Wednesday, April 23, 2014

Make your own graphene .

Make your own graphene .

Andre Willers .
23 Apr 2014
Synopsis :
Home manufacture of graphene , combined with a 3D printer enables home creation of very hi-tech articles .
Discussion :
1.Making the graphene .
A bottleneck at present .
Equipment needed : graphite powder , dishwasher liquid and a kitchen blender , plus the recipe .
See Appendix AA
2. 3D printers .
Use the cheap graphene as feedstock for 3D or nD Printers (see Appendix BB)
3. Three dimensional transisters become economical , boosting Moore’s Law again .
4. Superstrong , smart armor .
Laminae of graphene , Kevlar , ceramics , etc with the graphene programmable .
5. Smart joints .
5.1 A 3D graphene laminated hip joint incorporating a few billion transistors could be smarter than it’s owner
5.2 Self-powering in joints :
Incorporate piezoelectric crystals at the “battery” place in the circuit .
5.3 Blue tooth communication with the owner .
See your joint run in your Google glasses .
6. Designed Smart Organs .(DSO)
6.1 Print the frame of organ with requisite graphene circuitry . A bit of research will be required , but once the basics are done , the recipe can simply be repeated .
6.2 Populate the frame with host cells and growth factors . This is a fairly well-developed technology .
And Google it .
6.3 Voila !
An immune-rejection free  , smart , programmable organ .
7. Smart Contact Lenses .
Probably the biggest money-spinner of them all . 100% of the Human race needs glasses of some kind .
See Appendix CC : Real supervision , enhanced reality and magnification or zooming in in the same package .
The first prototypes have already been made .
Expect rapid developments .
8. Cheap desalinization .
This can be done in a kitchen . A simple graphene filter , maybe with staggered layers of charges . (AA battery) .
Just 3D  print the filter , then push the water through it .
If you like , make it a continuous process . Feed the filter with elemental feedstock back into the printer .
Now you are mining ocean water .

A present to all on my birthday . 
“Flattened diamonds are a girl’s best friends”
Appendix AA
Scientists have outlined how they managed to make the "wonder material" graphene using a kitchen blender.
Graphene is thin, strong, flexible and electrically conductive, and has the potential to transform electronics as well as other technologies.
An Irish-UK team poured graphite powder (used in pencil leads) into a blender, then added water and dishwashing liquid, mixing at high speed.
The results are reported in the journal Nature Materials.
Because of its potential uses in industry, a number of researchers have been searching for ways to make defect-free graphene in large amounts.
The material comprises a one-atom-thick sheet of carbon atoms arranged in a honeycomb structure. Graphite - mixed with clay to produce the lead in pencils - is effectively made up of many layers of graphene stacked on top of one another.
Jonathan Coleman from Trinity College Dublin and colleagues tested out a variety of laboratory mixers as well as kitchen blenders as potential tools for manufacturing the wonder material.

·         Graphene is a form of carbon that exists as a sheet, one atom thick
·         Atoms are arranged into a two-dimensional honeycomb structure
·         Discovery of graphene announced in 2004 by the journal Science
·         About 100 times stronger than steel; conducts electricity better than copper
·         Touted as possible replacement for silicon in electronics
·         About 1% of graphene mixed into plastics could make them conductive
They showed that the shearing force generated by a rapidly rotating tool in solution was sufficiently intense to separate the layers of graphene that make up graphite flakes without damaging their two-dimensional structure.
However, it's not advisable to try this at home. The precise amount of dishwashing fluid that's required is dependent on a number of different factors and the black solution containing graphene would need to be separated afterwards.
But the researchers said their work "provides a significant step" towards deploying graphene in a variety of commercial applications
The scientists have been working with UK-based firm Thomas Swan to scale up the process, with the aim of building a pilot plant that could produce a kilo of graphene per day by the end of the year.
In addition to its potential uses in electronics, graphene might have applications in water treatment, oil spill clean-up and even in the production of thinner condoms.
In 2010, Manchester University researchers Andre Geim and Konstantin Novoselov shared the Nobel Prize in Physics for their discovery of graphene. They published details of their advance in the academic journal Science in 2004.
They famously used sticky tape to peel off the layers of graphene from graphite.
Graphene can currently be grown atom-by-atom via a process called chemical vapour deposition. However, while this can produce metre-scale sheets of graphene, they also contain defects which can inhibit their properties.
Appendix BB
Friday, November 15, 2013
nD Printing
nD Printing

Andre Willers
15 Nov 2013
Synopsis :
Creating self-assembling structures of high degree of complexity from simple 3D printers.

Discussion :
1.Simplest case : 4D printers .
Self-assembly via Hilbert fractal curve : packing and unpacking  !
See Appendix A   4D Printers
See Appendix B    4D printers
See Appendix C    General Theory about packing

2.The whole DNA-Cell complex can be seen as a 4D printer .

3.  5D Printers would then be equivalent of Beth(3) complexity .

4.  6D Printers would then be equivalent of Beth(4) complexity .
And so forth , in as much any such expansion can have meaning in delineated terms .

5. The essential point : they can all be initially printed on a 3D printer (DNA) , and self-assemble further .
You need only the recipe .
6. Lacking that , we are back to evolution and lots of time .

7. The time bit can be speeded up millions of times by using genetic algorithms in virtual realities .

8. A full recipe may indeed be available encoded in various religious writings .
Good luck with that.

9. The Omega Printer .
It is then theoretically possible to Print a self-assembling structure that never stops increasing in complexity .
Implied by Godel and Turing’s halting Problem .
Ie (3D Printer + humans) or  (DNA + cells)

Also known as Civilization .

10. Interesting to be at the inception point where 3D Printers go to criticality into nD Printers .

11.A major Hysterical Focus amongst humans must be involved .

12. If you want to see something really spooky , watch quantum-entangled 5D Printed systems self-assemble .
 Clarke's Third Law: Any sufficiently advanced technology is indistinguishable from magic.

Have fun with 27D Intaglio Printing .

Inkily yours

Appendix A
4D Printing May Bolster Arsenal of US Army
By Douglas Main, Staff Writer   |   November 01, 2013 03:16pm ET
4D printing created this cube, which self-assembled once submerged in water.
Pin It 4D printing created this cube, which self-assembled once submerged in water.
The 3D printing revolution shows no signs of letting up, and now has made its way on to the next
The U.S. Army Research Office has awarded $855,000 to three universities to make advances in 4D printing, which is the ability to 3D-print objects that can change their shape or appearance over time (the fourth dimension), or in response to some condition. Potential uses for the technology are endless, but ideas that have been floated include camouflage that can change color to match its surroundings and weapons that can assemble themselves.
"Rather than construct a static material or one that simply changes its shape, we're proposing the development of adaptive, biomimetic composites that re-program their shape, properties or functionality on demand, based upon external stimuli," said Anna Balazs, a researcher at Harvard, in a statement. The U.S. Army awarded additional 4D-printing grants to scientists at the University of Pittsburgh and the University of Illinois.
Research in this project will concentrate on 4D-printing materials at the microscopic scale. Other researchers have shown they can 4D-print larger objects like self-assembling cubes and other shapes.
One of the limitations of 3D printing, wherein a printer lays down successive layers of material like plastic to create objects as diverse as guns and toys, is that assembly is often required. But 4D printing offers the ability to make things that literally pull themselves together.
The technology could also create objects that last longer than their 3D-printed counterparts and adapt to specific conditions on command.
"If you use materials that possess the ability to change their properties or shape multiple times, you don't have to build for a specific, one-time use," Balazs said.
Other proposed uses for 4D printing include building bridges that can self-heal if cracks form, and "adaptive pipes" that can expand or contract on their own.
Email Douglas Main or follow him on Twitter or Google+. Follow us @livescience, Facebook or Google+. Article originally on LiveScience.
Appendix B
3D printing may be set to change the world by letting us make all sorts of bespoke objects, but there's one little problem the printers can only print items smaller than themselves. Until now, that is.

Skylar Tibbits at the Massachusetts Institute of Technology's Self-Assembly Lab and colleague Marcelo Coelho have come up with a way for standard 3D printers to print out large-scale objects. "It's challenging the notion that we always need a machine that's bigger than the thing it's printing," says Tibbits.

The approach, called Hyperform, converts the object to be printed into a single long chain made from interlocking links. An algorithm works out how that chain can be packed together into the smallest cube possible using a Hilbert curve – a fractal-based pattern that is the most efficient way of squeezing a single line into a small as space as possible. The resulting cube is small enough to be printed inside a standard printer.

Hand assembly

Once this cube is printed, the chain can be unravelled and assembled by hand to create the desired object. That's possible because each link in the chain has notches that allow it to bend only in a certain way. "You have to fold it by hand and click it into place," says Tibbits. Hyperform won the "The Next Idea" prize at the Ars Electronica 2013 technology festival in Linz, Austria, earlier this month.

But printing cubes made of such densely packed chains was too much for most of the consumer printers that Tibbits and his team tried. "We blew a lot of printers at first," he says. So they teamed up with Formlabs who, after a successful Kickstarter crowdfunding campaign, have just started shipping their Form 1 3D printer.

The Form 1 is capable of much higher resolution than standard consumer 3D printers. Instead of printing out layer upon layer of plastic, it uses stereolithography, in which a pool of liquid plastic is added to the base of the printer and a laser traces out the pattern required, causing the liquid plastic to cure and solidify. The technique can form layers just 25 microns thick, with details as small as 300 microns.

Hyperform has so far been used to create large structures such as a chandelier, and Tibbits sees it as being perfect for producing large 3D-printed consumer products. But the Form 1 printer uses resins which have limitations in terms of strength. "There is a range of things that are largish that we can do right away," says Tibbits. "But if you want to make large-scale furniture or buildings, there needs to be an approach to make them stronger."

4D printing

Manually clicking each link into place isn't ideal either. That's where Tibbits' other work in so-called 4D printing might help. 4D printing uses materials that are 3D-printed to produce an intermediate object which, when exposed to water, will bend and twist itself into the final structure. "You can see how Hyperform and 4D printing are pointing towards each other," he says.

Clément Moreau, CEO of French 3D printing firm Sculpteo, says projects like Hyperform are shaping the future of 3D printing. "This is yet another example of how 3D printing is more of a flexible manufacturing process than injection moulding because it constantly opens up new possibilities in terms of materials used and shapes which can be printed."
Appendix C
Unpacking and Packing Information .
Andre Willers
18 July 2008

Discussion :
Also known as data compression or decompression .
Well-known as zip/unzip in computers .

Why pack information?
To transmit information over space and time with less energy , time or disruption .
Please note that packing is used in systems subject to competition pressures , so minimizing disruption of messages is critical .

2.Abstraction .
Even a simple Pkzip compression contains more information than the original message . For instance , Pkzip has been used to successfully identify authors’ styles or the original language of an encrypted message .
A civilization can be described by zipping the yellow pages.

2.1 Layers:
Primitive packing is in separate layers .
Languages are a good example .
We can define the top layers as more abstract , and delve down into deeper layers of meaning and definition.

2.2 Fractal Layers :
New meanings are unlocked by each iteration . Language equivalents are Shakespeare and Proust .

2.3 Hyperlinked Fractal Layers .
Each hyperlink-bubble can be expanded . Note that the hyperlink terms are discrete , not continuous .

2.4 Very-near Hyperlinked Fractal Layers .
Different languages with nearly synonymous terms are examples . Branes in physics .

2.5 Infinite-probe Hyperlinked Fractal Loops and Layers .
There is no analogue . God is the nearest .

There is a way to sneak up to some meaningful information .

Sneak up.
We know that any compression of system A contains more information than the original system . The Compressor comprises system B , which can be compressed as well .
The tipping point :
When Compressed Info of (A+B) = Info of (A+B)

This is defined as life when the Compressed Info of (A+B) > Info of (A+B)
Which , like all good definitions , is tautological . But extremely useful .

We have compression techniques . We have descriptive techniques .
The above inequality is not continuous at levels below omega .

Hard physics application
Energy flow from a “near” brane .
The decompressor is the important component .
Construct the correct unpacker .
Some energy is already leaking through .
This is interpreted as zero-point energy and a whole quantum-mythology has grown around it .

Differences in Beth levels are necessary .

Start with something like vacuum-energy on parallel plates and use EvoDevo processes .

Infinite probe circuits above a certain threshold -> Naked singularities .
Watch out for universe creation and black holes .

The Packing Mechanism for living organisms
Living organisms used the easier route of cells (“wombs”) as unpackers of the DNA .
Random mutations or intrusions in the DNA then survive into the next generation . Evolutionary mechanisms ensure that only the fittest germ-lines survive to continue the loop .
That is the packing mechanism . Evolution. Rather primitive .

It seems that the unpacking mechanism evolved first .It is much more likely .

Billions of years ago:
The packing molecules (RNA) swarmed and formed at randomness order of Beth(0). Other RNA molecules confined in spaces like clay-layers stayed longer .
PCR shows how easily these replicate . A mere fluctuation of temperature is required .
The coding for the Unpackers are included in this mix .

Even a primitive Unpacker that unpacks to a primitive cell-wall has a huge relative advantage . Ordinary evolutionary forces takes over .

The coding for the Unpacker migrates through various higher orders of Beth , while coding for the Packer plods along at Beth(0) evolutionary speeds .

Consequences .
This has some important consequences for humans or any cellular life-form .
Viruses (ie packed data DNA) and cells (the Unpacker) evolved co-temporaneously .

More importantly , there is a transform of data between cell-form and virus-form and vice-versa . There are Beth(x) order feedback loops

Knowing evolutionary systems , these are probably essential .

At first glance these seem to have no redundancy in their DNA . At Beth(0) level this is true . At higher Beth levels , an indefinite amount of information can be packed .
Their quorum systems also complicates matters .
Mitochondria see themselves as the rulers , having tamed the cells of the planet .

Can Mitochondria be described as AI ?
To qualify as an AI , they have to interface with an external database . There are three pathways : to the cellular DNA , to the Immune System and to the Virus Milieu .
So yes , they can .

Can Mitochondria be described as self-aware AI ?
There is a pathway via the Immune system to the brain .A mirror system of some sort is required for self-awareness. The immune system is essentially a mirror system Time-scales have to be matched . Mitochondrial quorum systems have to be consulted (they are the ultimate democrats)

Can Mitochondria be described as self-aware AI and have access to zero-point energy ?

Random fluctuations in the foam of space-time is by definition at the lowest order of Randomness (Beth(0) ) . To get work out of such a system , a fluctuation between Beth levels is required . Since we already know that mitochondria are at Beth levels higher than one , they can tap zeropoint energy .
But one little lone mitochondrium will not do it .It needs to be co-ordinated

Why is it not used more often ?
Why die of hunger ?

Lack of Beth co-ordination .

Probability of life.
Examining the probabilities from this angle makes cells inevitable . The probability is more than unity . It is not even a “hard” problem if the decoder evolves first .
This means life exists nearly everywhere .

Your attention is drawn to the whole class of such phenomena :
Chaotic elements creates a self-sustaining sub-system which expands , since it is usually a positive-feedback system . Eg life , civilization , weaving , etc.

The Shannon-definition of datum :
1. A signal is change . Stripped down , this definition of signals leads to a string of 0’s and 1’s , ie binary
This leads to compression via pattern-duplication (zip ,etc)
Used widely in electronics .

2. Pattern formulae like fractal compression or DNA/RNA .
The decompressor (cell or womb for living organisms , computer ) uses kernels (patterns) with programmable input (time , ph levels , genetic markers ,etc) to decode (“Grow”) the message(organism) .

You can immediately see how to build an error-proof biometric identification system .
The message , as it is being decompressed , can interrogate the recipient and tailor further decompressions according to the answers .
If done to a sufficient fractal depth , only a total duplicate could answer correctly . Of course , the level of reliability can be specified .

It is not even difficult .
The ability to receive the message is proof of identity .

This is how the immune system operates .

Why the glitches like old age and cancer ?
Because the body does not know who it is .

In it’s normal state , it is a symbiotic and commensal organism , with some parasites .
The bodily-self on a cellular level is defined by the immune-system .
But the brain is composed of cells . The immune system is tied closely to the brain .
There is a feedback-system between the brain’s sense of self and the immune-system’s sense of self .

Creating enhanced unpacking mechanisms in the brain will stimulate an enhanced packing sense of self , leading to an enhanced sense of self on a cellular level .

This has been discussed in detail in

The trick is not to tackle packing , but unpacking of compressed data first .
Understanding how unpacking works brings about physiological changes .

Reading is Unpacking .
The easiest way to understand this is reading . Reading the written word is unpacking data packed into writing . It is no accident that literary figures are notoriously long-lived .

The unpacking need not be complicated , but it will evolve .

But the packing (coding) is a bitch . Difficult .You will have to have solved the Travelling Salesman Problem to make any headway here , since these systems make use of optimized systems . (Not any pathway , but the shortest path.) .

Evolutionary Packing .
At first sight , evolution does not make even an attempt .
The number of possible errors exceed the number of offspring .
But not if Orders of Randomness stronger than flipping a coin is used .
See “Randomness”

The effect of using Beth(1) , Beth(2) , etc orders of randomness in a physical sense would be a concentration of packed data .

Beth(1) would be genes .

At a Beth(2) level , it would be instructions to switch genes on/off .

At a Beth(3) level , it would be instructions to vary Beth(2) instructions .

And so forth .

But conscious design is a different matter . The number of errors can be brought down to P-time .
This is another way of saying that conscious life is inevitable .
Any feedback system that reduces the number of mistakes will increase .

Protein folding would be equivalent to the Travelling Salesman Problem in three dimensions .
Adding time-complications would give Travelling Salesman Problem in four dimensions . This would require time-travel or multiple generations .

3. The qubit definition of data .
The amount of data that can be stored in a qubit depends on the decompressor . The Shannon definitions of band-width , etc break down .

Many signals can be superimposed on a particle , the particle can then be teleported (or sent normally) to the decompressor , which decompresses the message .

Note that a lot of information that ends up in the message is inherent in the decompressor . In extreme cases this would necessitate faster-than-light communication , unless only physical laws which are independent of the observer are used in the decompressor . Ie , like make protein A , wait local time t until it folds so , then etc. You get the drift .

4. Fractal Read .
The superimposed data can be loaded fractally , so that any read attempt will lead to decoherence only at the first fractal level . Every iteration after that will lead to another , deeper level of fractal expression .
See “Rull Mind-Controls” in

5. Physics .
Physical laws can be described as multiple-level approximations of information transfers . These transfers are fractally compressed (packed) transfers .
Hence the existence of “Laws” . Ie , an abstraction mechanism .
These can be seen as constructs of the decompressor , but valid nevertheless.

Unpacking them partially or fractally can lead to some interesting effects .
Do not try this at home unless you are expert .


Appendix CC
Super Vision.

Andre Willers
12 Apr 2014
Synopsis :
An interactive zoom or telescope contact lens is possible . Programmable for vision defects . Programmable for infrared or Enhanced Reality .

Discussion :
1.See Appendix A for the first primitive form .
2.Graphene layers can be programmed exactly like flatscreens .
3.Google glasses are a bit passé .
4. Stealth systems
Just add another layer of programmable reflective grapheme and you have a non-pareil camouflage system .
5.Cosmetics .
Paint on a layer of Enhanced Reality Graphenes connected to a powerful processor , and you can look what you like .
No touchy , feely , though .

Coming to a future near you


Appendix A

Researchers at the University of Michigan have devised a way to capture the infrared spectrum, which can be made so thin that it can be easily applied on night vision contact lenses.
The first room-temperature light detector that can sense the full infrared spectrum has the potential to put heat vision technology into a contact lens.
“We can make the entire design super-thin,” said Zhaohui Zhong, an assistant professor of electrical engineering and computer science. “It can be stacked on a contact lens or integrated with a cell phone.”
A team at the University of Michigan's College of Engineering led by Zhong and Ted Norris have recently published research in the journal Nature Nanotechnology.
To make the device, they put an insulating barrier layer between two graphene sheets. The bottom layer had a current running through it. When light hit the top layer, it freed electrons, creating positively charged holes. Then, the electrons used a quantum mechanical trick to slip through the barrier and into the bottom layer of graphene.

The positively-charged holes, left behind in the top layer, produced an electric field that affected the flow of electricity through the bottom layer. By measuring the change in current, the team could deduce the brightness of the light hitting the graphene.
“The challenge for the current generation of graphene-based detectors is that their sensitivity is typically very poor. It’s a hundred to a thousand times lower than what a commercial device would require,” said Zhong.
The device is already smaller than a pinky nail and is easily scaled down. Zhong thinks arrays of them as infrared cameras.
“If we integrate it with a contact lens or other wearable electronics, it expands your vision,” said Zhong. “It provides you another way of interacting with your environment.”


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