[{"data":1,"prerenderedAt":21},["ShallowReactive",2],{"blog-gpt-image2-scientific-review":3},{"id":4,"title":5,"slug":6,"summary":7,"cover_image":8,"content":9,"tags":10,"status":18,"sort_order":19,"created_at":20,"updated_at":20},9,"GPT Image 2 Scientific Drawing Review: Tested Against Nano Banana 2 (12 Reusable Prompts)","gpt-image2-scientific-review","GPT Image 2 scientific drawing review with 12 reusable prompts for mechanism diagrams, graphical abstracts, TOC graphics, compared against Nano Banana 2","\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-02.webp","\u003Ch2>Introduction\u003C\u002Fh2>\n\u003Cp>Hey everyone, this is SiliconTide!\u003C\u002Fp>\n\u003Cp>This week GPT Image 2 started rolling out to a wider audience. While most reviews cover general design scenarios, we're testing something different: \u003Cstrong>scientific research scenarios\u003C\u002Fstrong>.\u003C\u002Fp>\n\u003Cp>If you've ever struggled with mechanism diagrams in BioRender, panicked over a graphical abstract deadline, or spent hours assembling workflow icons — you know the pain. I spent three days testing GPT Image 2 on \u003Cstrong>cell signaling pathways, graphical abstracts, experimental workflows, molecular structures, astrophysics, neuroscience, academic posters, TOC graphics, and scientific infographics\u003C\u002Fstrong>. Then I pitted it against Nano Banana 2.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Bottom line:\u003C\u002Fstrong> For scientific drawing, GPT Image 2 completely dominates in productivity — though Nano Banana 2 still edges ahead in design aesthetics.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Three disclaimers:\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>① The model is still in gradual rollout; availability varies.\u003Cbr\u002F>\n② All images are pure text-to-image, no image editing, single pass.\u003Cbr\u002F>\n③ Molecular pathway structures are \u003Cstrong>visual illustrations only\u003C\u002Fstrong> — do not submit them as-is. Always verify with domain experts.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 01 — Mechanism Pathway\u003C\u002Fh2>\n\u003Ch3>🧬 Cell Signaling Pathway\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-02.webp\" alt=\"Cell Signaling Pathway - Autophagy mTOR-ULK1\" \u002F>\u003C\u002Ffigure>\n\u003Cp>The hardest category in scientific illustration — requiring chemical structures, spatial relationships, standard annotations, and signal arrows.\u003C\u002Fp>\n\u003Cpre>\u003Ccode>A Science\u002FNature-level academic mechanism diagram showing the mTOR-ULK1 signaling pathway of cellular autophagy. Light white background, whole eukaryotic cell cross-section as main body, double-layer phospholipid cell membrane (light blue), highlighting key components: extracellular growth factor (GF) binding to RTK, downstream PI3K-AKT activation; AKT phosphorylation activates mTORC1 complex; mTORC1 phosphorylates ULK1 to inactivate it; under nutrient starvation, ULK1 is released and activated, initiating autophagy; downstream PI3KC3 complex, LC3 lipidation, autophagosome formation, fusion with lysosome. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Complex pathways can be drawn with mostly correct protein positions and signal directions. But protein abbreviations may have \u003Cstrong>spelling errors\u003C\u002Fstrong> (e.g., mTOR rendered as mToR). Always \u003Cstrong>manually fix the text layer\u003C\u002Fstrong> before submission.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 02 — Pharmacology Pathway\u003C\u002Fh2>\n\u003Ch3>💊 Multi-Tissue Cascade Mechanism\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-03.webp\" alt=\"Multi-Tissue Cascade - GLP-1 Receptor Agonist\" \u002F>\u003C\u002Ffigure>\n\u003Cp>A \"pharmacology review\" style, three-panel illustration telling the whole-body story of a drug.\u003C\u002Fp>\n\u003Cpre>\u003Ccode>An academic review-level mechanism diagram showing multi-tissue action pathways of GLP-1 receptor agonists (e.g., Semaglutide). Horizontal three-panel composition. Left: pancreatic β-cell cross-section showing GLP-1R activation → cAMP↑ → PKA → insulin vesicle exocytosis. Center: hypothalamic arcuate nucleus neurons, POMC activated, NPY\u002FAgRP inhibited. Right: cardiovascular and liver showing inflammatory factor downregulation. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Three-panel composition is rock-solid. \"Three-tissue cascade\" narrative mechanism diagrams are GPT's comfort zone.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 03 — Submission Essential\u003C\u002Fh2>\n\u003Ch3>📑 Graphical Abstract\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-04.webp\" alt=\"Graphical Abstract - Old Model\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Old model output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-05.webp\" alt=\"Graphical Abstract - GPT Image 2\" \u002F>\u003C\u002Ffigure>\n\u003Cp>New model (GPT Image 2) output\u003C\u002Fp>\n\u003Cpre>\u003Ccode>A Cell Press-style Graphical Abstract on \"Gut microbiota metabolite TMAO accelerates atherosclerosis by activating NLRP3 inflammasome\". Horizontal 4:3, left-to-right narrative flow with 4 story nodes connected by bold arrows. 4:3 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> GPT Image 2 genuinely understands the \"flat narrative\" GA style of Cell Press \u002F Nature Communications. Main issue: small English text misspellings (e.g., Inflammasome → Inflamasome). Still need Photoshop for text fixes.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 04 — Methodology\u003C\u002Fh2>\n\u003Ch3>🔬 Experimental Workflow Schematic\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-06.webp\" alt=\"Workflow - Old Model\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Old model output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-07.webp\" alt=\"Workflow - GPT Image 2\" \u002F>\u003C\u002Ffigure>\n\u003Cp>New model (GPT Image 2) output\u003C\u002Fp>\n\u003Cpre>\u003Ccode>An Experimental Workflow Schematic showing \"single-cell RNA-seq (10x Genomics) complete pipeline\". Horizontal 16:9, 5-step horizontal pipeline layout. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> \"5-step horizontal pipeline\" is AI's most stable composition, almost directly usable for lab meeting PPT.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 05 — Structural Biology\u003C\u002Fh2>\n\u003Ch3>🧫 Molecular \u002F Protein Visualization\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-08.webp\" alt=\"Molecular - Old Model\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Old model (font rendering issues)\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-09.webp\" alt=\"Molecular - GPT Image 2\" \u002F>\u003C\u002Ffigure>\n\u003Cp>New model (note the font rendering in bottom right)\u003C\u002Fp>\n\u003Cpre>\u003Ccode>A high-aesthetic molecular visualization poster on \"SARS-CoV-2 Spike Protein and ACE2 receptor binding\". Pure black background, central spike protein trimer 3D cartoon structure. PyMOL\u002FChimeraX rendering quality. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Scores about 80 — visually resembles PyMOL rendering. Fine for teaching or popular science covers; for review papers, stick with real PyMOL.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 06 — Neuroscience\u003C\u002Fh2>\n\u003Ch3>🧠 Brain Science \u002F Neuroanatomy\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-10.webp\" alt=\"Brain Science - Reward Circuit\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>A neuroscience popular-science brain region connection diagram on \"Reward Circuit and Addiction Mechanism\". Sagittal brain section, highlighted regions: VTA, NAc, PFC, Amygdala, Hippocampus. Scientific American × Kurzgesagt style. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> This one is genuinely beautiful. Brain region positions and proportions are mostly correct. Neurotransmitter labels all spelled correctly.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 07 — Astrophysics\u003C\u002Fh2>\n\u003Ch3>🌌 Black Hole and Relativistic Jets\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-11.webp\" alt=\"Black Hole - Relativistic Jets\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>A cosmology-level popular science diagram on \"black hole accretion disk and relativistic jets\". Interstellar's Gargantua + EHT aesthetic. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> The \"Interstellar black hole\" visual language is burned into its DNA. Needs almost no changes.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 08 — Long Infographic\u003C\u002Fh2>\n\u003Ch3>📊 Academic Data Long Infographic\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-12.webp\" alt=\"AlphaFold Timeline Infographic\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>A vertical academic data infographic (9:16) on \"The Decade that Folded Biology: AlphaFold 2015-2025\". Financial Times × Pudding.cool × Scientific American style. 9:16 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Information density control is genuinely strong. Suitable for WeChat article headers.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 09 — Academic Poster\u003C\u002Fh2>\n\u003Ch3>🎨 Academic Conference Poster\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-13.webp\" alt=\"Academic Conference Poster\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>An academic conference poster thumbnail simulating A0 vertical poster in 9-panel layout. 2:3 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Layout ability for posters is very strong — well-organized panels with clear information hierarchy.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 10 — Creative Direction\u003C\u002Fh2>\n\u003Ch3>🎬 Turning Research Concepts into Movie Posters\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-14.webp\" alt=\"CRISPR The Edit - Movie Poster\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>A movie poster-style scientific creative visual on \"CRISPR: The Edit\" (fictional film). Black-gold blockbuster aesthetic. Interstellar × Oppenheimer × Dune movie poster aesthetic. 2:3 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Absolutely stunning. Perfect for research group annual posters, thesis defense openings, lecture preview covers.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 11 — WeChat Cover\u003C\u002Fh2>\n\u003Ch3>📱 Popular Science WeChat Cover Image\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-15.webp\" alt=\"Popular Science WeChat Cover\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>A popular science WeChat headline cover (16:9) on hippocampus secrets. The Atlantic × Sanlian Lifeweek cover style. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Can be directly used as WeChat cover image. Chinese font rendering is a GPT Image 2 strength.\u003C\u002Fp>\n\n\u003Ch2>PROMPT 12 — TOC Graphic\u003C\u002Fh2>\n\u003Ch3>🧪 TOC Graphic (Table of Contents)\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-16.webp\" alt=\"TOC Graphic - pH-Responsive\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>An ACS Journal-style TOC Graphic. Horizontal 3.25 × 1.75 inches. Left-to-right \"before → arrow → after\" narrative. ACS TOC specifications.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch2>PROMPT 13 — Defense Slide\u003C\u002Fh2>\n\u003Ch3>🧪 PPT Defense Slide\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-17.webp\" alt=\"PPT Defense Slide\" \u002F>\u003C\u002Ffigure>\n\u003Cp>A 16:9 image in the style of an NSFC Distinguished Young Scholar defense PPT, covering graphene synthesis.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Review:\u003C\u002Fstrong> Elegant and precise.\u003C\u002Fp>\n\n\u003Ch2>7 Direct-Use Scientific Prompts\u003C\u002Fh2>\n\n\u003Ch3>01 — Life Science Review: Gut Microbiota–Epithelial Barrier–Immune Regulation\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-18.webp\" alt=\"Gut Microbiota Mechanism\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Single-panel mechanism figure. 16:9. Pure white background. Topic: Gut microbiota-derived short-chain fatty acids strengthen the intestinal epithelial barrier and tune mucosal immunity. Left-to-right narrative. Publication-grade scientific illustration. Short English labels only, max 10 labels.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>02 — Chemistry\u002FMaterials TOC: MOF Captures CO₂ → Methanol\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-19.webp\" alt=\"MOF CO2 to Methanol\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Single-panel TOC graphic. 1.85:1. Pure white. Topic: porous MOF captures CO2 and photocatalytically converts it to methanol. Simple, scholarly, professional.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>03 — Neuroscience Journal Cover: Brain Organoid\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-20.webp\" alt=\"Brain Organoid Cover\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Journal cover concept. 3:4 vertical. Self-organizing neural activity in brain organoids. Deep black to indigo gradient. Midnight + cyan + violet + amber palette. No text.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>04 — Materials Science Cover: Perovskite Solar Cell\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-21.webp\" alt=\"Perovskite Solar Cell Cover\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Journal cover concept. 3:4. Interfacial passivation in perovskite solar cells. High-end scientific 3D render. Obsidian + cobalt + amethyst + amber palette.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>05 — Medical Illustration: mRNA-LNP to Germinal Center\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-22.webp\" alt=\"mRNA-LNP Vaccination\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Explanatory medical scientific illustration. 16:9. Four-segment left-to-right flow: deltoid injection → dendritic cell uptake → lymph node germinal center → neutralizing antibodies.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>06 — AI for Science: Multimodal Pathology Foundation Model\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-23.webp\" alt=\"AI4Sci Pathology\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Publication-grade schematic. 16:9. Multimodal pathology foundation model. Clean rectangles and arrows. Steel blue + sage + muted plum palette.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>07 — Earth Science: Land-River-Ocean Carbon Continuum\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-24.webp\" alt=\"Carbon Continuum\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Panoramic scientific illustration. 3:1. Land-river-ocean carbon continuum under extreme rainfall. Scientific infographic meets landscape cross-section.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch2>Long-Description Prompt Variants\u003C\u002Fh2>\n\n\u003Ch3>01 — Interdisciplinary Research Center Cross-Section\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-25.webp\" alt=\"Research Center Cross-Section\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Ultra-wide cross-section showing one day's workflow in an interdisciplinary research center. Oatmeal, slate blue, sage, terracotta, brass palette. 3:1 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>02 — \"Journey of One Carbon Atom\" Vertical Infographic\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-26.webp\" alt=\"Journey of One Carbon Atom\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Vertical infographic: carbon atom from atmospheric CO2 through leaf, soil, river, estuary, ocean to sediment. Nature News aesthetic. 3:4 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>03 — \"A Day in a Chloroplast\" Article Illustration\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-27.webp\" alt=\"Chloroplast as Solar Factory\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Chloroplast enlarged into a spatially layered \"micro-factory\" with thylakoid stacks, ATP synthase, Calvin cycle. Editorial illustration style. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>04 — Deep-Sea Hydrothermal Vent Journal Cover\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-28.webp\" alt=\"Hydrothermal Vent Cover\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Deep-sea hydrothermal vent microbial ecosystem journal cover concept. Mysterious, precise, solemn aesthetic. 3:4 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>05 — Single-Cell Sequencing Workflow Poster\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-29.webp\" alt=\"Single-Cell Workflow\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>White-background journal tutorial-style infographic on scRNA-seq workflow from tissue to atlas. Steel blue, sage, muted plum palette. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch3>06 — Gravitational Wave Interferometer Cutaway\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-30.webp\" alt=\"Gravitational Wave Interferometer\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Engineering + physics technical cutaway of laser interferometer for gravitational-wave detection. Physics Today aesthetic. 16:9 ratio.\u003C\u002Fcode>\u003C\u002Fpre>\n\n\u003Ch2>⚔️ HEAD-TO-HEAD: Nano Banana vs GPT Image 2\u003C\u002Fh2>\n\n\u003Ch3>Test 1: \"Global Warming Data Report 2026\"\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-31.webp\" alt=\"GPT Image 2 - Warming Report\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT Image 2\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-32.webp\" alt=\"Nano Banana 2 - Warming Report\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Banana 2\u003C\u002Fp>\n\n\u003Ch3>Test 2: \"The Truth About Bubble Tea\"\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-33.webp\" alt=\"Bubble Tea Comparison\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Left: Nano Banana, Right: GPT Image 2\u003C\u002Fp>\n\n\u003Ch3>Test 3: \"SiliconTide Children's Education Brand\"\u003C\u002Fh3>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-34.webp\" alt=\"GPT Image 2 Brand\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT Image 2\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-gpt-image2-review-35.webp\" alt=\"Nano Banana Brand\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Banana Pro\u003C\u002Fp>\n\n\u003Ch3>Comparison Summary\u003C\u002Fh3>\n\u003Cp>\u003Cstrong>1. English Technical Term Small Text:\u003C\u002Fstrong> GPT Image 2 wins, but still misspells abbreviations. Always rewrite text layer in Illustrator.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>2. Chinese Typography:\u003C\u002Fstrong> GPT Image 2 is clearly stronger for long titles and serif fonts. Reached \"mostly usable without editing\" level.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>3. Structural Spatial Relationships:\u003C\u002Fstrong> Roughly tied. Nano Banana better at overall harmony; GPT better at complex pathway signal flow.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>4. Image Editing:\u003C\u002Fstrong> Nano Banana wins completely for modifying existing figures.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>5. Illustration Quality:\u003C\u002Fstrong> Nano Banana feels more natural. GPT Image 2 has chronic excessive detail enhancement.\u003C\u002Fp>\n\n\u003Ch3>Recommendations\u003C\u002Fh3>\n\u003Cp>📌 Complex mechanism pathways → \u003Cstrong>GPT Image 2\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 Graphical Abstract → \u003Cstrong>GPT Image 2\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 TOC Graphic → \u003Cstrong>GPT Image 2\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 Experimental workflows → Both work, GPT slight edge\u003Cbr\u002F>\n📌 Research WeChat covers \u002F Chinese academic posters → \u003Cstrong>GPT Image 2\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 Editing existing mechanism diagrams → \u003Cstrong>Nano Banana\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 Preserving paper figure fidelity → \u003Cstrong>Nano Banana\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 Flat popular science (Kurzgesagt style) → \u003Cstrong>Nano Banana\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 Realistic figures + experimental scenes → \u003Cstrong>Nano Banana\u003C\u002Fstrong>\u003Cbr\u002F>\n📌 Molecular 3D visualization (PyMOL-style) → Both just \"look similar\"\u003C\u002Fp>\n\n\u003Ch2>Final Thoughts\u003C\u002Fh2>\n\u003Cp>The value of AI-generated images is never about \"replacing BioRender\" — it's about giving you an inspiration starting point, enabling rapid trial and error, bringing visual material costs to near zero, and letting non-designers produce decent first drafts.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Treat it as \"a first-year grad student who can draw\"\u003C\u002Fstrong> — sometimes right, sometimes nonsense, but you save half the starting time.\u003C\u002Fp>\n\u003Cp>Copy the 12 prompts above, swap keywords, and run — from GLP-1 to SGLT-2, from AlphaFold to CRISPR, all universally applicable.\u003C\u002Fp>\n",[11,12,13,14,15,16,17],"GPT Image 2","scientific drawing","Nano Banana","prompts","mechanism diagram","graphical abstract","TOC",1,70,"2026-05-21T03:19:14.000Z",1781516709290]