AI Scientific Illustration Gallery

Generate a schematic diagram of the wetting gradient effect. The difference in hydrophilicity and hydrophobicity on the two sides of the fabric can be used to construct a wetting gradient structure. When the inside of the fabric is hydrophobic and the outside is hydrophilic, the capillary force of the hydrophilic outer layer can drive moisture to pass through the hydrophobic inner layer. Furthermore, the hydrophobic inner layer repels moisture, increasing the driving force, causing the moisture to directionally transport outward without the application of external force.

APPROVED Scientific Illustration Style and Rendering Guidelines: Illustrations should adhere to a scientific illustration style, characterized by flat vector graphics, clean lines, and a white background. All figures must be high-resolution and suitable for publication. Color coding should be consistent with the following scheme: * Biological processes: green * Electrochemical processes: blue * AI & control intelligence: cyan Decorative or artistic elements are prohibited. Layout: The illustration should consist of four vertical panels arranged from left to right with balanced spacing and thin separators. Panel 3 (AI & integration) should be visually dominant. Panel 1 – Circular Feedstock Input: This panel should depict a circular feedstock input using standard scientific icons to represent food waste, animal manure, and wastewater. These inputs should converge into a single funnel labeled "high-strength organic feedstock." A circular arrow motif should be included to indicate the circular bioeconomy concept. No explanatory text is permitted in this panel. Panel 2 – Two-Stage Bioelectrochemical Conversion: * Top: A dark fermentation bioreactor (cylindrical vessel) should be shown. Arrows should indicate the conversion of organic matter into H₂ (gas bubbles) and a VFA-rich effluent. * Bottom: A schematic of a microbial electrolysis cell should be displayed, including the anode, cathode, proton exchange membrane, and external circuit. Show electro-

A schematic diagram illustrating the mechanism of a moisture-wicking fabric, designed with differential capillary action. This fabric consists of two layers with a coarse-to-fine fiber structure from the inside to the outside. This structure creates differences in fiber fineness and pore size, facilitating moisture diffusion from the inner layer to the outer layer, followed by evaporation.

Design a clean, high-resolution graphical abstract suitable for journal publication (flat scientific style, soft gradients, white background, minimal decorative elements) illustrating an AI-integrated dark fermentation–microbial electrolysis cell (DF–MEC) system for biohydrogen production. Layout (4 vertical panels, left → right): Panel 1 – Circular Feedstock Input: Icons representing food waste, livestock manure, and wastewater converging into a funnel labeled "high-strength organic waste," emphasizing a circular bioeconomy approach. Employ minimal labeling and standardized scientific icons. Panel 2 – Two-Stage Bioprocess: Top: Dark Fermentation reactor depicting H₂ production and VFA-rich effluent generation (simple arrows, gas bubbles). Bottom: Microbial Electrolysis Cell (MEC) illustrating anode oxidation of VFAs, electron flow through an external circuit, proton transport across a membrane, and hydrogen evolution at the cathode. Utilize schematic electrochemical symbols and minimal annotations. Panel 3 – AI-Enabled Intelligence & System Integration (Core Focus): Central AI

Create a clear and aesthetically pleasing scientific diagram for a school poster, in a vector academic illustration style, divided into three vertical or horizontal panels connected by progression arrows, representing the levels of organization of a chicken eggshell. At the scale of the shell (middle or central panel): Detailed cross-sectional view of the eggshell. Clearly label the layers from the outside to the inside: • Outer cuticle (antibacterial barrier) • Palisade layer (vertical calcite columns) • Mammillary cores (anchoring points) • Shell membranes (interwoven protein fibers) Add a small magnifying glass or zoom showing the organized calcite crystals. At the system level (in the uterus) – left or top panel: Simplified diagram of the uterus of the hen's oviduct. Show the egg forming surrounded by uterine fluid. Annotations: • Complete formation in ≈ 20 hours • Specific proteins (ovocleidin)

You are required to create a detailed vector art flowchart and graphical abstract illustrating a multi-step laboratory process for preparing and coating a carbon nanotube (CNT) dispersion solution onto a fabric sample. Follow these instructions precisely: 1. Step 1: Depict a precise digital balance being used to weigh 0.15 grams of CNT powder. 2. Step 2: Show a beaker containing 30 mL of distilled water to which the CNT powder is added. 3. Step 3: Illustrate a probe-type ultrasonic device operating at 150 watts, dispersing CNT particles evenly in the water. Emphasize the uniform suspension of CNT particles in the solution. 4. Step 4: Represent the fabric sample immersed in the CNT dispersion within the beaker, which is placed on a magnetic stirrer at room temperature. Illustrate the sequential coating cycles, clearly showing a thin CNT layer depositing on the fabric's surface. 5. Step 5: Graphically depict placing the coated fabric inside an oven set...

APPROVED. This document outlines a multi-step laboratory process for preparing and coating a carbon nanotube (CNT) dispersion solution onto a fabric sample, suitable for illustration as a vector art flowchart and graphical abstract. The process includes: 1) Weighing 0.15 grams of CNT powder using a digital balance. 2) Adding the CNT powder to 30 mL of distilled water in a beaker. 3) Dispersing the CNT particles in the water using a probe-type ultrasonic device operating at 150 watts, ensuring uniform suspension. 4) Immersing the fabric sample in the CNT dispersion within the beaker, placed on a magnetic stirrer at room temperature, and illustrating sequential coating cycles with a thin CNT layer depositing on the fabric surface. 5) Placing the coated fabric inside an oven.

APPROVED. This document outlines a multi-step laboratory procedure for preparing and coating a carbon nanotube (CNT) dispersion solution onto a fabric sample. The process involves: 1) Weighing 0.15 grams of CNT powder using a digital balance. 2) Adding the CNT powder to 30 mL of distilled water in a beaker. 3) Sonicating the mixture using a probe-type ultrasonic device at 150 watts to achieve uniform dispersion of CNT particles in the water. 4) Immersing the fabric sample in the CNT dispersion within the beaker, which is placed on a magnetic stirrer at room temperature, illustrating sequential coating cycles and the deposition of a thin CNT layer on the fabric surface. 5) Placing the coated fabric inside an oven.

Graphical Abstract Abstract Due to the high toxicity and low degradability of phenolic compounds, including hydroquinone (HQ), in environmental samples, there is a strong need for the development of efficient catalytic systems for the oxidation of hydroquinone to benzoquinone (BQ). Catalytic oxidation using nanoscale metal-based catalysts has been recognized as an effective approach for the removal of such contaminants. In this study, reduced graphene oxide-based iron oxide, iron nitride, and cobalt ferrite nanocomposites were synthesized using co-precipitation, pyrolysis, and hydrothermal methods. The obtained nanocomposites were characterized by UV–Vis spectroscopy, X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) surface area analysis, and field-emission scanning electron microscopy (FESEM). The catalytic performances of the synthesized nanocomposites toward the oxidation of hydroquinone to benzoquinone using H₂O₂ in aqueous solution were comparatively evaluated. The results

Generate a mechanism diagram for the photocatalytic degradation of organic pollutants.

This graphical abstract highlights research axes 1 to 4, alignment with the LAQV Strategy, the vision statement for a future pedagogical project, and the conclusion with final remarks.

Title: Delayed Immunomodulation Reverses Functional Connectivity and Motor Deficits in Adulthood After Neonatal Hypoxia-Ischemia (HI) Authors: Sanjana Mandhan, Eric Chin, Anushka Acharya, Riddhi Patel, Fabiola Beatriz Santiago Maldonado, Diana Ortega, Hawley Helmbrecht, Shenandoah Robinson, Lauren Jantzie. Background: Neonatal hypoxic-ischemic encephalopathy (HIE) occurs when the newborn brain is deprived of oxygen and blood flow around the time of birth. It remains a major cause of lifelong neurological and developmental disability in term infants. The resulting inflammation, oxidative stress, and cell death disrupt normal brain development, leading to long-term problems in movement, learning, and cognition. Current treatments such as therapeutic hypothermia provide only limited protection and do not completely prevent these functional disabilities. To this end, we repurposed an immunomodulatory cocktail containing melatonin to test the hypothesis that disrupted functional neural

A schematic diagram of the direct modulation process of a semiconductor laser, including the key steps of direct modulation and the resulting detrimental effects.

LLM-based drug recommendation + safety (DDI) + long-tail/imbalance + molecular structure alignment + Stage2 frequency-aware fusion. Top Left: LLM output resulting in a safety failure due to drug-drug interaction. Illustrate the input for a patient visit 't' (Dx/Proc/Text) → LLM → Recommended drug set {A, B, C}. Within {A, B, C}, highlight a DDI pair (e.g., A–B) with a red lightning bolt, and label it as "unsafe combination / DDI". Top Right: Why this occurs (lack of structural constraints). Label it as "atomic label embeddings + co-occurrence shortcut". Illustrate an unstructured label space: drug points are disorganized, and unsafe pairs are in close proximity. Bottom Left: Long-tail/imbalance failure. Include a frequency binning histogram from MIMIC-IV (0–50, 50–100…>5000), showing a high head and a long tail. Label it as "tail labels: sparse supervision → poor recall / calibration". Bottom Right: Our solution (structure + frequency-aware). Stage 1: Drug node graph (DDI edges in red, EHR co-occurrence edges in blue, temporal edges as dashed lines), where each ATC3 is a 'multi-prototype' small cluster. Stage 2: Schematic bar weights illustrating LLM + frequency-aware fusion (tail relies more on molecule prior; head relies more on task signal).

The following hypothesis is proposed: BMSC-Exos act on intestinal cells, upregulating and regulating endogenous ACSF2 expression, enhancing mitochondrial fatty acid activation and promoting mitochondrial β-oxidation (FAO), thereby improving mitochondrial function, reducing ROS levels, and inhibiting the NF-κB inflammatory pathway, ultimately promoting intestinal mucosal repair and achieving a therapeutic effect on Crohn's disease. Based on this and previous conversations, could you help me create a schematic diagram of the research effects and hypotheses?

## Part 1: Top Title and Overall Paradigm Position: At the top of the technology roadmap, centered. Content: Main Title: Text: Research Roadmap of Photodetectors Font Size: 28 points, bold. Subtitle/Research Paradigm: Text: "Calculation-Preparation-Construction-Design" Four-in-One Research Paradigm Font Size: 20 points, bold, font color is dark gray. Overall Timeline: Text: Draw a horizontal arrow across the entire diagram below the title. Labels: Label "Stage 1", "Stage 2", "Stage 3", "Stage 4" equidistantly above the arrow, and label virtual times such as "M1-M6", "M7-M12", etc. Arrow Style: 2 points thick, black. ## Part 2: Stage 1 - Calculation Position: Below "Stage 1" of the overall timeline. Structure: Divided into four layers vertically. Layer 1: Stage Title Bar Text: Stage 1: Theoretical Calculation and Mechanism Elucidation Font Size: 22 points, white, bold. Background: Dark blue rectangle, width equal to the stage content. Layer 2: Core Methods Text: [Core Methods] DFT | First Principles | Molecular Dynamics Font Size: 16 points, bold. Style: Light blue rounded rectangle, centered text. Layer 3: Research Content (three boxes in parallel) Box 1: Title: A-site Ion Substitution Content: A₄PbCl₆ Calculation Font Size: Title 14 points bold, content 12 points. Box 2: Title: B-site Ion Doping Content: Sb³⁺ Doping Font Size: Same as above. Box 3: Title: Theoretical Prediction Content: Dielectric Function; Absorption Spectrum Font Size: Same as above. Style: White box, thin black border, left-aligned layout. Layer 4: Stage Goals and Key Technologies Illustration Left Half - Stage Goal Box: Text: [Stage Goal] Reveal the intrinsic physical mechanism and establish a theoretical model of the "structure-property" relationship. Font Size: 15 points, white, bold. Style: Green rounded rectangle. Right Half - Key Technology/Theoretical Diagram Schematic Box: Title: Figure 1: Band Structure of A₄PbCl₆ System Content: [Place a virtual band diagram here, labeling band gap values Eg1, Eg2...]. Font Size: Figure title 12 points, virtual text in the figure 10 points. Style: Gray background box, slightly thicker border. ## Part 3: Stage 2 - Preparation Position: Immediately to the right of Stage 1, connected by the overall timeline arrow. Structure: Same as Stage 1, four layers vertically. Layer 1: Stage Title Bar Text: Stage 2: Controllable Synthesis Style: Same as before. Layer 2: Core Methods Text: [Core Methods] Modified Hot Injection Method | Re-precipitation Method | Ion Doping Style: Same as before. Layer 3: Research Content (3 boxes in parallel) Box 1: Quantum Dot Synthesis Box 2: Sb³⁺/Bi³⁺ Doped Modified Material Preparation Box 3: Structure and Spectroscopic Characterization (XRD, TEM, PL, UV-Vis), Style and Font Size: Same as Stage 1. Layer 4: Stage Goals and Key Technologies Illustration Left Half - Stage Goal Box: Text: [Stage Goal] Prepare high-purity chlorine-based nanomaterials to achieve precise band gap control. Right Half - Key Technology Illustration Box: Title: Figure 2: Process Flow Chart Content: [Virtual flow chart with steps such as "centrifugal purification"]. Style: Same as before.

Abstract Near real-time and non-destructive monitoring of wheat growth using the Leaf Area Index (LAI) is a reliable and proven method for effective agricultural management. However, challenges arise when dealing with high-dimensional data and capturing nonlinear variables using conventional methods. This study utilized three models–Bidirectional Long Short-Term Memory (Bi-LSTM), Deep Neural Network (DNN), and Random Forest (RF) to handle an array of variables. Key variables include VIS = 22, TFs = 64, initial = 86, and optimal = 26. Instruction A graphical abstract is required for this journal and should be a colorful, eye-catching image that captures the reader's attention. The abstract can be a figure from the manuscript or a mosaic of panels arranged horizontally in landscape format, with the horizontal axis three times longer than the vertical axis. Avoid using figure captions and keep labels inside the figures minimal and in large fonts.

ABSTRACT: Pavement icing presents significant safety and economic challenges, necessitating the development of effective and sustainable anti-icing technologies. This study aims to develop a novel dual-functional asphalt modifier that combines thermal regulation and hydrophobicity to actively inhibit ice formation. To achieve this, tetradecane was microencapsulated within a silica shell via interfacial polymerization to create phase change microcapsules (MPCMs). These MPCMs were then blended with polydimethylsiloxane (PDMS) to produce a composite modifier, which was incorporated into asphalt. The resulting MPCM/PDMS-modified asphalt was comprehensively characterized using thermal analysis, rheometry, fluorescence microscopy, and contact angle measurements. Key findings indicate that the composite modifier simul

Applications of Artificial Intelligence in Fixed Tooth-Supported Prosthodontics: A Systematic Review Abstract Background: Artificial intelligence is being increasingly integrated into dental practice, especially within fixed prosthodontics. Its application demonstrates potential for improving diagnostic precision, aiding clinical workflows, and enhancing the quality of dental restorations. Nevertheless, despite its increasing adoption, robust and consolidated evidence concerning its efficacy in essential prosthodontic procedures remains limited. Objective: To thoroughly assess the effectiveness of artificial intelligence-based systems in tooth-supported fixed prosthodontics, emphasizing their applications in automated crown design, margin and finish-line identification, crack detection, and the analysis of retention loss in fixed partial dentures. Methods: A systematic literature search was conducted across several databases, including PubMed, Scopus, Google Scholar, and Web of

Electrolytic Refining of Copper: A scientific schematic diagram in 16:9 format. The visual style is a high-definition educational vector illustration, rendered as a flat 2D cross-section with subtle depth shading. The color palette includes a white (#FFFFFF) or light grey (#F5F5F5) background; metallic copper orange (#B87333) for copper metal; vibrant translucent blue (#0096FF) for the electrolyte; dark grey/brown sludge (#4A4A4A) for impurities; and black (#000000, sans-serif font) for labels. Clarity is prioritized through a minimalist but detailed approach, ensuring clear separation of components. The scene composition features a rectangular electrolytic tank made of glass or transparent plastic, filled to 75% with the blue electrolyte. Electrodes are present.

Develop a laboratory workflow diagram illustrating the migration testing of chemical substances from recycled PET (rPET) bottles into food simulants, adhering to EN 13130-1 and Commission Regulation (EU) No. 10/2011. The workflow should encompass the following sequential steps: 1. Receipt and inspection of 600 ml food-grade 100% rPET bottles. 2. Filling of bottles with a 3% (w/v) acetic acid solution as a food simulant, employing the article-filling method. 3. Sealing of bottles with Parafilm to mitigate evaporation. 4. Incubation at controlled temperatures of 20 °C, 40 °C, and 60 °C for a duration of 10 days. 5. Collection of the simulant following the designated migration period. 6. Storage of collected samples at 4 °C prior to analysis. The workflow should be presented as a clear, step-by-step flowchart, with arrows delineating the sequence of operations. Employ professional laboratory terminology and maintain a concise, academic style suitable for inclusion in a scientific thesis or journal article.

The head difference between each power station section is calculated based on high-resolution ground elevation data and the flow data of the main nodes.

A scientific schematic illustration depicting the mechanism of heavy metal immobilization and inhibition of plant uptake. The diagram is presented as a unified whole: the upper section illustrates a healthy maize plant, complete with roots, stem, and leaves; the lower section represents the soil, amended with biochar derived from the co-pyrolysis of sewage sludge and attapulgite clay. Within the soil layer, porous black biochar particles are depicted, containing layered attapulgite clay and mineral components originating from the sludge. The immobilization pathways of six heavy metals (Cu, Cr, Cd, Pb, Zn, Ni) are illustrated through mechanisms including surface complexation, ion exchange, adsorption within pores, and the formation of insoluble mineral precipitates (e.g., carbonates, phosphates, Fe/Al oxides). These processes are indicated with arrows and descriptive labels. The reduced availability of metal ions in the vicinity of the root zone is displayed. The root hairs of the maize plant absorb a diminished quantity of metals, indicated by short arrows signifying limited uptake. Within the maize root, vacuolar sequestration is symbolized.

Raw materials: Epoxy resin E-51 (epoxy value 0.51 eq/100g, industrial grade), curing agent methyltetrahydrophthalic anhydride (MTHPA, industrial grade), accelerator 2-ethyl-4-methylimidazole (EMI-2,4, analytical grade), continuous basalt fiber (diameter 13μm, tensile strength ≥3500MPa, modulus ≥90GPa), silane coupling agent KH-560 (analytical grade), anhydrous ethanol (analytical grade). Preliminary preparation: Basalt fibers were cut into 10cm short fibers, soaked in anhydrous ethanol for 30min to remove oil, dried in an 80℃ oven for 2h to remove moisture, and sealed for later use. Fiber surface modification: A single-factor variable experiment was used to optimize KH-560. The key parameters were coupling agent concentration (1%, 3%, 5%, 7% by volume), modification temperature (40℃, 60℃, 80℃), and modification time (1h, 2h, 3h). The implementation process was as follows: KH-560 ethanol solution was prepared according to the concentration and ultrasonically dispersed for 10min. The pretreated fibers were placed in the solution and stirred at 100r/min at the set temperature. After the reaction, the fibers were washed three times with anhydrous ethanol, dried in a 100℃ oven for 3h, and sealed for preservation. Characterization was performed using FT-IR to analyze functional groups, SEM to observe morphology, and a contact angle measuring instrument to test hydrophilicity/hydrophobicity. Composite material preparation: The mass ratio of epoxy resin to curing agent was 100:80, the amount of accelerator was 2% of the mass of epoxy resin, and the fiber content was 10wt%-25wt%. Orthogonal experiment L₁₆(4³) was used for process optimization. The influencing factors were fiber content (10wt%, 15wt%, 20wt%, 25wt%), curing temperature (60℃, 70℃, 80℃, 90℃), and curing time (2h, 3h, 4h, 5h). The evaluation indexes were tensile strength and impact strength. The preparation process was as follows: the materials were weighed according to the formula and mixed by stirring in a 60℃ oil bath for 30min to prepare the resin matrix. The modified fibers were added according to the content and mechanically stirred at 300r/min for 20min, followed by ultrasonic dispersion for 15min. The mixture was poured into a mold coated with mold release agent (150mm×100mm×4mm) and cured under 5MPa pressure in a hot press according to the set conditions. After cooling and demolding, the blank material was obtained. Tensile, impact, and bending specimens were processed according to the standards to remove burrs and defects. Performance testing: For mechanical properties, 5 specimens were tested in each group and the average value was taken. Tensile properties were tested according to GB/T1447-2005 using a universal testing machine. Impact properties were tested according to GB/T1451-2005 using a simple supported beam impact testing machine (impact energy 5J). Bending properties were tested according to GB/T1449-2005 using a bending testing machine. Microstructure analysis: SEM was used to observe fiber surface roughness and interface bonding. FT-IR was used to test the wave number from 4000-400cm⁻¹. TGA was used to test aging damage in a nitrogen atmosphere from 30-800℃. Aging resistance test: Treatment methods included thermal aging at 100℃ with time gradients of 0h, 200h, 400h, 600h, 800h, and 1000h, and hygrothermal aging at 85℃ and 85% relative humidity with the same time gradients.