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Numerical Modeling of Fractional Quantum Hall Effect States in Finite Geometries for Device Miniaturization 面向器件小型化的有限几何分数阶量子霍尔效应态数值模拟
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-15 DOI: 10.1002/adts.202501582
Lokesh Sharma, Priya Mudgal, Shobha Sharma, Deepti Sharma, Debabrata Sikdar
This study presents a detailed numerical analysis of Fractional Quantum Hall Effect (FQHE) states in three confined 2D geometries: quantum dots, nanoribbons, and Corbino disks. Using Python-based simulations, with Kwant employed for lattice modeling and spectral analysis, the research examines how confinement geometry affects energy spectra, edge state localization, and topological stability, focusing on fractional filling factors ν${bm{nu }}$ = 1/3 and 5/2. Key parameters such as energy gaps, edge state density, and state degeneracy are analyzed across varying system sizes. The results reveal that Corbino disks exhibit superior topological robustness and stable energy gaps under confinement, while nanoribbons and quantum dots are more susceptible to edge degradation and gap suppression. These findings highlight the critical role of geometry in maintaining FQHE phase stability, offering design guidelines for integrating FQHE-based functionalities into scalable quantum electronic devices.
本研究对量子点、纳米带和Corbino盘这三种受限二维几何结构中的分数量子霍尔效应(FQHE)态进行了详细的数值分析。利用基于python的模拟,利用Kwant进行晶格建模和光谱分析,研究了约束几何如何影响能谱、边缘状态局部化和拓扑稳定性,重点关注分数填充因子ν${bm{nu}}$ = 1/3和5/2。关键参数,如能量间隙,边缘状态密度和状态简并分析了不同的系统尺寸。结果表明,在约束条件下,Corbino盘具有优越的拓扑鲁棒性和稳定的能隙,而纳米带和量子点更容易受到边缘退化和能隙抑制的影响。这些发现强调了几何结构在保持FQHE相位稳定性方面的关键作用,为将基于FQHE的功能集成到可扩展的量子电子器件中提供了设计指南。
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引用次数: 0
Organic Cation Orientation Preferences in Hybrid Lead Halide Perovskites 杂化铅卤化钙钛矿的有机阳离子取向偏好
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202501645
Somayyeh Alidoust, Adem Tekin
The crucial role of organic cation orientation in shaping the optoelectronic properties of hybrid organic–inorganic perovskites (HOIPs) is revealed through a systematic investigation of a diverse set of organic cations, the orientational preferences of many of which are considered for the first time. 22 different organic cations were incorporated as A‐site cations in the cubic, orthorhombic, and tetragonal crystal phases of . To explore a broad configurational space, these cations were randomly rotated, generating over 2500 structural variations, among which approximately 400 exhibited distinct symmetry. Density functional theory (DFT) calculations on these structures revealed that variations in organic A‐cation orientation can induce formation energy and bandgap differences of up to 0.32 and 0.64 eV, respectively. Rather than aiming to reproduce exactly known experimental compounds for each perovskite, we used a unified modeling approach to systematically explore how the size and orientation of organic cations govern lattice distortion and electronic structure in perovskite frameworks. Through rotational screening, a new orthorhombic phase of the well‐known (MA = ) was identified, in which MA cations are aligned along the [102] and [10 directions. Additionally, a novel pseudocubic triclinic perovskite, (TiZ = ), was discovered and validated as a stable perovskite based on its formation energy, bandgap, effective mass, mechanical properties, and dynamic stability.
通过对多种有机阳离子的系统研究,揭示了有机阳离子取向在形成杂化有机-无机钙钛矿(HOIPs)光电性能中的关键作用,其中许多是第一次考虑取向偏好。22种不同的有机阳离子作为A位阳离子掺入到三方晶相、正交晶相和四方晶相中。为了探索广阔的构型空间,这些阳离子被随机旋转,产生了2500多种结构变化,其中大约400种表现出明显的对称性。密度泛函理论(DFT)计算表明,有机A阳离子取向的变化可导致形成能和带隙的差异分别高达0.32和0.64 eV。我们的目标不是为每种钙钛矿重现确切已知的实验化合物,而是使用统一的建模方法系统地探索有机阳离子的大小和取向如何控制钙钛矿框架中的晶格畸变和电子结构。通过旋转筛选,确定了众所周知的(MA =)的新正交相,其中MA阳离子沿[102]和[10]方向排列。此外,还发现了一种新型的伪三斜钙钛矿(TiZ =),并根据其形成能、带隙、有效质量、力学性能和动态稳定性验证了它是一种稳定的钙钛矿。
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引用次数: 0
Computational Evaluation of Tetracyano‐p‐quinodimethane TCNQ Based Derivatives as Non‐Fullerene Acceptors for Organic Solar Cells 基于TCNQ衍生物的有机太阳能电池非富勒烯受体的计算评价
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202501758
Adeel Mubarik, Faiza Shafiq, Xue‐Hai Ju
This study investigates the potential use of naturally occurring TCNQ and its derivatives as non‐fullerene acceptors (NFAs) in organic solar cells (OSCs). The density functional theory (DFT) and time‐dependent density functional theory (TD‐DFT) calculations at the B3LYP/6–311G (d,p) levels are employed to analyze the electronic structures and optical behaviors of these compounds. The optoelectronic properties of these molecules in chloroform are investigated. Electronic properties, including the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies, electronic bandgap ( E g ), quantum chemical parameter, excitation energy ( E x ), maximum wavelength ( λ max ), oscillator strength (ƒ), binding energy ( E b ), open‐circuit voltage ( V oc ) and fill factor ( FF ) of the understudy molecules are calculated. Results indicated that the modification in TCNQ reduces the E g , increasing the λ max and the values of V oc and FF , especially for TCNQ11, which has V oc 1.459 V and FF 91.20 % when combined with donor polymer (DP) P3HT. These promising results underscore the potential of our studied molecules for efficient application in organic solar cells and their significant contribution to the advancement of photovoltaic technology.
本研究探讨了天然存在的TCNQ及其衍生物在有机太阳能电池(OSCs)中作为非富勒烯受体(nfa)的潜在用途。利用B3LYP/ 6-311G (d,p)能级的密度泛函理论(DFT)和时间依赖密度泛函理论(TD - DFT)计算分析了这些化合物的电子结构和光学行为。研究了这些分子在氯仿中的光电性质。计算了分子的电子性质,包括最高已占据分子轨道(HOMO)和最低未占据分子轨道(LUMO)能、电子带隙(eg)、量子化学参数、激发能(E x)、最大波长(λ max)、振荡器强度(f)、结合能(E b)、开路电压(V oc)和填充因子(FF)。结果表明,TCNQ的修饰降低了E - g,增加了λ max和V oc和FF值,特别是TCNQ11与给体聚合物(DP) P3HT结合时,V oc为1.459 V, FF为91.20%。这些有希望的结果强调了我们研究的分子在有机太阳能电池中有效应用的潜力,以及它们对光伏技术进步的重大贡献。
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引用次数: 0
First‐Principles Exploration of Charge Transfer and Optoelectronic Properties in Anthracene‐Based Hole Transporters for Perovskite Solar Cells: Insights Supported by Device‐Level Simulations 钙钛矿太阳能电池中蒽基空穴传输体电荷转移和光电子特性的第一性原理探索:器件级模拟支持的见解
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202501774
Sidra Manzoor, Faheem Abbas, Muhammad Ishaq, Gadah Albasher, Faiza Shafiq, Mehvish Perveen, Zainab Asif, Saima Noreen
The stability, effectiveness, and versatility of perovskite solar cells (PSCs) can only be improved with advanced solar materials, opening the door for future‐oriented green energy solutions. In this study, eight recently developed anthracene‐based triphenylamine hole transporting layers, HTLs, (PEH‐S1‐PEH‐S8), derived from the PEH‐R core with thiophene and acceptor substitutions, are systematically investigated using DFT and TD‐DFT calculations at B3LYP/6‐31G** level. These HTL materials' optical, electrical, and charge‐transport characteristics are thoroughly evaluated to understand the structure‐property relationship. The PEH‐S7 molecule facilitates the efficient transfer of electronic densities from HOMO to LUMO by elucidating the maximum absorbance at 730 nm, the highest oscillator frequency (f = 1.687), the greatest light harvesting efficacy (LHE = 0.979), and the highest electron affinity (EA = 2.96 eV) in tetrahydrofuran (THF) solvent with the highest open circuit voltage (V oc = 1.38 V). This also showed higher solar efficiency (19.89%) than commercial spiro‐OMeTAD. Comparing PEH‐S1‐PEH‐S8 to the PEH‐R, it is discovered that their electron and hole mobilities are higher. These findings show that the energy levels, reorganization energies, optical and charge‐transport properties of HTL materials can be successfully tuned by strategic peripheral substitution with thiophene and electron‐acceptor groups, thereby guiding the design of future high‐performance PSCs and practical device applications.
钙钛矿太阳能电池(PSCs)的稳定性、有效性和通用性只有通过先进的太阳能材料才能得到改善,为未来面向绿色能源的解决方案打开了大门。在本研究中,利用B3LYP/6‐31G**水平的DFT和TD‐DFT计算,系统地研究了新近开发的八个基于蒽基的三苯胺空穴传输层HTLs (PEH‐S1‐PEH‐S8),这些空穴传输层是由PEH‐R核中噻吩和受体取代得到的。这些HTL材料的光学、电学和电荷输运特性被彻底评估,以了解结构-性质关系。PEH‐S7分子在四氢呋喃(THF)溶剂中具有最高的开路电压(voc = 1.38 V),在730 nm处具有最大的吸光度,最高的振荡频率(f = 1.687),最大的光收集效率(LHE = 0.979)和最高的电子亲和力(EA = 2.96 eV),从而促进了电子密度从HOMO到LUMO的有效转移。这也表明了比商业spiro‐OMeTAD更高的太阳能效率(19.89%)。比较PEH‐S1‐PEH‐S8与PEH‐R,发现它们的电子迁移率和空穴迁移率更高。这些发现表明,HTL材料的能级、重组能、光学和电荷输运性质可以通过噻吩和电子受体基团的战略性外周取代来成功调节,从而指导未来高性能psc的设计和实际器件应用。
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引用次数: 0
Suitability of Transition Metal Decorated Graphene for Carcinogenic Water Pollutants Detection: Computational Insight 过渡金属装饰石墨烯在致癌水污染物检测中的适用性:计算洞察力
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202501751
Monika Srivastava, Anurag Srivastava
Water pollution due to heavy metal contamination has been the most challenging area in recent years. The heavy metals introduced into the water through numerous anthropogenic activities such as industrial and agricultural waste, mining etc., accumulate and will lead to adverse health risks to human and aquatic life. Thus, early and efficient detection of these pollutants in water is a growing demand, for which chemiresistive sensors stand as a promising approach due to their simplicity, accuracy, high sensitivity, and real‐time detection capability. To meet the increasing demand, this work investigates the transition metal (TM = Cu, Ni, and Zn) functionalized graphene for their sensing potential toward the toxic heavy metals: Arsenic (As), Chromium (Cr), Mercury (Hg), and Lead (Pb). This work integrates density functional theory (DFT) with Non‐Equilibrium Green's Function (NEGF) to evaluate the adsorption energetics, electronic, and transport properties. The findings reveal that functionalization of graphene with TM improves the adsorption energetics of heavy metals with significant variations in electronic and transport properties. The computed sensor parameters demonstrate a high sensitivity, ranging from 80% to 254% toward the studied heavy metal, and fast recovery, particularly toward the heavy metal mercury. Thus, the observed findings confirm the suitability of TM functionalized graphene for detecting heavy metal contaminants in water, in a real‐time environment.
重金属污染引起的水污染是近年来最具挑战性的领域。通过许多人为活动,如工业和农业废物、采矿等,将重金属引入水中,积累并将对人类和水生生物造成不利的健康风险。因此,对水中这些污染物的早期和有效检测是日益增长的需求,其中化学传感器由于其简单,准确,高灵敏度和实时检测能力而成为一种有前途的方法。为了满足日益增长的需求,本工作研究了过渡金属(TM = Cu, Ni和Zn)功能化石墨烯对有毒重金属:砷(As),铬(Cr),汞(Hg)和铅(Pb)的传感潜力。本研究将密度泛函理论(DFT)与非平衡格林函数(NEGF)相结合,以评估吸附能量学、电子和输运性质。研究结果表明,石墨烯与TM的功能化改善了重金属的吸附能量,并显著改变了电子和输运性质。计算得到的传感器参数对所研究的重金属具有较高的灵敏度,灵敏度范围在80% ~ 254%之间,并且对重金属汞的回收速度快。因此,观察到的发现证实了TM功能化石墨烯在实时环境中检测水中重金属污染物的适用性。
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引用次数: 0
DrLungker: A Deep Ensemble Learning Framework for Predicting Anti‐Lung Cancer Compound Activity and Validating Multitarget Potency through WaterMap, DFT, MD Simulations, and MM‐GBSA Analysis 通过水图、DFT、MD模拟和MM - GBSA分析预测抗肺癌化合物活性和验证多靶点效力的深度集成学习框架
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202501550
Shaban Ahmad, Khalid Raza
Lung cancer, with more than 50 approved drugs, is still the deadliest cancer, with 1.80 million annual deaths, necessitating rapid drug development, which can be accelerated by AI‐driven prediction of potent candidates. In this study, we downloaded the lung cancer BioAssay data from ChEMBL and PubChem and filtered at a 5.0 µ m threshold, yielding 4,537 and 8,661 unique active compounds, respectively, and equal inactive molecules are extracted from the big inactive compound library, totalling 26,396 unique, balanced compounds are taken for descriptor computations with QikProp and AlvaDesc software. Mean imputations and standard scaling with PCA for feature sorting, followed by three Deep Learning Models—Residual Neural Network, Feed Forward Neural Network, and Recurrent Neural Network—with an 80:20 split, 50–100 epochs, Adam optimizer, 0.001 learning rate, 32 batch size, early stopping, and ensembled (majority voting, averaging, and stacking) to enhance robustness, accuracy, generalization, stability, and confidence in predicting Activity scores from 1 to 10. A user interface is built to deploy the trained models (h5) for scoring unlabeled compounds (scores 5–10 as highly active), achieving 0.99–1.0 accuracy and F1 scores. The top predicted compound library is docked (HTVS, SP, XP, MM‐GBSA) against ALK, HSP5, KRas, MMP‐8, and tRNA DHDS2, identifying the top three multitargeted hits (PubChem CIDs: 144074375, 440810382, and 48426893) with docking scores from –10.8 to –5.6 kcal/mol and MM‐GBSA energies from –67.7 to –10.4 kcal/mol. Pharmacokinetics and DFT analyses confirmed the drug‐likeness of the compound, while 5 ns WaterMap simulations revealed implicit water roles in interactions, and 100 ns MD simulations showed deviations and fluctuations within 2 Å, with numerous intermolecular interactions. The entire in‐silico study supported and validated the deep learning predictions, identifying the computational potency of compounds against lung cancer proteins—warranting experimental validation.
肺癌有50多种获批药物,仍然是最致命的癌症,每年有180万人死亡,因此需要快速开发药物,这可以通过人工智能驱动的有效候选药物预测来加速。在本研究中,我们下载了ChEMBL和PubChem的肺癌生物分析数据,并以5.0µm阈值过滤,分别得到4,537和8,661个独特的活性化合物,并从大的非活性化合物库中提取相等的非活性分子,总共26,396个独特的平衡化合物,使用QikProp和AlvaDesc软件进行描述符计算。使用PCA进行特征排序的平均输入和标准缩放,然后使用三种深度学习模型-残差神经网络,前馈神经网络和递归神经网络-使用80:20分割,50-100次epoch, Adam优化器,0.001学习率,32批大小,早期停止和集成(多数投票,平均和叠加)来增强鲁棒性,准确性,泛化,稳定性和对预测活动得分从1到10的信心。构建一个用户界面来部署训练模型(h5),用于对未标记化合物(得分5-10为高活性)进行评分,达到0.99-1.0的准确性和F1分数。预测最高的化合物库与ALK、HSP5、KRas、MMP‐8和tRNA DHDS2对接(HTVS、SP、XP、MM‐GBSA),确定了前三个多靶点(PubChem CIDs: 144074375、440810382和48426893),对接分数从-10.8到-5.6 kcal/mol, MM‐GBSA能量从-67.7到-10.4 kcal/mol。药代动力学和DFT分析证实了该化合物的药物相似性,而5 ns WaterMap模拟揭示了相互作用中隐含的水作用,100 ns MD模拟显示在2 Å内的偏差和波动,存在许多分子间相互作用。整个计算机研究支持并验证了深度学习预测,确定了化合物对抗肺癌蛋白的计算能力,需要实验验证。
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引用次数: 0
Designing High Performance Organic Donor Molecules for Photovoltaics 设计用于光伏的高性能有机供体分子
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202501560
Fabian Bauch, Chuan‐Ding Dong, Stefan Schumacher
The advancement of non‐fullerene acceptors has rocketed the power conversion efficiency (PCE) of organic photovoltaic (OPV) devices to values reaching close to 21%. However, the development of complementary donor materials has not kept pace, posing a key challenge for further improving device performance. In this theoretical study, we combine density functional theory (DFT) with Marcus theory to systematically design and evaluate donor molecules with ‐A architectures. Our focus lies in tuning electronic and optical properties – such as frontier molecular orbital energies, and singlet and triplet excitation characteristics – toward more efficient charge generation when coupled to non‐fullerene acceptor Y6. In small donor systems featuring fused thiophene ‐bridges, we find two‐dimensional delocalization of the highest occupied molecular orbital (HOMO) across the backbone and the core's side chain, which enhances the transition dipole moment. Furthermore, while fused ‐bridges lead to relatively stable transition rate constants across various interfacial configurations, they exhibit a limited CT state manifold, which may impede efficient charge separation following excitation of the acceptor. These findings provide molecular design insights critical for next‐generation high‐performance all‐molecule OPV devices.
非富勒烯受体的进步使有机光伏(OPV)器件的功率转换效率(PCE)达到接近21%的值。然而,互补供体材料的发展并没有跟上步伐,这对进一步提高器件性能构成了关键挑战。在这项理论研究中,我们将密度泛函理论(DFT)与Marcus理论相结合,系统地设计和评估具有‐A结构的供体分子。我们的重点在于调整电子和光学性质-如前沿分子轨道能量,单线态和三重态激发特性-当耦合到非富勒烯受体Y6时,更有效地产生电荷。在具有熔融噻吩桥的小供体体系中,我们发现主链和核心侧链上的最高已占据分子轨道(HOMO)的二维离域,这增强了跃迁偶极矩。此外,虽然熔融桥在不同的界面结构中导致相对稳定的跃迁速率常数,但它们表现出有限的CT状态流形,这可能阻碍受体激发后的有效电荷分离。这些发现为下一代高性能全分子OPV器件提供了至关重要的分子设计见解。
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引用次数: 0
Leveraging DFT Calculations and Machine Learning toward Materials Innovations for Proton Ceramic Fuel Cells (PCFCs): A Comprehensive Review 利用DFT计算和机器学习实现质子陶瓷燃料电池(pcfc)材料创新:综合综述
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202500855
Sangameswaran Krishnan, Zehua Pan, Zheng Zhong, Zilin Yan
Protonic ceramic fuel cells (PCFCs) represent a significant advancement in fuel cell technology due to their ability to operate at intermediate temperatures, offering enhanced efficiency and reduced material degradation compared to traditional high‐temperature oxygen ion conducting solid oxide fuel cells (O‐SOFCs). While PCFCs hold immense potential for commercialization, their material innovation remains a critical bottleneck to achieving widespread viability. This comprehensive review explores the synergistic integration of density functional theory (DFT) based calculations with machine learning (ML) methodologies, illuminating their collective impact on accelerating PCFC material development. Combination of DFT's atomic‐level precision in material property prediction with ML's sophisticated predictive algorithms, creates a powerful framework for exploring vast compositional spaces of critical materials, including perovskite oxides, double perovskite oxides, Ruddlesden‐Popper oxides, and other similar systems. The integration not only enhances computational efficiency but also enables the systematic investigation of complex structure–property relationships essential for advancing PCFC technology. The review methodically examines three interconnected themes: First, it delves into the cutting‐edge strategies and material developments that have propelled recent advances in PCFC applications; second, it analyzes DFT's pivotal role in facilitating PCFC progress through accurate atomic‐scale modeling; and third, it elucidates the revolutionary impact of ML integration with DFT methodologies and its implications for PCFC developments. By focusing on seminal contributions within each domain, this work provides a strategic perspective on the convergence of computational chemistry and ML in PCFC's future advancements.
质子陶瓷燃料电池(pcfc)代表了燃料电池技术的重大进步,因为它们能够在中等温度下工作,与传统的高温氧离子传导固体氧化物燃料电池(O - SOFCs)相比,提供了更高的效率和更少的材料降解。虽然pcfc具有巨大的商业化潜力,但其材料创新仍然是实现广泛可行性的关键瓶颈。这篇全面的综述探讨了基于密度泛函理论(DFT)的计算与机器学习(ML)方法的协同集成,阐明了它们对加速PCFC材料开发的共同影响。DFT在材料属性预测中的原子级精度与ML复杂的预测算法相结合,为探索关键材料的巨大组成空间创造了一个强大的框架,包括钙钛矿氧化物、双钙钛矿氧化物、Ruddlesden - Popper氧化物和其他类似系统。这种集成不仅提高了计算效率,而且能够系统地研究复杂的结构-性质关系,这对推进PCFC技术至关重要。该综述系统地考察了三个相互关联的主题:首先,它深入研究了推动PCFC应用最新进展的前沿战略和材料发展;其次,通过精确的原子尺度建模分析了DFT在促进PCFC进展中的关键作用;第三,它阐明了机器学习与DFT方法集成的革命性影响及其对PCFC发展的影响。通过关注每个领域的开创性贡献,本工作为计算化学和ML在PCFC未来发展中的融合提供了战略视角。
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引用次数: 0
Advancing HTL‐Free Cs 2 PtI 6 Carbon Perovskite Solar Cells: Insights from Hybrid Simulation and Machine Learning 推进无html的c2pti - 6碳钙钛矿太阳能电池:来自混合模拟和机器学习的见解
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-13 DOI: 10.1002/adts.202501860
Mahasen H. Albelbeisi, Saleh Chebaane, Sana Ben Khalifa, Norah A. M. Alsaif
The primary causes of the high cost of perovskite solar cells are metal electrodes and hole transport layers. In this theoretical work, we examine the outputs of a hole transport layer‐free carbon‐based solar cell with an FTO/ETL/Cs 2 PtI 6 /Carbon electrode structure using the Solar Cell Capacitance Simulator (SCAPS‐1D). The paper studied various carbon electrode types‐Graphene/Carbon Black (G/CB) (5 eV), Graphene (4.9 eV), Graphene Oxide (GO) (4.8 eV), and Bio‐carbon (4.5 eV)‐ and electron transport layers‐SnO 2 , TiO 2 , LBSO, and WO 3 . The studied parameters included perovskite and ETL layer thickness, doping density, and defect density. The outputs showed that the best PCE of 15.50% resulted from using G/CB electrode and TiO 2 as the ETL, with a thickness of 0.09 µm, and a doping density of 10 × 10 19 cm −3 . Additionally, for the Cs 2 PtI 6 absorber layer, a Cs 2 PtI 6 composition with a thickness of 1.2 µm, a defect density of 1× 10 15 cm −3 , and a doping density of 10 × 10 12 cm −3 demonstrated superior performance, resulting in a PCE of 15.50%. These findings suggest that the FTO/TiO 2 /Cs 2 PtI 6 /G/CB structure, particularly with optimized TiO 2 and Cs 2 PtI 6 layers, holds great potential for hole transport layer‐free‐carbon‐based solar cell fabrication. Furthermore, machine learning models with a random forest algorithm evaluated the relative importance of the features on cell efficiency, and predicted the efficiency of the suggested configuration with R 2 of 0.93 underscoring the potential of machine learning in enhancing solar cell design and performance.
钙钛矿太阳能电池成本高的主要原因是金属电极和空穴传输层。在这项理论工作中,我们使用太阳能电池电容模拟器(SCAPS‐1D)研究了具有FTO/ETL/ c2pti 6 /碳电极结构的无空穴传输层碳基太阳能电池的输出。本文研究了不同的碳电极类型——石墨烯/炭黑(G/CB) (5 eV)、石墨烯(4.9 eV)、氧化石墨烯(GO) (4.8 eV)和生物碳(4.5 eV)——以及电子传输层——SnO 2、tio2、LBSO和wo3。研究参数包括钙钛矿和ETL层厚度、掺杂密度和缺陷密度。结果表明,以G/CB电极和tio2为ETL,厚度为0.09µm,掺杂密度为10 × 10 19 cm−3,PCE为15.50%。此外,对于c2pti 6吸收层,厚度为1.2 μ m,缺陷密度为1× 10 15 cm−3,掺杂密度为10 × 10 12 cm−3的c2pti 6组合物表现出优异的性能,PCE为15.50%。这些发现表明,FTO/ tio2 / c2pti 6 /G/CB结构,特别是优化的tio2和c2pti 6层,在无空穴传输层的碳基太阳能电池制造中具有很大的潜力。此外,使用随机森林算法的机器学习模型评估了特征对电池效率的相对重要性,并预测了建议配置的效率,r2为0.93,强调了机器学习在提高太阳能电池设计和性能方面的潜力。
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引用次数: 0
Critical Behavior and Magnetocaloric Simulation in LSMO/NaF Composites Using Landau Theory 基于朗道理论的LSMO/NaF复合材料临界行为及磁热模拟
IF 3.3 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES Pub Date : 2025-12-10 DOI: 10.1002/adts.202501677
Mohamed Hsini, Nadia Zaidi, Amel Haouas
The critical behavior of (1−x) LSMO/xNaF composites with x = 0, 0.05, 0.15, and 0.20 near the second‐order paramagnetic–ferromagnetic transition is investigated through a combination of Arrott–Noakes formalism (ANF) and Kouvel–Fisher (KF) analysis. Critical exponents ( β , γ ) are determined iteratively to be (1.0004, 0.3406), (1.1593, 0.6230), (1.0467, 0.4391), and (1.0479, 0.4673) for (1‐x)LSMO/xNaF with x = 0, 0.05, 0.15, and 0.20, respectively. Furthermore, magnetocaloric entropy changes , computed via Landau theory, exhibited strong correspondence with Maxwell relation results, with minor discrepancies at high fields attributed to saturation effects. Overall, the results highlight the robustness of Landau phenomenology in describing criticality and magnetocaloric behavior, while revealing subtle doping‐induced modifications in exchange interactions.
结合arrot - noakes形式(ANF)和Kouvel-Fisher (KF)分析,研究了x = 0、0.05、0.15和0.20时(1−x) LSMO/xNaF复合材料在二阶顺磁-铁磁跃迁附近的临界行为。当x = 0、0.05、0.15和0.20时,(1‐x)LSMO/xNaF的临界指数(β, γ)分别为(1.0004,0.3406)、(1.1593,0.6230)、(1.0467,0.4391)和(1.0479,0.4673)。此外,通过朗道理论计算的磁热熵变化与麦克斯韦关系的结果具有很强的一致性,在高场中由于饱和效应而产生的差异较小。总的来说,结果突出了朗道现象学在描述临界性和磁热行为方面的鲁棒性,同时揭示了掺杂诱导的交换相互作用中的微妙修饰。
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引用次数: 0
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Advanced Theory and Simulations
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