Search Results (280)

Among the most promising alloys for photovoltaic applications is copper–indium–gallium–selenide (CIGS) because of its enhanced optical properties. This study examines the influence of current density and pulse timing on the electrodeposition of Cu(In, Ga)Se₂ (CIGS) thin films from a dilute electrolyte. It assesses how these parameters affect deposition quality, film characteristics, and device performance. CIGS absorber layers were electrodeposited using a pulsed-current method, with systematic variations in current density and pulse on/off durations in a low-concentration solution. The deposited precursors were subsequently selenized and incorporated into fully assembled CIGS solar cell architectures. Structural characteristics were analyzed by X-ray diffraction (XRD), whereas composition and elemental distribution were assessed by energy-dispersive X-ray spectroscopy (EDS). Optical properties pertinent to photovoltaic performance were evaluated through transmittance and reflectance measurements. The results indicate that moderate current densities, when combined with brief off-times, produce dense, microcrack-free films exhibiting enhanced crystallinity and near-stoichiometric Cu/(In + Ga) and Ga/(In + Ga) ratios, in contrast to films deposited at higher current densities and extended off-times. These optimized pulse parameters also produce absorber layers with advantageous optical band gaps and improved device performance. Overall, the study demonstrates that regulating pulse parameters in attenuated electrolytes is an effective strategy to optimize CIGS film quality and to facilitate the advancement of economical, solution-based fabrication methods for high-performance CIGS solar cells. Full article

The rapid commercialization of next-generation photovoltaic (PV) technologies, particularly perovskite, thin-film roll-to-roll (R2R) architectures, and tandem devices, requires robust assessment of environmental performance at the level of industrial manufacturing processes. Environmental impacts can no longer be evaluated solely at the device or module level. Although many life-cycle assessment (LCA) studies compare silicon, cadmium telluride (CdTe), copper indium gallium selenide (CIGS), and perovskite technologies, most rely on aggregated indicators and database-level inventories. Few studies systematically compile and harmonize process-level life-cycle inventories (LCIs) for the manufacturing steps that differentiate emerging industrial routes, such as solution coating, R2R processing, atomic layer deposition, low-temperature annealing, and advanced encapsulation–metallization strategies. In addition, inconsistencies in functional units, system boundaries, electricity-mix assumptions, and scale-up modeling continue to limit meaningful cross-study comparison. To address these gaps, this review (i) compiles and critically analyzes process-resolved LCIs for innovative PV manufacturing routes across laboratory, pilot, and industrial scales; (ii) quantifies sensitivity to scale-up, yield, throughput, and electricity carbon intensity; and (iii) proposes standardized methodological rules and open-access LCI templates to improve reproducibility, comparability, and integration with techno-economic and prospective LCA models. The review also synthesizes current evidence on recycling, circularity, and critical-material management. It highlights that end-of-life (EoL) benefits for emerging PV technologies are highly conditional and remain less mature than for crystalline-silicon systems. By shifting the analytical focus from technology class to manufacturing process and life-cycle configuration, this work provides a harmonized evidence base to support scalable, circular, and low-carbon industrial pathways for next-generation PV technologies. Full article

This paper presents a theoretical study of the structural, electronic, and elastic properties of gallium-doped CuInSe₂ using the GGA exchange-correlation functional with the Hubbard correction for five Ga compositions: 0, 0.25, 0.5, 0.75, and 1. The found lattice parameters decrease with gallium composition and obey Vegard’s law. Traditional DFT calculations fail to explain the band structure of Copper Indium Gallium Selenide compounds (CIGS). The use of Hubbard corrections of d-electrons of copper, indium, gallium, and p-electrons of selenium opens the gap, showing a semiconductor’s behavior of CuInGaSe2 alloys in the range 1.04 eV to 1.88 eV, which are in good agreement with available experimental data and current theory using an expensive hybrid exchange-correlation functional. The obtained formation energies for the different gallium compositions are close to −1 eV/atom, and the phonon spectra indicate the thermodynamic stability of these alloys. The values of the elastic constant satisfy the Born elastic stability conditions, suggesting that these compounds are mechanically stable. Moreover, we compute the bulk modulus (B), shear modulus (G), Young’s modulus (E), Poisson ratio (p), Pugh’s ratio (r), and average Debye speed ($v$), and the Debye temperature (${\mathsf{\Theta }}_{\mathrm{D}}$) with the Ga composition. There is a symmetry between our results and the experimental data, as well as earlier simulation results. Full article

Conventional and electronic cigarette (e-cig) users face an increased risk of cardiorespiratory diseases, driven by well-characterized pathways involving inflammation and oxidative stress (OS). Conventional cigarettes contain numerous harmful chemicals, such as nicotine and non-nicotine compounds, which produce reactive oxygen species. Although initially considered a safer alternative, the e-cig still generates toxic aldehydes that are capable of triggering oxidative responses. Heart rate variability (HRV) is an important tool for assessing autonomic function and predicting prognosis. Cardiac autonomic dysfunction, indicated by reduced HRV, has emerged as a critical cardiovascular risk factor associated with several diseases. Clinical and experimental studies show that increased OS is directly associated with heightened sympathetic activity and inversely with parasympathetic modulation. This review demonstrates that exposure to conventional cigarettes smoking and e-cigs adversely affects cardiac autonomic function, detectable by a global reduction in HRV that reflects a shift toward sympathetic dominance and a consequent increase in cardiovascular risk. These changes are associated with increased OS due to nicotine and non-nicotine compounds maintaining sympathovagal imbalance in smokers. Thus, we suggest that autonomic dysfunction, detected by HRV, correlates with oxidative responses and may be used as a modifiable risk factor in longitudinal studies involving both smoking modalities. Full article

E-cigarettes (E-cigs) are increasing in popularity and are considered a potentially safer alternative to traditional cigarettes. However, prior studies have demonstrated that inhalation of nicotine-containing e-cigs can cause substantial pathophysiologic changes, and “vaping” of some substances has led to severe lung damage. Our group recently described the role of cortactin (CTTN), a cytoskeletal actin-binding regulatory protein, in mediating cigarette smoke (CS) and E-cig-induced lung endothelial apoptosis and mitochondrial dysfunction. In the current study, we advance this work by characterizing the effects of E-cig on lung endothelial nanomechanical properties and barrier function. Lung EC exposure to E-cig extract (50 µg/mL) resulted in disruption of endothelial barrier properties as assessed by Electric Cell–Substrate Impedance Sensing (ECIS). Since excess mitochondrial reactive oxygen species (mitoROS) is an important marker of mitochondrial dysfunction, we next assessed the effect of Mito-TEMPO (10 µM, 3 h), a cell-permeable antioxidant, on E-cig-induced endothelial permeability. Pretreatment with Mito-TEMPO provided EC barrier protection after E-cig challenge, suggesting a key role of mitoROS in E-cig-induced EC permeability. E-cig exposure induces cytoskeleton rearrangement, leading to gap formation in lung EC, and significantly alters EC elastic properties as assessed by atomic force microscopy (AFM). Reduction in CTTN expression by siRNA further augmented the injurious effects of E-cig on EC permeability and elastic properties. This is the first study to explore the role of CTTN in evaluating the effect of E-cigarette exposure on the lung endothelium using AFM and provides novel mitochondrial and biophysical characterization of the effects of E-cig exposure on human lung EC. This work advances our understanding of the pathophysiologic effects of E-cig exposure. Full article

This study investigates how molybdenum oxide (MoO_x) rear interface passivation—specifically its thickness and deposition conditions—affects CIGS thin-film solar cells. The MoO_x layer effectively suppresses selenium/sulfur diffusion into the molybdenum back contact during high-temperature processing, while improving the absorber’s microstructure by reducing interfacial voids. These modifications enhance electrical properties, yielding lower series resistance, higher shunt resistance, and improved fill factor and current density. Although recombination increases slightly, the reduction in voltage-related fill factor loss ultimately boosts hole extraction and suppresses electron recombination at the back contact. Consequently, MoO_x-passivated cells achieve superior performance, with industrial-scale modules (1650 mm × 658 mm) reaching 152.41 W output power and 14.0% efficiency. This work provides valuable insights for optimizing MoO_x-based interface engineering to improve CIGS solar cell efficiency and manufacturability. Full article

Alternate (irregular) bearing, characterized by large fluctuations in fruit yield between consecutive years, remains a major constraint to sustainable avocado (Persea americana) production. This study aimed to assess the potential of satellite remote sensing and climatic variables to characterize and predict alternate bearing patterns in commercial orchards in Tzaneen, Limpopo Province, South Africa. Historical yield data (2018–2024) from 46 “Hass” avocado blocks were analyzed alongside Sentinel-2 derived vegetation indices (NDVI, GNDVI, NDRE, CIG, CIRE, EVI2, LSWI) and flowering indices (WYI, NDYI, MTYI). To align temporal scales, all VIs and FIs were aggregated into eight quarterly averages from the two years preceding each yield year and spatially averaged across each orchard block. Climatic predictors including maximum temperature (Tmax), minimum temperature (Tmin), vapor pressure deficit (VPD), and precipitation were screened against historical yields to identify critical periods, with June–October emerging as the most influential months, and these variables were aggregated accordingly to match annual alternate bearing patterns. Five machine learning (ML) algorithms—Random Forest, XGBoost, CATBoost, LightGBM, and TabPFN—were trained and tested using a Leave-One-Year-Out (LOYO) approach. Results showed that VPD, Tmin, and Tmax during the flowering period (July–September) were the most influential variables affecting subsequent yields. TabPFN achieved the highest predictive accuracy (Accuracy = 0.88; AUC = 0.95) and strongest temporal generalization. Spectral gradients between flowering and early fruit drop were lower during “on” years, reflecting stable canopy vigor. This combined use of remote sensing and climatic variables in a ML framework represents a novel approach, and the findings demonstrate that integrating remote sensing and climatic indicators enables early discrimination of “on” and “off” years, supporting proactive orchard management and improved yield stability. Full article

Electronic cigarettes (E-Cig) are a new way of delivering nicotine, gaining popularity among adolescents and young adults, who often do not realize their harmful effects. Although the adverse effects of E-Cigs on the liver and heart have been demonstrated, their effects on the skeletal muscle have not been well studied. In this study, we evaluated the skeletal muscle effects of E-Cig aerosol, delivered in a manner similar to human vaping, in a mouse model of obesity induced by a high-fat diet (HFD). C57BL/6 mice, fed either a normal chow diet (NCD) or HFD, were exposed to either saline aerosol control or aerosol generated from Blu PLUS^TM containing 0% or 2.4% nicotine for 12 weeks. Mice fed an NCD were included to distinguish whether E-Cig effects on the skeletal muscle required the presence of obesity induced by an HFD. The soleus muscle, an oxidative muscle rich in mitochondria, was assessed by Western blotting, electron microscopy, and biochemical assays. An NCD group was included to assess the baseline effects of HFD-induced obesity, on the skeletal muscle. The skeletal muscle from HFD-fed mice exposed to E-Cig 2.4% had reduced levels of phospho-AMPK compared with saline and E-Cig 0% groups, while E-Cigs had no effect on NCD-fed mice. Levels of phospho-adipose triglyceride lipase were also reduced in both E-Cig 2.4% and 0% compared with the saline group. These metabolic protein impairments were accompanied by increased levels of oxidative stress and phospho-p38 MAPK. Deregulation of the autophagy markers, microtubule-associated protein 1A/1B-light chain 3 (LC3-I; inactive form) and LC3-II (active form), was also observed, evidenced by decreased levels of LC3-II, ratio LC3-II/LC3-I, and increased levels of p62. Transmission electron microscopy analysis showed that E-Cig 2.4% induced damage to mitochondrial structure compared with the saline or E-Cig 0% groups. These findings suggest that E-Cig exposure on HFD impairs the skeletal muscle, adding to the growing list of affected organs for ongoing regulatory efforts concerning nicotine-containing substances. Full article

The tunable bandgap of CIGSe has established bandgap engineering as a pivotal research direction for advancing the efficiency frontiers of solar cells. In particular, the proposal of the V-shaped bandgap gradient has motivated extensive efforts to achieve precise control over elemental composition and spatial distribution within the absorber layer. Against this backdrop, this review systematically classifies active control strategies—such as surface sulfurization, Ga grading, and Ag alloying—according to their doping mechanisms and the resulting bandgap profiles. It further evaluates emerging profiles, including the “hockey-stick” distribution, against the conventional V-shaped benchmark, and explores future pathways for bandgap engineering in next-generation, high-efficiency photovoltaic devices. Further improvements in photovoltaic efficiency can effectively boost power generation and lower solar power costs, providing a practical solution to future energy and environmental challenges. Full article

The global temperature increase has posed urgent challenges, with buildings accountable for as much as 40% of CO₂ emissions, and their decarbonization is critical to meet the net-zero target by 2050. Solar photovoltaics present a promising trajectory, especially through building-integrated photovoltaics (BIPVs), where thin-film technologies can be used to replace traditional building materials. This article critically examined the development of thin-film solar cells for BIPVs, including their working mechanisms, material structures, and efficiency improvements in various generations. The discussion underscored that thin-film technologies, including CdTe and CIGS, had noticeably shorter energy payback times between 0.8 and 1.5 years compared to crystalline silicon modules that took 2 to 3 years, thus promising quicker recovery of energy and higher sustainability values. Whereas certain materials posed toxicity and environmental concerns, these were discovered to be surmountable through sound material selection and manufacturing innovation. The conclusions highlighted that the integration of lower material usage, high efficiency potential, and better energy payback performance placed thin-film BIPVs as an extremely viable option for mitigating lifecycle emissions. In summary, the review emphasized the critical role of thin-film solar technologies in making possible the large-scale implementation of BIPVs to drive the world toward net-zero emissions at a faster pace. Full article

This study proposes a novel framework for analyzing Vehicle-Integrated Photovoltaic (VIPV) systems, integrating optical, thermal, and electrical models. The model modifies existing fixed PV methodologies for VIPV applications to assess received irradiance, PV module temperature, and energy production, and is available as an open-source MATLAB tool (VIPVLIB) enabling simulations via a smartphone. A key innovation is the integration of meteorological data and real-time driving, dynamically updating vehicle position and orientation every second. Different time resolutions were explored to balance accuracy and computational efficiency for optical model, while the thermal model, enhanced by vehicle speed, wind effects, and thermal inertia, improved temperature and power predictions. Validation on a minibus operating within the University of Palermo campus confirmed the applicability of the proposed framework. The roof received 45–47% of total annual irradiation, and the total yearly energy yield reached about 4.3 MWh/Year for crystalline-silicon, 3.7 MWh/Year for CdTe, and 3.1 MWh/Year for CIGS, with the roof alone producing up to 2.1 MWh/Year (c-Si). Under hourly operation, the generated solar energy was sufficient to fully meet daily demand from April to August, while during continuous operation it supplied up to 60% of total consumption. The corresponding CO₂-emission reduction ranged from about 3.5 ton/Year for internal-combustion vehicles to around 2 ton/Year for electric ones. The framework provides a structured, data-driven approach for VIPV analysis, capable of simulating dynamic optical, thermal, and electrical behaviors under actual driving conditions. Its modular architecture ensures both immediate applicability and long-term adaptability, serving as a solid foundation for advanced VIPV design, fleet-scale optimization, and sustainability-oriented policy assessment. Full article

Gold (Au) is one of the noble metals most used as a catalyst in the growth of one-dimensional nanostructures. Usually, an ultra-thin Au film is coated followed by thermal annealing to obtain Au nanoclusters. Although annealing temperature, duration and film thickness parameters have been heavily studied, there are no studies on the sputter working gas pressure, which also greatly affects the film microstructure. In this study, low (5 mTorr) and high (15 mTorr) working gas pressures were examined in addition to Au film thicknesses of 2 nm, 5 nm and 8 nm. Additionally, copper indium gallium selenide (CIGS) films were deposited on Au films with different thicknesses and argon (Ar) gas pressures. It was confirmed from SEM and AFM images that the Au films undergo drastic morphology change from smooth to extremely porous film surfaces with increasing thickness regardless of gas pressure. However, the porosity of films is increased at higher growth pressure for each thickness. Specifically, the most porous film was obtained at a 5 nm thickness with 15 mTorr, and it was filled with nanomounds. Not surprisingly, the only apparent columnar-type formation was observed for CIGS deposition, which was carried out on the most porous film. It can be interpreted that Au nanomounds behave like catalysts on which the CIGS nanocolumns grow. Full article

Preeclampsia (PE) and intrauterine growth restriction (IUGR) are major pregnancy complications that are linked to placental dysfunction and environmental stimulation such as the use of electronic cigarettes (eCig). This study investigates the molecular impacts of timed eCig exposure in a C57BL/6 mouse model of PE and IUGR using bulk RNA-sequencing of placental tissues. Pregnant mice were exposed to eCig vapor via nose-only system starting at embryonic day 12.5 (eCig-6d, before spiral artery (SA) invasion) or 14.5 (eCig-4d, after SA invasion) until E18.5 (necropsy), with healthy controls exposed to room air (n = 6/group). The eCig-4d group developed PE, whereas the eCig-6d group developed both PE and IUGR. RNA-seq analysis revealed 429 differentially expressed genes (DEGs) in eCig-4d (IUGR-like) group and 64 DEGs in eCig-6d (PE + IUGR-like) group compared to controls. Pathway and gene network analyses indicated that eCig-4d exposure activated NF-κB–driven inflammation, suppressed ECM organization and collagen biosynthesis, and downregulated vasoactive genes/mitochondrial-associated genes (NOS1/2), accompanied by impaired complement initiation and reduced both macrophage and monocyte signals. Similarly, eCig-6d exposure led to downregulation of complement-associated genes and granule-related components, possibly implicating weakened neutrophil responsiveness and compromised inflammatory resolution at the maternal–fetal interface. Our findings align with prior studies on physiological dysfunctions in PE and IUGR, while also providing novel insights into the temporally specific cellular responses induced by eCig exposure. Full article

Non-destructive diameter estimation of cabbage heads and yield prediction employing Unmanned Aerial Vehicle (UAV) imagery are superior to conventional approaches, which are labor intensive and time consuming. This approach assesses spatial variability across the field, effective allocation of resources, and supports variable application rates of fertilizer and supply chain management. Here, individual cabbage head diameters were estimated using deep learning-based pose estimation models (YOLOv8s-pose and YOLOv11s-pose) using high spatial resolution RGB images acquired from UAV 6 m during the cabbage-growing season in 2024. With a mean relative error (MRE) of 4.6% and a high mean average precision (mAP) 98.5% at 0.5, YOLOv11s-pose emerged as the best-performing model, verifying its accuracy for pragmatic agricultural use. The approximated diameter was then combined with climatic variables (temperature and rainfall) and canopy reflectance indices (normalized difference vegetation index (NDVI), normalized difference red edge index (NDRE), and green chlorophyll index (CIg)) that were extracted from the multispectral images with 6 m resolution and fed into AI models to develop individual cabbage head fresh weight. Among the machine learning models (MLMs) tested, CatBoost achieved the lowest Mean Squared Error (MSE = 0.025 kg/cabbage), highest R² (0.89), and outperformed other models based on the Diebold–Mariano statistical test (p < 0.05). This finding suggests that an integrated AI-powered framework enhances non-invasive and precise yield estimation in cabbage farming. Full article

In the context of reservoir monitoring, time-lapse (4D) full-waveform inversion (FWI) of seismic data can potentially estimate reservoir changes with high resolution. However, most existing field-data applications are carried out with isotropic, and often acoustic, FWI algorithms. Here, we apply a time-lapse FWI methodology for transversely isotropic (TI) media with a vertical symmetry axis (VTI) to offshore streamer data acquired at Pyrenees field in Australia. We explore different objective functions, including those based on global correlation (GC) and designed to mitigate errors in the source signature (SI, or source-independent). The GC objective function, which utilizes mostly phase information, produces the most accurate inversion results by mitigating the difficulties associated with amplitude matching of the synthetic and field data. The SI FWI algorithm is generally more robust in the presence of distortions in the source wavelet than the other two methods, but its application to field data is hampered by reliance on amplitude matching. Taking anisotropy into account provides a better fit to the recorded data, especially at far offsets. In addition, the application of the anisotropic FWI improves the flatness of the major reflection events in the common-image gathers (CIGs). The 4D response obtained by FWI reveals time-lapse parameter variations likely caused by the reservoir gas coming out of solution and by the replacement of gas with oil. Full article