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Eingabe A ist ein berühmtes Gericht (Foto oder Name des Gerichts). AnalysierenSie die vollständige Zutatenaufschlüsselung des Gerichts, die primären Geschmacksverbindungen, chemische Wechselwirkungen und die wissenschaftliche Grundlage, warum die Zutaten zusammenwirken.
OptionaleEingabe B ist eine Stilreferenz (Laborausrüstung / Tech-Produktverpackung). Falls nicht vorhanden, wählen Sie die Ästhetik des Periodensystems der Elemente trifft auf Apple-Produktdesign.
Ziel: EineDisplaytafel im Rasterformat (20"x16") inPeriodensystemstruktur, wobei jede Zutatin einem eigenen Fach mit kulinarischen und wissenschaftlichen Informationen beschriftet und nach Geschmacksprofil farbcodiert ist.
Regeln:
Rückwand aus gebürstetem Aluminium, weißem Acryl oder mattiertem Glas20-30 kleine, klare Fächer in einem Periodensystem-RasterlayoutJedesFach enthält: Zutatenspezimen, gebräuchlicher Name, wissenschaftlicher Name, primäres Geschmacksmolekül
Farbcodierte Ränder: Umami (rot), süß (rosa), sauer (gelb), bitter (grün), Fett (orange), aromatisch (lila)
Mittlerer"Legenden"-Bereich: 3D-Molekülstrukturdiagramm der charakteristischen VerbindungUntereEcke: tatsächliches handgeschriebenes Rezept auf gealtertem Pergament oder Vellum unter GlasAR-Marker zum Scannen, um animierte 3D-Molekülmodelle zu sehen
Klare serifenlose Typografie (wie Helvetica oder Futura)
MinimalistischesDesign mit viel Weißraum
Inklusive atomarer "Nummern" für jede Zutat, die das Verhältnis/die Wichtigkeit zeigen
Ausgabe: EINBild, 4:5 sauberer Produktfotografie-Stil mit weichen Schatten auf reinweißem Hintergrund
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Infografik / Edu Visual - Generator für das Periodensystem der Kulinarik als Anzeigetafel
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Ein komplexer Anweisungsprompt, der darauf ausgelegt ist, eine visuelle Darstellung des Geschmacksprofils eines Gerichts im Stil eines wissenschaftlichen Periodensystems zu erzeugen. Er erfordert die Analyse der Zutaten und Geschmacksverbindungen eines Gerichts und die anschließende Darstellung einer detaillierten Anzeigetafel mit farbcodierten Fächern, Molekularstrukturen und einem handgeschriebenen Rezept, wobei Chemie-Ästhetik mit Produktdesign kombiniert wird.
A complex, structured prompt for generating a 'Culinary Science' diorama photograph, specifically illustrating the chemistry of a food item like chocolate or caramel. The scene features an L-shaped display box, a periodic table background with samples in Petri dishes, a 1:12 scale scientist figure, and massive 3D extruded letters made of the food itself, rendered in a 'Wes Anderson' symmetry.
A complex instruction prompt designed to transform a dish (via photo or name) into a scientific, periodic table-style display board. The output is a 20"x16" grid showing the complete ingredient breakdown, color-coded by flavor profile (umami, sweet, sour, bitter, fat, aromatic), and styled with a scientific periodic table meets Apple product design aesthetic, including 3D molecular diagrams and AR markers.
A complex instructional prompt designed to generate a visual representation of a dish's flavor profile in the style of a scientific periodic table. It requires analyzing a dish's ingredients and flavor compounds, then rendering a detailed display board with color-coded compartments, molecular structures, and a handwritten recipe, combining chemistry aesthetics with product design.
A complex, multi-step instruction prompt designed to visualize a food item (defaulting to pineapple pizza) as a 'Molecular Gastronomy' acrylic display box set against a void black background. It requires breaking the food down into 'Periodic Table' style ingredients and includes a miniature scientist figure for scale, emphasizing a Dark Mode aesthetic and macro photography.
A complex, multi-phase prompt designed to generate a 2x2 grid of 'Historical Macro Dioramas' based on user-selected ingredients. It requires the AI to first determine an 'Era Texture' (Ancient, Renaissance, Industrial, Modern) and then create a hyper-detailed macro photograph of a messy workspace. Each panel features an open book with 2D sketches and a 3D pop-up diorama of a finished meal, complete with tiny period-accurate figurines of an inventor and a rival.
A creative prompt for generating an epic 3D scene where a massive broadsheet newspaper is mid-unfold, and its headlines physically erupt into miniature dioramas of the events they describe. It specifies that column text rises as city blocks and the ink smell is almost visible, aiming for an 8K photorealistic result.
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Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Authentication-derived identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Non-precise location data, Precise location data
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
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