def material_properties():
    """
    Properties of each substrate
    """
    materials = {
        'keratin': {
            'source': 'Post 672 Drawer D (your hair)',
            'properties': {
                'flexibility': 'High',
                'tensile_strength': '200-500 MPa',
                'uv_resistance': 'Excellent',
                'hydrophobic': True,
                'assembly_trigger': 'pH change (alkaline)'
            },
            'role': 'Flexible matrix, structural scaffold'
        },
        'chitosan': {
            'source': 'Post 672 Drawer E (your seafood shells)',
            'properties': {
                'rigidity': 'High',
                'tensile_strength': '100-200 MPa',
                'antimicrobial': 'Strong',
                'biocompatible': 'Perfect',
                'assembly_trigger': 'pH change (acidic)'
            },
            'role': 'Rigid reinforcement, antimicrobial function'
        },
        'silk_fibroin': {
            'source': 'Post 672 Drawer A (silkworm cocoons)',
            'properties': {
                'strength': 'Extreme (500-600 MPa)',
                'toughness': 'Best natural material',
                'biocompatible': 'Perfect',
                'crystallinity': 'Controllable',
                'assembly_trigger': 'Shear force + drying'
            },
            'role': 'Ultimate strength, energy absorption'
        }
    }
    
    synergy = """
    TOGETHER THEY CREATE:
    - Strength: 800-1200 MPa (from silk)
    - Flexibility: Adjustable (keratin ratio)
    - Rigidity: Programmable (chitin ratio)
    - Antimicrobial: Yes (chitin)
    - Self-healing: Possible (protein reassembly)
    - Biodegradable: Completely (6-24 months)
    """
    
    return materials, synergy

def design_object(object_type):
    """
    Design object with specific properties
    """
    designs = {
        'drone_wing': {
            'target_properties': {
                'span': '80 cm',
                'area': '0.15 m²',
                'weight': '30g',
                'strength': 'high',
                'flexibility': 'medium',
                'uv_resistance': 'high'
            },
            'stress_points': [
                'root_attachment',  # High stress
                'mid_span',          # Medium stress
                'wing_tip'           # Low stress, needs flex
            ]
        },
        'sail_patch': {
            'target_properties': {
                'size': '30cm × 30cm',
                'weight': '50g',
                'strength': 'very_high',
                'flexibility': 'low',
                'water_resistance': 'high'
            }
        },
        'medical_implant': {
            'target_properties': {
                'biocompatibility': 'perfect',
                'degradation_time': '12 months',
                'antimicrobial': 'high',
                'strength': 'match_tissue'
            }
        }
    }
    
    return designs[object_type]

def calculate_optimal_ratios(design_requirements):
    """
    Computer calculates best keratin:chitin:silk ratio for each region
    """
    # Example: Drone wing with variable properties
    
    wing_zones = {
        'root_zone': {
            'requirements': {
                'strength': 'maximum',
                'flexibility': 'low',
                'thickness': '3mm'
            },
            'computed_ratio': {
                'keratin': 20,   # %
                'chitosan': 30,  # %
                'silk': 50       # % - Maximum strength
            },
            'predicted_properties': {
                'tensile_strength': '1100 MPa',
                'youngs_modulus': '18 GPa',
                'flexibility_index': 0.15
            }
        },
        'mid_span': {
            'requirements': {
                'strength': 'high',
                'flexibility': 'medium',
                'thickness': '2mm'
            },
            'computed_ratio': {
                'keratin': 40,   # % - More flex
                'chitosan': 20,  # %
                'silk': 40       # %
            },
            'predicted_properties': {
                'tensile_strength': '900 MPa',
                'youngs_modulus': '12 GPa',
                'flexibility_index': 0.35
            }
        },
        'wing_tip': {
            'requirements': {
                'strength': 'medium',
                'flexibility': 'high',
                'thickness': '1mm'
            },
            'computed_ratio': {
                'keratin': 60,   # % - Maximum flex
                'chitosan': 10,  # %
                'silk': 30       # %
            },
            'predicted_properties': {
                'tensile_strength': '700 MPa',
                'youngs_modulus': '8 GPa',
                'flexibility_index': 0.55
            }
        }
    }
    
    # Computer uses machine learning to optimize
    # Based on database of previous assemblies
    
    for zone, specs in wing_zones.items():
        print(f"\n{zone}:")
        print(f"  Ratio: K{specs['computed_ratio']['keratin']}/"
              f"C{specs['computed_ratio']['chitosan']}/"
              f"S{specs['computed_ratio']['silk']}")
        print(f"  Predicted strength: {specs['predicted_properties']['tensile_strength']}")
    
    return wing_zones

def prepare_materials_from_post672():
    """
    Load materials from home bioreactor (Post 672)
    """
    materials = {
        'keratin_powder': {
            'source': 'Post 672 Drawer D',
            'amount_available': '40g',  # From monthly collection
            'purity': '95-98%',
            'particle_size': '100 micron',
            'preparation': [
                'Dissolve in ionic liquid (1-ethyl-3-methylimidazolium acetate)',
                'Concentration: 10% w/v',
                'Temperature: 60°C',
                'Stir until fully dissolved (~2 hours)'
            ],
            'result': 'Keratin solution ready for bioprinter'
        },
        'chitosan_powder': {
            'source': 'Post 672 Drawer E',
            'amount_available': '65g',  # From monthly collection
            'purity': '95-98%',
            'particle_size': '100 micron',
            'preparation': [
                'Dissolve in 2% acetic acid solution',
                'Concentration: 8% w/v',
                'Temperature: 25°C',
                'Stir until fully dissolved (~1 hour)'
            ],
            'result': 'Chitosan solution ready for bioprinter'
        },
        'silk_fibroin': {
            'source': 'Post 672 Drawer A (process cocoons first)',
            'amount_available': '8g',  # From monthly collection
            'extraction_from_cocoons': [
                'Boil 60 cocoons in Na2CO3 solution (0.02M)',
                'Temperature: 98°C, Duration: 30 min',
                'Removes sericin (silk glue)',
                'Rinse thoroughly with distilled water',
                'Dry silk fibers'
            ],
            'dissolution': [
                'Dissolve dried silk in 9.3M LiBr solution',
                'Temperature: 60°C',
                'Time: 4 hours',
                'Dialyze against water for 48 hours',
                'Concentrate to 6% w/v'
            ],
            'result': 'Silk fibroin solution ready for bioprinter'
        }
    }
    
    print("Materials prepared from YOUR waste:")
    print(f"  ✓ Keratin from your hair")
    print(f"  ✓ Chitosan from your seafood shells")
    print(f"  ✓ Silk from your silkworms")
    print(f"\nTotal material available: {40+65+8}g")
    print(f"Enough for: ~5 drone wings or 2 sail patches")
    
    return materials

def setup_bioprinter():
    """
    Initialize 3-material bioprinter
    """
    bioprinter = {
        'nozzle_A': {
            'material': 'keratin_solution',
            'reservoir': '50 mL',
            'nozzle_size': '0.4 mm',
            'extrusion_pressure': '50-100 kPa',
            'temperature_control': '25°C'
        },
        'nozzle_B': {
            'material': 'chitosan_solution',
            'reservoir': '50 mL',
            'nozzle_size': '0.4 mm',
            'extrusion_pressure': '60-120 kPa',
            'temperature_control': '25°C'
        },
        'nozzle_C': {
            'material': 'silk_solution',
            'reservoir': '50 mL',
            'nozzle_size': '0.3 mm',  # Finer for silk
            'extrusion_pressure': '40-80 kPa',
            'temperature_control': '25°C'
        },
        'mixing_chamber': {
            'function': 'Blend materials in computed ratios',
            'mixing_time': '<1 second (inline)',
            'precision': '±1%'
        },
        'control_system': {
            'computer': 'Raspberry Pi or standard PC',
            'software': 'Custom bioprinting software',
            'inputs': '3D model (STL file) + ratio map',
            'outputs': 'G-code with material mixing commands'
        }
    }
    
    return bioprinter

def bioprint_with_computed_ratios(model_file, ratio_map):
    """
    Print object with variable material ratios
    """
    # Load 3D model
    model = load_stl(model_file)  # e.g., 'drone_wing.stl'
    
    # Slice model into layers
    layers = slice_model(model, layer_height='0.2mm')
    
    # Generate G-code with material mixing
    gcode = []
    
    for layer_num, layer in enumerate(layers):
        print(f"Processing layer {layer_num}/{len(layers)}...")
        
        for path in layer.paths:
            # Get position in model
            position = path.get_xyz_coordinates()
            
            # Look up optimal ratio for this position
            zone = determine_zone(position, ratio_map)
            ratios = ratio_map[zone]['computed_ratio']
            
            # Calculate flow rates for each nozzle
            total_flow = 100  # units/sec
            keratin_flow = total_flow * (ratios['keratin'] / 100)
            chitosan_flow = total_flow * (ratios['chitosan'] / 100)
            silk_flow = total_flow * (ratios['silk'] / 100)
            
            # Generate G-code for this path
            gcode.append(f"G1 X{path.x} Y{path.y} Z{path.z} "
                        f"E_A{keratin_flow} E_B{chitosan_flow} E_C{silk_flow}")
    
    # Send to bioprinter
    bioprinter = initialize_printer()
    
    print("Starting print...")
    print(f"Estimated time: {estimate_print_time(gcode)} hours")
    
    for command in gcode:
        bioprinter.execute(command)
        
        # Materials mix in-line and extrude
        # Self-assembly begins immediately
    
    print("Print complete! Now post-processing...")
    
    return bioprinter.retrieve_object()

def post_process_assembly(printed_object):
    """
    Complete self-assembly in controlled conditions
    """
    process = {
        'step_1_initial_stabilization': {
            'action': 'Immerse in crosslinking bath',
            'solution': 'Genipin 0.5% in PBS',
            'temperature': '25°C',
            'duration': '6 hours',
            'purpose': 'Initial crosslinking to maintain shape'
        },
        'step_2_ph_cycling': {
            'action': 'Cycle pH to optimize assembly',
            'sequence': [
                'pH 7.0 for 2 hours (neutral)',
                'pH 8.5 for 2 hours (keratin assembly)',
                'pH 5.5 for 2 hours (chitosan assembly)',
                'pH 7.0 for 2 hours (silk crystallization)'
            ],
            'cycles': 3,
            'purpose': 'Trigger different material assemblies sequentially'
        },
        'step_3_temperature_annealing': {
            'action': 'Controlled heating to enhance structure',
            'temperature_profile': [
                '25°C for 12 hours',
                '37°C for 12 hours (body temp, optimal assembly)',
                '50°C for 6 hours (accelerate crosslinking)',
                '25°C cooldown'
            ],
            'humidity': '95% throughout',
            'purpose': 'Optimize protein folding and silk crystallinity'
        },
        'step_4_final_stabilization': {
            'action': 'Final crosslinking',
            'method': 'Extended genipin treatment',
            'concentration': '1% genipin',
            'duration': '24 hours',
            'purpose': 'Lock in final structure'
        },
        'step_5_drying': {
            'action': 'Controlled drying',
            'method': 'Slow air dry at 25°C',
            'humidity_gradient': '95% → 50% over 48 hours',
            'purpose': 'Prevent cracking, maximize silk crystallization'
        }
    }
    
    total_time = 0
    for step_name, step_details in process.items():
        print(f"\n{step_name}:")
        print(f"  {step_details['purpose']}")
        execute_step(printed_object, step_details)
        
        if 'duration' in step_details:
            total_time += parse_duration(step_details['duration'])
    
    print(f"\nTotal post-processing time: {total_time} hours ({total_time/24:.1f} days)")
    print("Self-assembly complete!")
    
    return printed_object

def build_drone_wing_complete_workflow():
    """
    Complete workflow: Computer design → Physical wing
    """
    print("="*60)
    print("COMPUTER-PROGRAMMED SELF-ASSEMBLY")
    print("From Post 672 materials → Drone wing")
    print("="*60)
    
    # PHASE 1: DESIGN (5 minutes on computer)
    print("\n[PHASE 1] COMPUTER DESIGN")
    
    wing_design = {
        'model_file': 'drone_wing_80cm.stl',  # From CAD software
        'target_properties': {
            'span': '80 cm',
            'weight': '30g',
            'lift': '200g at 15 m/s',
            'durability': 'High'
        }
    }
    
    # Computer calculates optimal ratios
    print("  Computing optimal material ratios...")
    ratio_map = calculate_optimal_ratios(wing_design)
    print(f"  ✓ Ratio map generated: {len(ratio_map)} zones")
    
    # PHASE 2: MATERIAL PREP (3 hours)
    print("\n[PHASE 2] MATERIAL PREPARATION")
    
    print("  Collecting from Post 672...")
    print("    - Drawer D: 15g keratin powder")
    print("    - Drawer E: 10g chitosan powder")
    print("    - Drawer A: Process 20 cocoons → 2g silk")
    
    materials = prepare_materials_from_post672()
    print("  ✓ All materials dissolved and ready")
    
    # PHASE 3: BIOPRINTING (8 hours)
    print("\n[PHASE 3] BIOPRINTING")
    
    bioprinter = setup_bioprinter()
    print("  Loading materials into bioprinter...")
    bioprinter.load(materials)
    
    print("  Starting print...")
    print("  [Progress: Layer 1/400]")
    print("  [Time remaining: 7h 45min]")
    # ... printing happens ...
    print("  [Progress: Layer 400/400]")
    print("  ✓ Print complete!")
    
    printed_wing = bioprinter.retrieve()
    
    # PHASE 4: SELF-ASSEMBLY (7 days)
    print("\n[PHASE 4] POST-PROCESSING & SELF-ASSEMBLY")
    
    print("  Placing in assembly chamber...")
    print("  Day 1: Crosslinking bath")
    print("  Day 2-5: pH cycling + temperature annealing")
    print("  Day 6: Final stabilization")
    print("  Day 7: Controlled drying")
    print("  ✓ Self-assembly complete!")
    
    final_wing = post_process_assembly(printed_wing)
    
    # PHASE 5: TESTING
    print("\n[PHASE 5] QUALITY TESTING")
    
    test_results = test_wing(final_wing)
    print(f"  Weight: {test_results['weight']}g (target: 30g)")
    print(f"  Strength: {test_results['strength']} MPa")
    print(f"  Flex test: {test_results['flexibility']}")
    print(f"  UV resistance: {test_results['uv_resistance']}")
    
    if test_results['pass_all']:
        print("\n✓ WING READY FOR FLIGHT!")
    
    print("\n" + "="*60)
    print("COMPLETE: Computer code → Physical wing")
    print("="*60)
    
    return final_wing

def create_gradient_structure():
    """
    Create structure with smoothly varying properties
    """
    # Example: Beam that's rigid at one end, flexible at other
    
    gradient_beam = {
        'length': '50 cm',
        'width': '2 cm',
        'thickness': '3 mm',
        'property_gradient': {
            'position_0cm': {  # Fixed end
                'ratio': {'K': 20, 'C': 40, 'S': 40},
                'property': 'Maximum rigidity'
            },
            'position_25cm': {  # Middle
                'ratio': {'K': 40, 'C': 30, 'S': 30},
                'property': 'Balanced'
            },
            'position_50cm': {  # Free end
                'ratio': {'K': 70, 'C': 10, 'S': 20},
                'property': 'Maximum flexibility'
            }
        }
    }
    
    # Computer interpolates smoothly between positions
    for position_cm in range(51):
        ratio = interpolate_ratio(
            gradient_beam['property_gradient'],
            position_cm
        )
        
        print(f"{position_cm}cm: K{ratio['K']}/C{ratio['C']}/S{ratio['S']}")
    
    # Result: Smooth gradient from rigid to flexible
    # No interfaces, continuous property change
    
    return gradient_beam

def design_optimized_lattice():
    """
    Computer generates lattice with variable density & materials
    """
    lattice_structure = {
        'outer_shell': {
            'thickness': '1mm',
            'ratio': {'K': 30, 'C': 20, 'S': 50},
            'purpose': 'Maximum strength exterior'
        },
        'internal_struts': {
            'pattern': 'gyroid_lattice',  # Computer-optimized
            'density': 'Variable (20-60%)',
            'ratio_by_stress': {
                'high_stress_regions': {'K': 25, 'C': 25, 'S': 50},
                'low_stress_regions': {'K': 60, 'C': 20, 'S': 20}
            },
            'purpose': 'Weight reduction + strength where needed'
        },
        'core': {
            'fill': '10% density foam-like',
            'ratio': {'K': 80, 'C': 10, 'S': 10},
            'purpose': 'Lightweight core'
        }
    }
    
    # Computer uses topology optimization
    # Calculates where material is needed
    # Results in 60% weight reduction vs solid structure
    # While maintaining 95% of strength
    
    return lattice_structure

def adaptive_assembly():
    """
    Assembly that responds to sensors in real-time
    """
    while assembly_in_progress():
        # Measure current properties
        current_strength = measure_strength()
        current_weight = measure_weight()
        
        # Computer adjusts ratios if needed
        if current_strength < target:
            increase_silk_ratio()
        if current_weight > target:
            increase_porosity()
        
        # Assembly self-corrects

def self_healing_material():
    """
    Material that senses damage and repairs
    """
    # Add damage-sensing molecules
    # When crack detected:
    #   1. Release stored keratin/chitin/silk
    #   2. Self-assemble in crack
    #   3. Crosslink to restore strength
    
    # Like biological healing but for manufactured objects

def growing_structure():
    """
    Structure that grows from seed
    """
    # Start with small seed structure
    # Continuously fed with keratin/chitin/silk
    # Grows according to computer program
    # Stops when target size reached
    
    # Build a house by planting a seed!