon footprint reduction for solar thermal and ultrasonic systems, respectively, compared to microwave pretreatment. This work provides both experimental validation and theoretical framework for future large-scale implementation and highlights the potential of ML-driven optimization to advance sustainable sludge-to-energy conversion, offering significant implications for reducing operational costs.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100435"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal parameter design for power electronic converters using a probabilistic learning-based stochastic surrogate model 基于概率学习的随机代理模型的电力电子变流器参数优化设计

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-28 DOI: 10.1016/j.nxener.2025.100464

Akash Mahajan , Shivam Chaturvedi , Srijita Das , Wencong Su , Van-Hai Bui

The selection of optimal design for power electronic converter parameters involves balancing efficiency and thermal constraints to ensure high performance without compromising safety. This study proposes a novel probabilistic-learning-based stochastic surrogate modeling framework, which simultaneously enables uncertainty-aware predictions and feasibility-guided optimization, a combination not commonly explored in prior converter design studies. The approach begins with a neural network classifier that evaluates the feasibility of parameter configurations, effectively filtering out unsafe and/or impractical inputs. Subsequently, a probabilistic prediction model estimates the converter’s efficiency and temperature while quantifying prediction uncertainty, providing both performance insights and reliability metrics. Finally, a heuristic optimization-based model is employed to optimize a multiobjective function that maximizes efficiency while adhering to thermal constraints. The optimization process incorporates penalty terms to discourage solutions that violate practical thresholds, ensuring actionable and realistic recommendations. An advanced heuristic optimization method is used to find the optimal solution and is compared with several well-known search algorithms, including genetic algorithm, particle swarm optimization, simulated annealing, tabu search, and stochastic hill climbing. The results demonstrate significant improvements in predictive accuracy and optimization outcomes, offering a robust solution for advancing power electronics design. The proposed framework is generalizable and can benefit the broader scientific community by serving as a scalable tool for fast, reliable design space exploration across diverse converter architectures and operating scenarios.

电力电子变换器参数优化设计的选择涉及平衡效率和热约束，以确保在不影响安全性的前提下实现高性能。本研究提出了一种新的基于概率学习的随机代理建模框架，该框架同时实现了不确定性感知预测和可行性指导优化，这是先前转换器设计研究中通常未探索的组合。该方法首先使用神经网络分类器来评估参数配置的可行性，有效地过滤掉不安全和/或不切实际的输入。随后，一个概率预测模型估计转换器的效率和温度，同时量化预测的不确定性，提供性能洞察和可靠性指标。最后，采用启发式优化模型对多目标函数进行优化，使其在遵守热约束的情况下实现效率最大化。优化过程包含惩罚条款，以阻止违反实际阈值的解决方案，确保可操作和现实的建议。采用一种先进的启发式优化方法寻找最优解，并与遗传算法、粒子群优化算法、模拟退火算法、禁忌搜索算法和随机爬坡算法进行了比较。结果表明，预测精度和优化结果显着提高，为推进电力电子设计提供了强大的解决方案。该框架具有通用性，可以作为一种可扩展的工具，在不同的转换器架构和操作场景中进行快速、可靠的设计空间探索，从而使更广泛的科学界受益。

{"title":"Optimal parameter design for power electronic converters using a probabilistic learning-based stochastic surrogate model","authors":"Akash Mahajan , Shivam Chaturvedi , Srijita Das , Wencong Su , Van-Hai Bui","doi":"10.1016/j.nxener.2025.100464","DOIUrl":"10.1016/j.nxener.2025.100464","url":null,"abstract":"<div><div>The selection of optimal design for power electronic converter parameters involves balancing efficiency and thermal constraints to ensure high performance without compromising safety. This study proposes a novel probabilistic-learning-based stochastic surrogate modeling framework, which simultaneously enables uncertainty-aware predictions and feasibility-guided optimization, a combination not commonly explored in prior converter design studies. The approach begins with a neural network classifier that evaluates the feasibility of parameter configurations, effectively filtering out unsafe and/or impractical inputs. Subsequently, a probabilistic prediction model estimates the converter’s efficiency and temperature while quantifying prediction uncertainty, providing both performance insights and reliability metrics. Finally, a heuristic optimization-based model is employed to optimize a multiobjective function that maximizes efficiency while adhering to thermal constraints. The optimization process incorporates penalty terms to discourage solutions that violate practical thresholds, ensuring actionable and realistic recommendations. An advanced heuristic optimization method is used to find the optimal solution and is compared with several well-known search algorithms, including genetic algorithm, particle swarm optimization, simulated annealing, tabu search, and stochastic hill climbing. The results demonstrate significant improvements in predictive accuracy and optimization outcomes, offering a robust solution for advancing power electronics design. The proposed framework is generalizable and can benefit the broader scientific community by serving as a scalable tool for fast, reliable design space exploration across diverse converter architectures and operating scenarios.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100464"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Perovskite solar cells: Efficiency and stability enhancement using covalent organic frameworks 钙钛矿太阳能电池：使用共价有机框架提高效率和稳定性

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-16 DOI: 10.1016/j.nxener.2025.100451

Reza Feizi , Fatemeh Razi Astaraei , Mohammad Sameti

Perovskite solar cells (PSCs) represent a significant advancement in photovoltaic technology, attracting considerable attention owing to their outstanding power conversion efficiency (PCE). However, their path to widespread commercialization is hindered by challenges such as low stability and the rapid degradation of the perovskite active layer. To address these issues, covalent organic frameworks (COFs) have emerged as an innovative class of materials known for their low density, high porosity, and good stability, rendering them suitable for integration into PSCs. In these solar cells, COFs enhance the crystalline quality of the perovskite layer, align energy levels, and reduce recombination losses, thereby improving both efficiency and stability. This review begins with a bibliometric analysis, examining notable keywords, pioneer countries, and publication growth. It then explores the impact of COFs integrated into key components and interfaces of PSCs, including the perovskite active layer, the hole and electron transport layers (HTL/ETL), and their critical interfaces. The focus is on improvements in structural integrity, PCE gains, and stability enhancements. Additionally, the review elucidates processes behind these beneficial effects and offers insights into how COFs can effectively address current limitations faced by PSCs.

钙钛矿太阳能电池（PSCs）由于其优异的功率转换效率（PCE）而受到广泛关注，是光伏技术的一大进步。然而，钙钛矿活性层的低稳定性和快速降解等挑战阻碍了它们广泛商业化的道路。为了解决这些问题，共价有机框架（COFs）已经成为一类创新的材料，以其低密度、高孔隙率和良好的稳定性而闻名，使其适合集成到psc中。在这些太阳能电池中，COFs提高了钙钛矿层的结晶质量，排列了能级，减少了复合损失，从而提高了效率和稳定性。本综述从文献计量分析开始，考察了著名的关键词、先驱国家和出版物增长。然后探讨了COFs集成到psc的关键组件和界面中的影响，包括钙钛矿活性层、空穴和电子传输层（html /ETL）及其关键界面。重点是改进结构完整性、PCE增益和稳定性增强。此外，该综述阐明了这些有益影响背后的过程，并提供了COFs如何有效解决PSCs当前面临的限制的见解。

{"title":"Perovskite solar cells: Efficiency and stability enhancement using covalent organic frameworks","authors":"Reza Feizi , Fatemeh Razi Astaraei , Mohammad Sameti","doi":"10.1016/j.nxener.2025.100451","DOIUrl":"10.1016/j.nxener.2025.100451","url":null,"abstract":"<div><div>Perovskite solar cells (PSCs) represent a significant advancement in photovoltaic technology, attracting considerable attention owing to their outstanding power conversion efficiency (PCE). However, their path to widespread commercialization is hindered by challenges such as low stability and the rapid degradation of the perovskite active layer. To address these issues, covalent organic frameworks (COFs) have emerged as an innovative class of materials known for their low density, high porosity, and good stability, rendering them suitable for integration into PSCs. In these solar cells, COFs enhance the crystalline quality of the perovskite layer, align energy levels, and reduce recombination losses, thereby improving both efficiency and stability. This review begins with a bibliometric analysis, examining notable keywords, pioneer countries, and publication growth. It then explores the impact of COFs integrated into key components and interfaces of PSCs, including the perovskite active layer, the hole and electron transport layers (HTL/ETL), and their critical interfaces. The focus is on improvements in structural integrity, PCE gains, and stability enhancements. Additionally, the review elucidates processes behind these beneficial effects and offers insights into how COFs can effectively address current limitations faced by PSCs.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100451"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A comprehensive review on heat exchangers in crude oil refineries: Classification, degradation mechanisms, and performance optimization strategies 原油炼油厂热交换器的分类、降解机理和性能优化策略综述

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-14 DOI: 10.1016/j.nxener.2025.100443

Krishnavel Velandi Nadar, Naser Mullayousef, Saleh Naser Meqwar

This review explores the performance, challenges, and advancements of heat exchangers in crude oil refining industries, focusing on Z-type, spiral wound, pillow plate, and printed circuit configurations. These exchangers operate under harsh thermal and chemical conditions, often leading to failures caused by polythionic acid attack, sulfur dioxide (SO₂), hydrogen sulfide (H₂S), and ammonium chloride fouling. Common corrosion mechanisms such as stress corrosion cracking, oxygen-induced degradation, and localized pitting significantly impact exchanger longevity and efficiency. To address these issues, the review highlights enhancement techniques, including the use of copper oxide nanofluids, pinch analysis for process integration, and thermodynamic principles for optimized design. By consolidating insights into failure mechanisms and efficiency improvements, this review acts as a valuable source for refining industry professionals aiming to bring up the resilience and performance of HE in energy-intensive environments.

本文探讨了原油炼制工业中热交换器的性能、挑战和进展，重点介绍了z型、螺旋缠绕、枕板和印刷电路配置。这些交换器在恶劣的热和化学条件下运行，经常导致由聚硫酸侵蚀、二氧化硫（SO₂）、硫化氢（H₂S）和氯化铵污垢引起的故障。常见的腐蚀机制，如应力腐蚀开裂、氧诱导降解和局部点蚀，严重影响换热器的寿命和效率。为了解决这些问题，本文重点介绍了增强技术，包括氧化铜纳米流体的使用、工艺集成的夹点分析以及优化设计的热力学原理。通过整合对故障机制和效率改进的见解，本综述为炼油行业专业人士提供了宝贵的资源，旨在提高HE在能源密集型环境中的弹性和性能。

引用次数: 0

Review on hydrogen fuel cells as an alternative fuel 氢燃料电池作为替代燃料的研究进展

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-14 DOI: 10.1016/j.nxener.2025.100460

Heth Sethia, Abhishek Priyam

The use of hydrogen fuel cells has greatly increased in recent years. Advanced fuel cells are efficiently addressing the needs of portable power, backup power, and even modular power fuel cells. It has also been used to power cars and other vehicles. Hydrogen fuel cells are now specialized under the name portable power modules to highlight their newly discovered vehicle-mountable outboard engines. This review also targets the other issues of handling and encasing hydrogen fuel in specialized containers. All these gaps that revolve around the modern world are intertwined with one advancing vehicle engine to fix the ever-increasing global warming levels. Challenges faced by cost, storage, and infrastructure barriers are addressed, in addition to technological advancements in catalyst effectiveness, membrane technology, and hydrogen supply logistics. The report ends with a visionary outlook, outlining research avenues to drive the shift to a hydrogen economy.

近年来，氢燃料电池的使用大大增加。先进的燃料电池正在有效地解决便携式电源，备用电源，甚至模块化动力燃料电池的需求。它也被用来为汽车和其他车辆提供动力。氢燃料电池现在被专门命名为便携式电源模块，以突出其新发现的可安装在车辆上的舷外发动机。本次审查还针对其他问题的处理和包装氢燃料在专门的容器。所有这些围绕现代世界的差距都与一个先进的汽车发动机交织在一起，以解决不断增加的全球变暖水平。除了催化剂有效性、膜技术和氢供应物流方面的技术进步外，还解决了成本、存储和基础设施障碍等方面面临的挑战。该报告以一个富有远见的展望结束，概述了推动向氢经济转变的研究途径。

引用次数: 0

A hybrid triboelectric nanogenerator integrating sliding and contact modes activated by a single motion for enhanced output and sensitivity 一种混合摩擦电纳米发电机，集成滑动和接触模式，由单一运动激活，以提高输出和灵敏度

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-09-27 DOI: 10.1016/j.nxener.2025.100437

Jie-Wei Gim , Lei-Jun Siau , Pei-Song Chee , Eng-Hock Lim , Jen-Hahn Low

Triboelectric nanogenerators (TENGs) have emerged as a promising solution for converting low-frequency ambient mechanical energy into electrical energy, especially from human motion. Hybrid-mode TENGs are gaining increasing attention for their potential to enhance energy harvesting efficiency by combining multiple triboelectric mechanisms within a single device. In this work, a hybrid sliding-contact mode TENG (HSC-TENG) is proposed, integrating both lateral sliding and vertical contact-separation modes, triggered by a single vertical motion. Polylactic acid (PLA) is selected as the positive friction layer, while Ecoflex 0050 is used as the negative layer. These materials enable the fabrication of protruded trapezoidal structures that promote hybrid motion. To fully exploit this geometry, a matching prism-shaped electrode is incorporated. The parallel alignment between the electrode and contact surface enhances charge transfer during both sliding and compression phases. The proposed HSC-TENG achieves an open-circuit voltage of 1.28 V and short-circuit current of 263 nA, with the triboelectric active area of 22.27 cm², which is 200% higher than conventional single-mode contact-separation TENG. Dynamic testing was conducted to validate the TENG design, demonstrating stable performance and structural robustness over 10,000 continuous operation cycles. The device was further demonstrated in a practical application, successfully charging capacitors and serving as a self-powered button for interactive, sustainable user interfaces.

摩擦电纳米发电机（TENGs）已经成为一种很有前途的解决方案，可以将低频环境机械能转化为电能，特别是从人体运动中转化为电能。混合模式的teng由于其在单个设备中结合多个摩擦电机制来提高能量收集效率的潜力而受到越来越多的关注。在这项工作中，提出了一种混合滑动接触模式TENG (HSC-TENG)，集成了横向滑动和垂直接触分离模式，由单个垂直运动触发。正摩擦层选用聚乳酸（PLA），负摩擦层选用Ecoflex 0050。这些材料能够制造出促进混合运动的突出的梯形结构。为了充分利用这种几何形状，一个匹配的棱镜形电极被纳入。电极和接触面之间的平行排列增强了滑动和压缩阶段的电荷转移。所设计的HSC-TENG的开路电压为1.28 V，短路电流为263 nA，摩擦电有效面积为22.27 cm2，比传统的单模触点分离TENG提高了200%。进行了动态测试以验证TENG设计，在10,000个连续运行周期中展示了稳定的性能和结构鲁棒性。该装置在实际应用中得到进一步验证，成功地为电容器充电，并作为交互式、可持续用户界面的自供电按钮。

{"title":"A hybrid triboelectric nanogenerator integrating sliding and contact modes activated by a single motion for enhanced output and sensitivity","authors":"Jie-Wei Gim , Lei-Jun Siau , Pei-Song Chee , Eng-Hock Lim , Jen-Hahn Low","doi":"10.1016/j.nxener.2025.100437","DOIUrl":"10.1016/j.nxener.2025.100437","url":null,"abstract":"<div><div>Triboelectric nanogenerators (TENGs) have emerged as a promising solution for converting low-frequency ambient mechanical energy into electrical energy, especially from human motion. Hybrid-mode TENGs are gaining increasing attention for their potential to enhance energy harvesting efficiency by combining multiple triboelectric mechanisms within a single device. In this work, a hybrid sliding-contact mode TENG (HSC-TENG) is proposed, integrating both lateral sliding and vertical contact-separation modes, triggered by a single vertical motion. Polylactic acid (PLA) is selected as the positive friction layer, while Ecoflex 0050 is used as the negative layer. These materials enable the fabrication of protruded trapezoidal structures that promote hybrid motion. To fully exploit this geometry, a matching prism-shaped electrode is incorporated. The parallel alignment between the electrode and contact surface enhances charge transfer during both sliding and compression phases. The proposed HSC-TENG achieves an open-circuit voltage of 1.28 V and short-circuit current of 263 nA, with the triboelectric active area of 22.27 cm<sup>2</sup>, which is 200% higher than conventional single-mode contact-separation TENG. Dynamic testing was conducted to validate the TENG design, demonstrating stable performance and structural robustness over 10,000 continuous operation cycles. The device was further demonstrated in a practical application, successfully charging capacitors and serving as a self-powered button for interactive, sustainable user interfaces.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100437"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of binder on the electrochemical, mechanical, and thermal properties of hard carbon anodes in Na-ion batteries 粘结剂对钠离子电池硬碳阳极电化学、力学和热性能的影响

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-07-26 DOI: 10.1016/j.nxener.2025.100373

Grigorii P. Lakienko , Zoya V. Bobyleva , Ekaterina Yu. Korneeva , Aleksandr V. Babkin , Oleg A. Drozhzhin , Lada V. Yashina , Evgeny V. Antipov

A polymer binder is one of the critical components of metal-ion battery electrodes, and the choice of the appropriate polymer should be based on a comprehensive analysis of several key factors. In this study, for the first time, we compared the thermal, electrochemical, and mechanical stability of hard carbon (HC) electrodes depending on the binder used: polyvinylidene fluoride (PVDF), polyacrylonitrile (PAN), sodium carboxymethylcellulose (CMC), styrene-butadiene rubber (SBR), or sodium alginate (Alg). Thermal stability studies using differential scanning calorimetry (DSC) demonstrated that during thermal decomposition, all electrodes in the charged state release more heat than charged HC powder. The corresponding increase in enthalpy depends on the thermal stability of the polymer itself. Among the binders tested, the CMC/SBR combination seems to be the most promising for practical applications in electrodes, as it provides good cyclability, strong adhesion, and a relatively low thermal effect.

聚合物粘结剂是金属离子电池电极的重要组成部分之一，选择合适的聚合物应综合分析几个关键因素。在这项研究中，我们首次比较了硬碳（HC）电极的热、电化学和机械稳定性，这取决于所使用的粘合剂：聚偏氟乙烯（PVDF）、聚丙烯腈（PAN）、羧甲基纤维素钠（CMC）、丁苯橡胶（SBR）或海藻酸钠（Alg）。差示扫描量热法（DSC）热稳定性研究表明，在热分解过程中，所有带电状态的电极都比带电的HC粉末释放更多的热量。焓的相应增加取决于聚合物本身的热稳定性。在测试的粘合剂中，CMC/SBR组合似乎最有希望在电极的实际应用中，因为它具有良好的可循环性，强附着力和相对较低的热效应。

{"title":"Effect of binder on the electrochemical, mechanical, and thermal properties of hard carbon anodes in Na-ion batteries","authors":"Grigorii P. Lakienko , Zoya V. Bobyleva , Ekaterina Yu. Korneeva , Aleksandr V. Babkin , Oleg A. Drozhzhin , Lada V. Yashina , Evgeny V. Antipov","doi":"10.1016/j.nxener.2025.100373","DOIUrl":"10.1016/j.nxener.2025.100373","url":null,"abstract":"<div><div>A polymer binder is one of the critical components of metal-ion battery electrodes, and the choice of the appropriate polymer should be based on a comprehensive analysis of several key factors. In this study, for the first time, we compared the thermal, electrochemical, and mechanical stability of hard carbon (HC) electrodes depending on the binder used: polyvinylidene fluoride (PVDF), polyacrylonitrile (PAN), sodium carboxymethylcellulose (CMC), styrene-butadiene rubber (SBR), or sodium alginate (Alg). Thermal stability studies using differential scanning calorimetry (DSC) demonstrated that during thermal decomposition, all electrodes in the charged state release more heat than charged HC powder. The corresponding increase in enthalpy depends on the thermal stability of the polymer itself. Among the binders tested, the CMC/SBR combination seems to be the most promising for practical applications in electrodes, as it provides good cyclability, strong adhesion, and a relatively low thermal effect.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100373"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Upcycling plastic waste into advanced carbon materials: A comprehensive review of applications in energy and environment 塑料废物升级为先进碳材料：在能源和环境中的应用综述

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-09-18 DOI: 10.1016/j.nxener.2025.100429

Mehmet Melikoglu

This review highlights upcycling, a promising strategy transforming diverse plastic streams into high-value carbon-based materials. The escalating global accumulation of plastic waste, currently at over 400 million tonnes annually, demands a fundamental shift from a linear take-make-dispose model to a circular economy. The manuscript synthesizes advancements (2020–2025) in converting major plastic types: Polypropylene (PP), Polyethylene Terephthalate (PET), Polystyrene (PS), and Polyethylene (PE) into functional carbons like Graphene (GNs), Carbon Nanotubes (CNTs), Activated Carbons (ACs), Carbon Nanosheets (CNS), and Disordered Hard Carbon (HC). These materials show remarkable potential. In energy storage, they enhance supercapacitors and batteries. For catalysis, they serve as efficient electrocatalysts for the Hydrogen Evolution Reaction (HER), Oxygen Evolution Reaction (OER), and Oxygen Reduction Reaction (ORR), and aid in photocatalytic and Fenton-like degradation. They are also effective in environmental remediation via adsorption and electrochemical treatment and contribute to advanced material synthesis. Their integration into emerging technologies, including Perovskite Solar Cells (PSCs) and Triboelectric Nanogenerators (TENGs), expands their utility. Initial Life Cycle Assessment (LCA) studies confirm their environmental benefits, demonstrating reductions in climate change potential and human toxicity. Future research should prioritize precision material design, multi-functional hybrids (e.g., carbon integrated with metal oxides), and advanced in-situ characterization to understand structure-property relationships. Developing scalable, energy-efficient processes through techno-economic analysis and modeling is crucial. Diversifying applications and ensuring holistic sustainability via Social LCA (S-LCA) and policy frameworks will accelerate the transition to a sustainable-circular economy.

这篇综述强调了升级回收，这是一种有前途的战略，将各种塑料流转化为高价值的碳基材料。全球塑料垃圾的积累不断升级，目前每年超过4亿吨，要求从线性获取-制造-处理模式向循环经济模式进行根本性转变。该手稿综合了将主要塑料类型：聚丙烯（PP）、聚对苯二甲酸乙二醇酯（PET）、聚苯乙烯（PS）和聚乙烯（PE）转化为石墨烯（GNs）、碳纳米管（CNTs）、活性炭（ACs）、碳纳米片（CNS）和无序硬碳（HC）等功能碳的进展（2020-2025）。这些材料显示出非凡的潜力。在能量存储方面，它们增强了超级电容器和电池的性能。在催化方面，它们是析氢反应（HER）、析氧反应（OER）和氧还原反应（ORR）的高效电催化剂，并有助于光催化和类芬顿降解。它们通过吸附和电化学处理在环境修复中也很有效，并有助于先进材料的合成。它们与新兴技术的结合，包括钙钛矿太阳能电池（PSCs）和摩擦纳米发电机（TENGs），扩大了它们的用途。初始生命周期评估（LCA）研究证实了它们的环境效益，显示了气候变化潜力和人类毒性的降低。未来的研究应优先考虑精密材料设计，多功能混合材料（例如碳与金属氧化物集成），以及先进的原位表征，以了解结构-性能关系。通过技术经济分析和建模开发可扩展的、节能的流程至关重要。通过社会LCA （S-LCA）和政策框架实现应用的多样化并确保整体可持续性，将加速向可持续循环经济的过渡。

{"title":"Upcycling plastic waste into advanced carbon materials: A comprehensive review of applications in energy and environment","authors":"Mehmet Melikoglu","doi":"10.1016/j.nxener.2025.100429","DOIUrl":"10.1016/j.nxener.2025.100429","url":null,"abstract":"<div><div>This review highlights upcycling, a promising strategy transforming diverse plastic streams into high-value carbon-based materials. The escalating global accumulation of plastic waste, currently at over 400 million tonnes annually, demands a fundamental shift from a linear take-make-dispose model to a circular economy. The manuscript synthesizes advancements (2020–2025) in converting major plastic types: Polypropylene (PP), Polyethylene Terephthalate (PET), Polystyrene (PS), and Polyethylene (PE) into functional carbons like Graphene (GNs), Carbon Nanotubes (CNTs), Activated Carbons (ACs), Carbon Nanosheets (CNS), and Disordered Hard Carbon (HC). These materials show remarkable potential. In energy storage, they enhance supercapacitors and batteries. For catalysis, they serve as efficient electrocatalysts for the Hydrogen Evolution Reaction (HER), Oxygen Evolution Reaction (OER), and Oxygen Reduction Reaction (ORR), and aid in photocatalytic and Fenton-like degradation. They are also effective in environmental remediation via adsorption and electrochemical treatment and contribute to advanced material synthesis. Their integration into emerging technologies, including Perovskite Solar Cells (PSCs) and Triboelectric Nanogenerators (TENGs), expands their utility. Initial Life Cycle Assessment (LCA) studies confirm their environmental benefits, demonstrating reductions in climate change potential and human toxicity. Future research should prioritize precision material design, multi-functional hybrids (e.g., carbon integrated with metal oxides), and advanced in-situ characterization to understand structure-property relationships. Developing scalable, energy-efficient processes through techno-economic analysis and modeling is crucial. Diversifying applications and ensuring holistic sustainability via Social LCA (S-LCA) and policy frameworks will accelerate the transition to a sustainable-circular economy.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100429"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0