Growth Process Research Articles

Abstract. Organosulfate (OS) surfactants can influence cloud condensation nuclei (CCN) activation and hygroscopic growth by reducing the surface tension of aerosol particles. We investigate the surface tension and hygroscopicity of aerosols containing short- and long-chain OSs in supersaturated aqueous droplets using an electrodeformation method coupled with Raman spectroscopy. For droplets containing short-chain OSs, the surface tension decreases as relative humidity (RH) decreases, even under dry and highly viscous conditions. Sodium ethyl sulfate (SES) lowered surface tension to approximately 30 mN m−1, a value lower than that of sodium dodecyl sulfate (SDS) at its critical micelle concentration. We also studied ternary systems containing OSs with citric acid (CA) or sodium chloride (NaCl). Even small amounts of SDS, with a molar ratio of 10−3 relative to CA, reduce surface tension by up to 40 % at low RH compared to CA alone. Despite strong surface tension reduction, ternary OS–CA–water systems show hygroscopicity nearly identical to binary CA–water systems, suggesting that surface tension does not influence water uptake under subsaturated conditions. Ternary systems containing NaCl and OS undergo efflorescence at 47 % RH, but the crystallized NaCl becomes partially engulfed. If the RH is subsequently increased, the particle takes up water. At the deliquescence point (72 % RH), the particle becomes homogeneous again. These findings improve our understanding of particle growth and cloud drop formation processes, which influence cloud properties like albedo and lifetime.

As global concern for food security continues to grow, modern monitoring technologies are playing a pyramidally crucial role in the agricultural sector. However, in the face of complex and fluctuating light requirements during crop growth, the further development of environmental monitoring technology is constrained by both the complexity and variability of environmental conditions and the limited accuracy and functionality of current light sensors. Herein, a self-powered all-inorganic tin-lead (Sn-Pb) perovskite photodetector (PD) is reported, and a novel all-in-one engineering approach utilizing benzenesulfonyl hydrazide (BSH) is incorporated to effectively enhance the photodetection performance of the PD. The BSH molecule plays a pivotal role in balancing and mitigating crystallization and grain growth processes of Sn-Pb perovskite, while also inhibiting the oxidation of Sn2+ and the formation of Sn vacancy defects in perovskite film. Consequently, the optimized champion PD reaches a responsivity of 0.36 A W-1 and a detectivity of 1.74 × 1013 Jones at 650 nm. Benefitting from its excellent performance, the prototype of a light sensor employing PDs achieves specific detection of red and blue light in a simulated lighting environment required for plants development. This research not only presents a feasible strategy to improve photodetection performance of Sn-Pb perovskite PDs but also provides novel insights for designing monitoring and feedback systems in intelligent agriculture applications.

High-throughput sequencing technology was used to systematically analyze the composition, diversity, and dynamic changes of soil microbial communities during the wheat growing season in Lintong, Shaanxi Province. The abundance of bacterial communities significantly increases after the complete planting cycle of wheat, while the fungal community structure was relatively stable. At the phylum level, Proteobacteria, Acidobacteria, Bacteroidetes, and Actinobacteria constitute the dominant bacterial communities. The fungal community was Ascomycota and Zygomycota. The growth process of wheat significantly changes the structural composition of bacterial communities, enhances enzyme activity and biological regulatory functions of bacterial communities, while inhibiting cellular processes and environmental information processing functions. This study revealed the succession pattern of soil microbial communities during the wheat growing season, identified key microbial groups that maintain soil ecosystem functions, and provided an important theoretical basis and practical guidance for the sustainable management of the surface substrate layer in the study area. Bangladesh J. Bot. 54(3): 741-748, 2025 (September) Special

Abstract This paper examines the extensive and intensive margins of intangible investments in firm growth processes in the short and medium term. Both intensive and extensive margins of investment are highly skewed and differ across sectors. Less productive firms are less likely to invest in intangibles, whereas incorporated firms are more likely to do so. Intangible capital only complements physical capital for a limited number of firms. Intangible investment is positively associated with short-term productivity growth, especially among firms that invest consistently over time. Medium-term effects on productivity are limited, and largely confined to the top-performing firms. For employment growth, we find systematic short-term effects of intangible investment. Regular investment patterns correlate with higher employment growth over both time horizons. These results challenge conventional assumptions that intangible capital uniformly enhances firm performance and highlight the importance of sustained investment behaviour and sectoral context.

The transport of sugars produced by photosynthesis between source and sink tissues controls multiple biological processes in growth and development. However, the key factors, both genetic and environmental, that influence sugar transport and crop yield are largely unknown. We identified a plasma membrane-localized sugar transporter, GmSWEET38, that facilitates the translocation of sugars to seeds and nodules in soybean (Glycine max L.). GmSWEET38 exhibited both efflux and influx activities of sucrose and fructose in Xenopus oocytes. GmSWEET38 expression was high in the vascular system of roots and nodules, and overexpression of GmSWEET38 enhanced the sugar contents of roots and seeds, consequently promoting nodule development and seed production. Loss of GmSWEET38 function exerted the opposite effects. Intriguingly, GmSWEET38 specifically transported fructose into the rhizosphere, where it is used by beneficial bacteria. By modulating sugar transport and allocation to enhance symbiotic nitrogen fixation, GmSWEET38 can be used for the breeding of high-yielding soybean cultivars.

The perovskite solar cells (PSCs) are advancing toward commercialization, with the development of large‐area modules serving as a critical prerequisite. The continuous production of perovskite solar modules (PSMs) needs more time for film deposition and involves more complex sample transfer operations compared with small‐area perovskite fabrication, thus requiring broadening the process window. Here, we proposed a custom‐tailored solvent engineering strategy to broaden the prevacuum‐quenching interval window for achieving efficient PSCs and PSMs through incorporating hexamethylphosphoramide (HMPA). Due to the strong interaction between PbI 2 and HMPA, this solvent engineering delays the perovskite nucleation and growth process, leading to the perovskite film with reduced defect density and lateral heterogeneity. Besides, the stable PbI 2 ‐HMPA combination stabilizes the intermediate solvent phases in the wet film, broadening the prevacuum‐quenching interval window from 30 to 60 s. Consequently, the resulting PSCs fabricated in ambient air achieved a champion power conversion efficiency (PCE) of 24.37%, with enhanced device stability. Furthermore, the PSMs (47.94 cm 2 ) obtained a champion PCE of 20.16% with high reproducibility, demonstrating the feasibility and flexibility of our strategy to large‐scale production of perovskite devices.

The formation of bubbles at an orifice is a key problem in gas–liquid two-phase flow. In the electronic atomizer, the bubble size and generation frequency formed at the gas exchange port are important factors affecting the heat and mass transfer efficiency and two-phase flow in the atomization process. Therefore, it is of great theoretical and practical significance to study the process of bubble growth and detachment at the orifice. In this work, the dynamic change in bubble volume during the periodic growth of the orifice is analyzed by visual experiments. The effects of outlet liquid flow rate, orifice parameter, and liquid properties on bubble detachment volume and detachment frequency are discussed. It is found that under different orifice diameters and outlet liquid flow rates, the bubble generation period can be divided into three forms: single-, double-, and triple-bubble periodicities based on the number of bubbles in the period. The detachment frequency and detachment volume of bubbles increase with the increase the in outlet flow rate. The change in liquid properties also affects the bubble growth and detachment characteristics. This work provides a theoretical basis for the design of an air exchange structure in an electronic atomizer.

Phase boundary dynamics for ice nucleation and growth processes in fresh and sea water

Based on an optimized InAs/(001) InP quantum dot (QD) growth process, we systematically characterized 1.55 μm InAs QD lasers and demonstrated markedly improved high-temperature operation. Continuous-wave lasing above 105°C was achieved both in Fabry-Pérot (FP) devices with five QD layers in the broad-area (BA) geometry and nine QD layers in a narrow-ridge geometry. Under pulsed operation, these FP-BA lasers sustained lasing up to 120°C, and it reached a low threshold current density of 296 A/cm2 (59.2 A/cm2 per QD layer).

Effects of combined high temperature and water stress on soybean growth and physiological processes in a temperature gradient chamber

Seasonal evolution of brackish ice microstructure during growth and decay processes

Insights into the physiological and biochemical responses of peanut plants under combined arsenic and flooding stress.

The PuWRKY29-PuMYB62 module responds to salicylic acid to inhibit the synthesis of stone cells in 'Nanguo' pear.

Hydraulic fracturing is a technique employed to weaken rock formations during hard rock excavation. This study aims to investigate the impact of hydraulic fracturing on crack propagation in rock walls and its subsequent effect on the load borne by roadheaders during the cutting of pre-cracked rock. A three-dimensional model for the crack growth process in rock walls under hydraulic fracturing is developed using the CFD-DEM (Computational Fluid Dynamics–Discrete Element Method) two-way fluid–structure coupling approach. The results indicate that crack propagation under hydraulic fracturing occurs in four distinct phases: the initiation of the main crack, the further development of the main crack, the fine cracking phase, and the retardation of the main crack with the subsequent expansion of secondary cracks. The study analyzes the influence of pore size and water injection pressure on crack growth. It is observed that an increase in pore size and injection pressure within a certain range results in a nonlinear increase in crack propagation. Specifically, when the hydraulic fracturing aperture expands from 85 mm to 100 mm, the number of fracture bonds increases by 56.2%. Similarly, as water injection pressure rises from 25 MPa to 40 MPa, the number of broken bonds increases by 153.9%. The force exerted on rock with pre-existing cracks is found to be 9.05% lower compared to unfractured rock, with the average forces in the Z and Y directions reduced by 11.46% and 7.2%, respectively. However, the average force in the X direction increases by 5.49%. These findings provide a valuable reference for optimizing hydraulic fracturing procedures in hard rock excavation.

Label-free prediction of vascular connectivity in perfused microvascular networks in vitro.

Gradient descent, computed through backpropagation (BP), has been widely used to train spiking neural networks (SNNs). However, the approach has several limitations. It requires manual intervention to tune the network architecture, is prone to catastrophic forgetting of previously learned information when exposed to data containing new information, and is computationally demanding. To address these issues, we propose brain-mimetic developmental spiking neural networks (BDNNs), which emulate the postnatal development of biological neural circuits. We evaluated BDNNs using a neuromorphic tactile system with the task of classifying objects through grasping. Our findings show that BDNNs grow dynamically in response to input data by incrementally recruiting hidden neurons, leading to steadily increasing classification accuracy without the need for manual architecture tuning. The growth process adapts autonomously to the complexity of incoming data. BDNNs also exhibit strong knowledge transfer capabilities, which effectively leverage previously learned knowledge about grasping objects to incrementally learn about new objects. Furthermore, in comparative experiments using the same dataset and hardware, BDNNs achieved classification performance comparable to the standard BP-based method and its variants, while learning one to three orders of magnitude faster. Furthermore, the BDNN outperforms existing continual learning algorithms in the performance and speed. These results highlight BDNNs as a promising approach for continual learning and real-time edge computing applications. The source code of our work is publicly available at https://github.com/1jiaqixing/BDNNversion1.

Researchers now successfully fabricate well-aligned transition metal dichalcogenide (TMD) nanowires and nanobelts. However, achieving efficient carrier transport perpendicular to the nanowire direction remains a significant challenge, which continues to limit their application in integrated polarization-sensitive devices. Based on the synergistic mechanism of precursor anisotropic diffusion and step-edge-guided growth, an effective chemical vapor deposition (CVD) approach enabled by in situ coverage monitoring is developed to overcome existing limitations. By precisely terminating the growth process at its optimal stage, highly aligned and crosstalked monolayer MoS2 nanoribbons (NRs) are obtained. Crucially, these NRs demonstrate efficient current conduction along both the parallel and perpendicular directions, enabled by the inter-ribbon crosstalk structures. Reflection difference spectroscopy (RDS) and polarized Raman characterization confirm strong in-plane optical anisotropy within the arrays. Electrical measurements reveal a remarkably high parallel-to-perpendicular current ratio of up to 63.2 at 30V bias, enabling a distinct polarized light response. Furthermore, transient absorption (TA) spectroscopy uncovers anisotropic carrier dynamics in the NR arrays. This work represents the first demonstration of mimicking the differential electrical transport behavior characteristic of intrinsically anisotropic materials using an otherwise isotropic TMD material system, opening new possibilities for anisotropic optoelectronics.

Personality assessment has long been recognized as a valuable tool for understanding individual differences with implications for self-understanding and growth-related processes. Building on the development of the Personality Spectrum Analysis (PSA), the present study evaluated the SOLACE Spectrum, a revised and expanded measure designed to provide a reliable and accessible framework for understanding personality in therapeutic and relational contexts. Data were collected from 1021 adults through online administration, and exploratory factor analysis revealed six components: Stability, Optimism, Leadership, Achievement, Compassion, and Extroversion. The instrument demonstrated strong internal consistency (α = 0.91) and robust test–retest reliability (0.851–0.922), indicating stability over time. Findings support the SOLACE Spectrum as a psychometrically sound measure that can inform understanding of personality traits, relationship processes, and personal growth processes. Its application may assist professionals in therapy, counseling, and educational or organizational settings by providing descriptive feedback on personality dimensions, highlighting areas of strength, and identifying potential areas for reflection and personal insight.

Abstract Magnetic minerals can preserve remanent magnetization to provide ancient magnetic field records. Although thermoremanent magnetization (TRM) is well understood, chemical remanent magnetization (CRM) from chemical processes is also prevalent in nature and can complicate TRM records by introducing additional remanence signals. Previous studies show that CRM in single‐domain (SD) particles can lead to paleointensity underestimates. However, most natural magnetic particles are non‐uniformly magnetized, such as in the single‐vortex (SV) states, whose CRM mechanism remains unclear. Using micromagnetic modeling, we investigate CRM acquisition in fine‐grained magnetite during grain growth processes. We show that the CRM in SV particles is nearly linear with the external magnetic fields below 100 μT, within typical terrestrial magnetic fields. Unlike SD particles, SV particles show stronger CRM compared to TRM, which could potentially bias to higher paleointensity estimates. These findings highlight the importance of considering non‐uniform domain states when interpreting CRM records in paleomagnetic studies.

A design methodology of crystal growth furnace and process aided by two-step optimization using machine learning models and genetic algorithm