Industrial Melanism by Neil Grayson- SOLD OUT
Doodle Labs is delighted to bring Industrial Melanism to the blockchain, a generative NFT collection inspired by Neil Grayson’s physical series of the same name. This series of 999 NFTs are created by an algorithm, carefully crafted to build upon Neil’s signature works while breaking free of the limitations of the physical world.
Neil Grayson's oil paintings are designed to be altered in appearance when lit by various light sources and seen from different angles. Press and drag the cursor (or your finger if on mobile) to brighten or darken the background and to play with the illumination of the moths. If the mouse is inactive, the lighting will slowly oscillate from light to dark over time. On desktop, hitting the spacebar or double-clicking on the image will pause the program.
To purchase an Industrial Melanism NFT please visit OpenSea
Neil Grayson is a New York city based artist working primarily in oil and metals on canvas. He is represented by Eykyn Maclean, a blue chip gallery in NYC that also represents Van Gogh, Monet, Picasso, Warhol, and more. As a teenager he was described as an “obsessive prodigy”, spending six months at the Metropolitan Museum of Art duplicating his favorite work by Rembrandt. His oil painting- nearly identical to the original- was covered in press at the time, with the Met calling it “the best copy of a master…ever seen.”
About Industrial Melanism
Since then, Neil has applied the same dedicated fastidiousness to all of his works. His Industrial Melanism series generally refers to the change in color of the peppered moth – from white with black speckles to entirely black – during the Industrial Revolution, and remains one of the clearest examples in which the evolutionary process has been observed. The light moths, formerly camouflaged on trees with white lichens, became easy prey for the birds as the trees darkened from heavy soot emissions. The darker moths – suddenly better suited to their environment – thrived, and within a human's lifetime scientists watched as the once nearly all light population became 98% dark.
Combining his fascination with Industrial Melanism with his search for (metaphorical as well as physical) light in the darkness, Grayson’s physical series explores the concepts of reinvention and transformation using the varying oxidation rates of precious metals (silver, white gold, platinum, and palladium) to create dimensionality and movement, taking advantage of the sudden changes in hue of the reflective metal surfaces creating unique visual experiences from every angle.
Turn of the Gyre (Industrial Melanism)
2017, White gold, silver, oil on canvas.
16 Birds (Industrial Melanism)
2017, Silver, palladium, white gold, oil on canvas.
Chaos (Industrial Melanism)
2016, Silver, white gold, oil on canvas.
The Generative Process
Neil has been working hand in hand with the Doodle Labs team the past few months to create the generative algorithm, or script, that produces these NFTs. The script is written in p5.js, and is stored directly on the Etherum blockchain. When you click the “live view” button on any given token, this presents a real-time rendering of your NFT artwork that is immutably preserved on-chain.
Part of the generative nature of the script is that each NFT in the series is unique, following a 1-of-1-of-X model. Each NFT is made up of a series of attributes, which are combined to create millions of potential outputs. For this project, the attribute categories include the color palette (palette), the types of metals (element), the background (foundation), the brush strokes (scumbling), the moving overlay texture (dynamic texture), the arrangement of moths (composition), and the size of moths (scale).
We have worked with Neil to add rarities into the code as well, making some attributes rarer than others. For example, platinum and palladium elements are much rarer than silver or white gold. Through lots of testing and experimentation, we have refined the code so that all of the outputs are uniquely Neil’s work, but implemented generatively via algorithm.