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Q-CTRL: machine learning technique to pinpoint quantum errors – News – The University of Sydney

Posted: August 3, 2021 at 1:53 am

Professor Michael Biercuk is CEO of quantum tech startup Q-CTRL.

Researchers at the University of Sydney and quantum control startup Q-CTRL have announced a way to identify sources of error in quantum computers through machine learning, providing hardware developers the ability to pinpoint performance degradation with unprecedented accuracy and accelerate paths to useful quantum computers.

A joint scientific paper detailing the research, titled Quantum Oscillator Noise Spectroscopy via Displaced Cat States, has been published inPhysical Review Letters, the worlds premier physical science research journal and flagship publication of the American Physical Society (APS Physics).

Focused on reducing errors caused by environmental noise - the Achilles heel of quantum computing - the University of Sydney team developed a technique to detect the tiniest deviations from the precise conditions needed to execute quantum algorithms using trapped ion and superconducting quantum computing hardware. These are the core technologies used by world-leading industrial quantum computing efforts at IBM, Google, Honeywell, IonQ, and others.

The University team is based at the Quantum Control Laboratory led by Professor Michael Biercukin the Sydney Nanoscience Hub.

Topinpoint the source of the measured deviations, Q-CTRL scientists developed a new way to process the measurement results using custom machine-learning algorithms. In combination with Q-CTRLs existing quantum control techniques, the researchers were also able to minimise the impact of background interference in the process. This allowed easy discrimination between real noise sources that could be fixed and phantom artefacts of the measurements themselves.

Combining cutting-edge experimental techniques with machine learning has demonstrated huge advantages in the development of quantum computers, said Dr Cornelius Hempel of ETH Zurich who conducted the research while at the University of Sydney. The Q-CTRL team was able to rapidly develop a professionally engineered machine learning solution that allowed us to make sense of our data and provide a new way to see the problems in the hardware and address them.

Q-CTRL CEO Professor Biercuk said: The ability to identify and suppress sources of performance degradation in quantum hardware is critical to both basic research and industrial efforts building quantum sensors and quantum computers.

Quantum control, augmented by machine learning, has shown a pathway to make these systems practically useful and dramatically accelerate R&D timelines, he said.

The published results in a prestigious, peer-reviewed journal validate the benefit of ongoing cooperation between foundational scientific research in a university laboratory and deep-tech startups. Were thrilled to be pushing the field forward through our collaboration.

Q-CTRL was spun-out of the University of Sydney by Professor Michael Biercuk from the School of Physics. The startup builds quantum control infrastructure software for quantum technology end-users and R&D professionals across all applications.

Q-CTRL has assembled the worlds foremost team of expert quantum-control engineers, providing solutions to many of the most advanced quantum computing and sensing teams globally. Q-CTRL is funded by SquarePeg Capital, Sierra Ventures, Sequoia Capital China, Data Collective, Horizons Ventures, Main Sequence Ventures and In-Q-Tel. Q-CTRL has international headquarters in Sydney, Los Angeles, and Berlin.

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Q-CTRL: machine learning technique to pinpoint quantum errors - News - The University of Sydney

Recommendation and review posted by Ashlie Lopez

Google’s ‘time crystals’ could be the greatest scientific achievement of our lifetimes – The Next Web

Posted: August 3, 2021 at 1:53 am

Eureka! A research team featuring dozens of scientists working in partnership with Googles quantum computing labs may have created the worlds first time crystal inside a quantum computer.

This is the kind of news that makes me want to jump up and do a happy dance.

These scientists may have produced an entirely new phase of matter. Im going to do my best to explain what that means and why I personally believe this is the most important scientificbreakthrough in our lifetimes.

However, for the sake of clarity, theres two points I need to make first:

In colloquial terms, its a big screw you to Sir Isaac Newton.

Time crystals are a new phase of matter. For the sake of simplicity, lets imagine a cube of ice.

When you put a cube of ice in glass of water, youre introducing two separate entities (the ice cube and the liquid water) to each other at two different temperatures.

Everyone knows that the water will get colder (thats why we put the ice in there) and, over time, the ice will get warmer and turn into water. Eventually youll just have a glass of room-temperature water.

We call this process thermal equilibrium.

Most people are familiar with Newtons first law of motion, its the one that says an object at rest tends to stay at rest and an object inmotion tends to stay in motion.

An important side-effect of this law of physics is that it means a perpetual motion machine is classically impossible.

According to classical physics, the universe is always moving towards entropy. In other words: if we isolate an ice cube and a room-temperature glass of water from all other external forces, the water will always melt the ice cube.

The entropy (the movement towards change) of any system will always remain the same if there are no processes, and it will always increase if there are processes.

Since our universe has stars exploding, black holes sucking, and people lighting things on fire chemical processes entropy is always increasing.

Except when it comes to time crystals. Time crystals dont give a damn what Newton or anyone else thinks. Theyre lawbreakers and heart takers. They can, theoretically, maintain entropy even when theyre used in a process.

Think about a crystal youre familiar with, such as a snowflake. Snowflakes arent just beautiful because each one is unique, theyre also fascinating formations that nearly break the laws of physics themselves.

Crystalline structures form in the physical world because, for whatever fundamental scientific reason, the atoms within them want to exist in certain exact points.

Want is a really weird word to use when were talking about atoms Im certainly not implying theyre sentient but its hard to describe the tendency toward crystalline structures in abstracts such as why.

A time crystal is a new phase of matter that, simplified, would be like having a snowflake that constantly cycled back and forth between two different configurations. Its a seven-pointed lattice one moment and a ten-pointed lattice the next, or whatever.

Whats amazing about time crystals is that when they cycle back and forth between two different configurations, they dont lose or use any energy.

Time crystals can survive energy processes without falling victim to entropy. The reason theyre called time crystals is because they can have their cake and eat it too.

They can be in a state of having eaten the whole cake, and then cycle right back to a state of still having the cake and they can, theoretically, do this forever and ever.

Most importantly, they can do this inside of an isolated system. That means they can consume the cake and then magically make it reappear over and over again forever, without using any fuel or energy.

Literally everyone should care. As I wrote back in 2018, time crystals could be the miracle quantum computing needs.

Nearly every far-future tech humans can imagine, from teleportation to warp drives and from artificial food synthesizers to perpetual motion reactors capable of powering the world without burning fuels or harnessing energy, will require quantum computing systems.

Quantum computers can solve really hard problems. Unfortunately, theyre brittle. Its hard to build them, hard to maintain them, hard to get them to do anything, and even harder to interpret the results they give. This is because of something called decoherence, which works a lot like entropy.

Computer bits in the quantum world, qubits, share a funky feature of quantum mechanics that makes them act differently when observed than when theyre left alone. That sort of makes any direct measurements of qubit states (reading the computers output) difficult.

But time crystals want to be coherent. So putting them inside a quantum computer, and using them to conduct computer processes could potentially serve an incredibly important function: ensuringquantum coherence.

[Greetings Humanoids! Did you know we have a newsletter all about AI and quantum computing? You can subscribe to itright here]

No. No, no, no, no no. Dont get me wrong. This is baby steps. This is infancy research. This is Antony van Leeuwenhoek becoming the first person to use a microscope to look at a drop of water under magnification.

What Googles done, potentially, is prove that humans can manufacture time crystals. In the words of the researchers themselves:

These results establish a scalable approach to study non-equilibrium phases of matter on current quantum processors.

Basically they believe theyve proven the concept, so now its time to see what can be done with it.

Time crystals have always been theoretical. And by always, I mean: since 2012 when they were first hypothesized.

If Googles actually created time-crystals, it could accelerate the timeline for quantum computing breakthroughs from maybe never to maybe within a few decades.

At the far-fetched, super-optimistic end of things we could see the creation of a working warp drive in our lifetimes. Imagine taking a trip to Mars or the edge of our solar system, and being back home on Earth in time to catch the evening news.

And, even on the conservative end with more realistic expectations, its not hard to imagine quantum computing-based chemical and drug discovery leading to universally-effective cancer treatments.

This could be the big eureka weve all been waiting for. I cant wait to see what happens in peer-review.

If you want to know more, you can read Googles paper here. And if youre looking for a technical deep-dive into the scientific specifics of what the researchers accomplished in the lab, this piece on Quanta Magazine byNatalie Wolchover is the bees knees.

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Google's 'time crystals' could be the greatest scientific achievement of our lifetimes - The Next Web

Recommendation and review posted by Ashlie Lopez

U.S. DoE sends another $ 73 million into the future of Quantum –

Posted: August 3, 2021 at 1:53 am

The US Department of Energy (DoE), the most influential body in the way the largest supercomputers are designed and built, has been looking beyond CMOS long before the introduction of exascale systems.

Agencies have made multiple bets that quantum computing will play an important role in the future of large-scale scientific computing, whether as an accelerator of some sort or as a more general-purpose system of the future. There is. With so many projects scattered around, its difficult to maintain current totals, but at current rates, DoE will invest well over $ 1 billion in future quantum technology by the end of 2022. Its possible, and its not unreasonable to think that this doesnt include millions of dollars. Reserved to build the quantum internet.

That gambling dollar figure continues to grow with an additional $ 73 million added today.

DoE has been strong in funding quantum computing for the past few years. Over the course of five years, it has pushed $ 115 million into this area from comprehensive programs like Q-Next, splitting its funding into the quantum application and domain areas (widely referred to by DoE as Quantum Information Science or QIS). increase). The system, even if the realization of that funding could be 10 years (or more) ahead and still might not replace traditional supercomputers.

In 2019, DoE awarded more than $ 60 million for quantum computing in communications, and in January 2020 announced $ 625 million for the new quantum computing center. $ 30 million for QIS in key application areas in March of this year. It will be added to the $ 115 million Q-Next program at Argonne National Laboratory. All of this does not include DoE funding that works with NSF and other institutions and programs, in addition to the $ 73 million announced today. So perhaps its already over a billion.

This week, DoE funds new thinking and experimental and theoretical efforts to promote understanding of the quantum phenomena of systems that can be used in Quantum Information Science (QIS) and the use of quantum computing in chemistry and materials science research. Announced $ 73 million to offer .. This influx of investment 29 projects Above all, more than 3 years to new materials, cryogenic systems and algorithms.

Very few winners have focused on the application, and the majority of the funding seems to support the quantum hardware effort. This includes projects focused on creating qubits (materials, enhanced stability, all-new qubit types), fault tolerance, and error correction. Some efforts focus on quantum simulation in traditional systems.

The award spans various universities and national laboratories. The Berkeley National Lab has two awards, one group focusing on the superconducting structure of scalable quantum systems, and the other team developing f-element qubits with controllable coherence and entanglement. I am. Argonne National Laboratory also has two groups, one focusing on entanglement issues and the other focusing on quantum spin coherence of photosynthetic proteins.

Other notable programs funded include work on applications such as quantum chemistry (Emory University) and molecular dynamics / materials science (University of Southern California). There are also some award-winning teams that focus on specific programming-related challenges.

The project was selected based on a peer review under the DOE Funding Opportunity Announcement Materials and Chemical Science Research for Quantum Information Science by the Department of Basic Energy Sciences (BES) of DOE. NS DOE Science Bureaus efforts in QIS It is notified by community input and applications focused on target missions such as quantum computing, quantum simulation, quantum communication, and quantum sensing. DOEs Science Department supports 5 National QIS Research Center A diverse portfolio of research projects, including recent awards for promoting QIS in areas related to nuclear physics and fusion energy science.

Quantum science represents the next technological revolution and frontier in the information age, and the United States is at the forefront, said Energy Secretary Jennifer M. Granholm. National Labs will strengthen resilience in the face of increasing cyber threats and climate disasters, paving the way for a cleaner and safer future.

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U.S. DoE sends another $ 73 million into the future of Quantum

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U.S. DoE sends another $ 73 million into the future of Quantum -

Recommendation and review posted by Ashlie Lopez

PsiQuantum: $450 Million In Funding And $3.15 Billion Valuation – Pulse 2.0

Posted: August 3, 2021 at 1:53 am

PsiQuantum recently announced it raised $450 million in Series D funding at a $3.15 billion valuation. The funding was raised to build the worlds first commercially viable quantum computer.

The funding round was led by funds and accounts managed by BlackRock along with participation from insiders including Baillie Gifford and M12 (Microsofts venture fund) and new investors including Blackbird Ventures and Temasek. PsiQuantum has raised a total of $665 million in funding to date.

Founded in 2016, PsiQuantumw was created by some of the worlds foremost quantum computing experts who understood that a useful quantum computer required fault-tolerance and error correction, and therefore at least 1 million physical qubits.

PsiQuantum includes a growing team of world-class engineers and scientists who are working on the entire quantum computing stack from the photonic and electronic chips, through packaging and control electronics, cryogenic systems, quantum architecture, and fault tolerance, to quantum applications. In May 2020, the company had started manufacturing the silicon photonic and electronic chips that form the foundation of the Q1 system, a significant system milestone in PsiQuantums roadmap to deliver a fault-tolerant quantum computer.

Unlike other quantum computing efforts, PsiQuantum is focused on building a fault-tolerant quantumcomputer supported by a scalable and proven manufacturing process. And the company has developed a unique technology in which single photons (particles of light) are manipulated using photonic circuits which are patterned onto a silicon chip using standard semiconductor manufacturing processes.

PsiQuantum is building quantum photonic chips as well as the cryogenic electronic chips to control the qubits, using the advanced semiconductor tools in the production line of PsiQuantums manufacturing partnerGlobalFoundries.

When fault-tolerant quantum computers become available, humankind can use them to solve otherwise impossible problems. And PsiQuantum is currently working with global leaders in the healthcare, materials, electronics, financial, security, transportation, and energy sectors to identify and optimize algorithms and applications to support business readiness for the broad adoption of quantum computing.


Quantum computing is the most profoundly world-changing technology uncovered to date. It is my conviction that the way to bring this technology into reality is by using photonics. Our company was founded on the understanding that leveraging semiconductor manufacturing is the only way to deliver the million qubits that are known to be required for error correction, a prerequisite for commercially valuable quantum computing applications. This funding round is a major vote of confidence for that approach.

Jeremy OBrien, CEO and co-founder of PsiQuantum

A commercially viable, general-purpose quantum computer has the potential to create entirely new industries ready to address some the most urgent challenges we face, especially in climate, healthcare, and energy. To see this promising technology deployed within a reasonable time frame requires it to be built using a scalable manufacturing process. Silicon photonics combined with an advanced quantum architecture is the most promising approach weve seen to date.

Tony Kim, managing director at BlackRock

Investing is about backing companies with the potential to deliver transformational growth. With its uniquely scalable approach, PsiQuantum is on track to deliver the worlds first useful quantum computer and unlock a powerful new era of innovation in the process. Whether its developing better battery materials, improving carbon capture techniques, or designing life-saving drugs in a fraction of the time, quantum computing is key to solving many of the worlds most demanding challenges.

Luke Ward, investment manager at Baillie Gifford

We invested in PsiQuantum based on the strength of the companys bold vision matched by a robust, disciplined, stepwise engineering plan to achieve that goal. We are impressed by the technical progress we have seen in hardware development along with refinement of a novel quantum architecture ideally suited for photonics. PsiQuantum and Microsoft have a shared perspective on the need for a good number of logical qubits enabled by fault tolerance and error correction on 1 million-plus physical qubits when it comes to building a truly useful quantum computer.

Samir Kumar, managing director at Microsofts venture fund M12

PsiQuantum: $450 Million In Funding And $3.15 Billion Valuation - Pulse 2.0

Recommendation and review posted by Ashlie Lopez

Supercomputers are becoming another cloud service. Here’s what it means – ZDNet

Posted: August 3, 2021 at 1:53 am

These days supercomputers aren't necessarily esoteric, specialised hardware; they're made up of high-end servers that are densely interconnected and managed by software that deploys high performance computing (HPC) workloads across that hardware. Those servers can be in a data centre but they could also be in the cloud as well.

When it comes to large simulations like the computational fluid dynamics to simulate a wind tunnel processing the millions of data points needs the power of a distributed system and the software that schedules these workloads is designed for HPC systems. If you want to simulate 500 million data points and you want to do that 7,000 or 8,000 times to look at a variety of different conditions, that's going to generate about half a petabyte of data; even if a cloud virtual machine (VM) could cope with that amount of data, the compute time would take millions of hours so you need to distribute it and the tools to do that efficiently need something that looks like a supercomputer, even if it lives in a cloud data centre.

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When the latest Top 500 list came out this summer, Azure had four supercomputers in the top 30; for comparison, AWS had one entry on the list, in 41st place.

SEE: Nextcloud Hub: User tips (free PDF) (TechRepublic)

HPC users on Azure run computational fluid dynamics, weather forecasting, geoscience simulation, machine learning, financial risk analysis, modelling for silicon chip design (a popular enough workload that Azure has FX-series VMs with an architecture specifically for electronic design automation), medical research, genomics, biomedical simulations and physics simulations, as well as workloads like rendering.

They do some of that on traditional HPC hardware; Azure offers Cray XC and CS supercomputers and the UK's Met Office is getting four Cray EX systems on Azure for its new weather-forecasting supercomputer. But you can also put together a supercomputer from H and N-Series VMs (using hardware like NVidia A100 Tensor Core GPUs and Xilinx FPGAs as well as the latest Epyc 7300 CPUs) with HPC images.

One reason the Met Office picked a cloud supercomputer was the flexibility to choose whatever the best solution is in 2027. As Richard Lawrence, the Met Office IT Fellow for supercomputing.put it at the recent HPC Forum, they wanted "to spend less time buying supercomputers and more time utilizing them".

But how does Microsoft build Azure to support HPC well when the requirements can be somewhat different? "There are things that cloud generically needs that HPC doesn't, and vice versa," Andrew Jones from Microsoft's HPC team told us.

Everyone needs fast networks, everybody needs fast storage, fast processors and more memory bandwidth, but the focus on how all that is integrated together is clearly different, he says.

HPC applications need to perform at scale, which cloud is ideal for, but they need to be deployed differently in cloud infrastructure from typical cloud applications.

SEE: Google's new cloud computing tool helps you pick the greenest data centers

If you're deploying a whole series of independent VMs it makes sense to spread them out across the datacenter so that they are relatively independent and resilient from each other, whereas in the HPC world you want to pack all your VMs as closest together as possible, so they have the tightest possible network connections between each other to get the best performance he explains.

Some HPC infrastructure proves very useful elsewhere. "The idea of high-performance interconnects that really drive scalable application performance and latency is a supercomputing and HPC thing," Jones notes. "It turns out it also works really well for other things like AI and some aspects of gaming and things like that."

Although high speed interconnects are enabling disaggregation in the hyperscale data centre, where you can split the memory and compute into different hardware and allocate as much as you need of each, that may not be useful for HPC even though more flexibility in allocating memory would be helpful, because it's expensive and not all the memory you allocate to a cluster will be used for every job.

"In the HPC world we are desperately trying to drag every bit of performance out of the interconnect we can and distributing stuff all over the data centre is probably not the right path to take for performance reasons. In HPC, we're normally stringing together large numbers of things that we mostly want to be as identical as possible to each other, in which case you don't get those benefits of disaggregation," he says.

What will cloud HPC look like in the future?

"HPC is a big enough player that we can influence the overall hardware architectures, so we can make sure that there are things like high memory bandwidth considerations, things like considerations for higher power processes and, therefore, cooling constraints and so on are built into those architectures," he points out.

The HPC world has tended to be fairly conservative, but that might be changing, Jones notes, which is good timing for cloud. "HPC has been relatively static in technology terms over the last however many years; all this diversity and processor choice has really only been common in the last couple of years," he says. GPUs have taken a decade to become common in HPC.

SEE: What is quantum computing? Everything you need to know about the strange world of quantum computers

The people involved in HPC have often been in the field for a while. But new people are coming into HPC who have different backgrounds; they're not all from the traditional scientific computing background.

"I think that diversity of perspectives and viewpoints coming into both the user side, and the design side will change some of the assumptions we'd always made about what was a reasonable amount of effort to focus on to get performance out of something or the willingness to try new technologies or the risk reward payoff for trying new technologies," Jone predicts.

So just as HPC means some changes for cloud infrastructure, cloud may mean big changes for HPC.

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Supercomputers are becoming another cloud service. Here's what it means - ZDNet

Recommendation and review posted by Ashlie Lopez

"Greening Biomaterials and Scaffolds Used in Regenerative Medicine – Newswise

Posted: August 3, 2021 at 1:52 am

Newswise Green manufacturing is becoming an increasingly critical process across industries, propelled by a growing awareness of the negative environmental and health impacts associated with traditional practices. In the biomaterials industry, electrospinning is a universal fabrication method used around the world to produce nano- to microscale fibrous meshes that closely resemble native tissue architecture. The process, however, has traditionally used solvents that not only are environmentally hazardous but also pose a significant barrier to industrial scale-up, clinical translation, and, ultimately, widespread use.

Researchers atColumbia Engineeringreport that they have developed a "green electrospinning" process that addresses many of the challenges to scaling up this fabrication method, from managing the environmental risks of volatile solvent storage and disposal at large volumes to meeting health and safety standards during both fabrication and implementation. The teams newstudy, published June 28, 2021, by Biofabrication, details how they have modernized the nanofiber fabrication of widely utilized biological and synthetic polymers (e.g. poly--hydroxyesters, collagen), polymer blends, and polymer-ceramic composites.

The study also underscores the superiority of green manufacturing. The groups green fibers exhibited exceptional mechanical properties and preserved growth factor bioactivity relative to traditional fiber counterparts, which is essential for drug delivery and tissue engineering applications.

Regenerative medicine is a $156 billion global industry, one that is growing exponentially. The team of researchers, led byHelen H. Lu, Percy K. and Vida L.W. Hudson Professor ofBiomedical Engineering, wanted to address the challenge of establishing scalable green manufacturing practices for biomimetic biomaterials and scaffolds used in regenerative medicine.

We think this is a paradigm shift in biofabrication, and will accelerate the translation of scalable biomaterials and biomimetic scaffolds for tissue engineering and regenerative medicine, said Lu, a leader in research on tissue interfaces, particularly the design of biomaterials and therapeutic strategies for recreating the bodys natural synchrony between tissues. Green electrospinning not only preserves the composition, chemistry, architecture, and biocompatibility of traditionally electrospun fibers, but it also improves their mechanical properties by doubling the ductility of traditional fibers without compromising yield or ultimate tensile strength. Our work provides both a more biocompatible and sustainable solution for scalable nanomaterial fabrication.

The team, which included several BME doctoral students from Lus group, Christopher Mosher PhD20 and Philip Brudnicki, as well as Theanne Schiros, an expert in eco-conscious textile synthesis who is also a research scientist at Columbia MRSEC and assistant professor at FIT, applied sustainability principles to biomaterial production, and developed a green electrospinning process by systematically testing what the FDA considers as biologically benign solvents (Q3C Class 3).

They identified acetic acid as a green solvent that exhibits low ecological impact (Sustainable Minds Life Cycle Assessment) and supports a stable electrospinning jet under routine fabrication conditions. By tuning electrospinning parameters, such as needle-plate distance and flow rate, the researchers were able to ameliorate the fabrication of research and industry-standard biomedical polymers, cutting the detrimental manufacturing impacts of the electrospinning process by three to six times.

Green electrospun materials can be used in a broad range of applications. Lus team is currently working on further innovating these materials for orthopaedic and dental applications, and expanding this eco-conscious fabrication process for scalable production of regenerative materials.

"Biofabrication has been referred to as the fourth industrial revolution' following steam engines, electrical power, and the digital age for automating mass production, noted Mosher, the studys first author. This work is an important step towards developing sustainable practices in the next generation of biomaterials manufacturing, which has become paramount amidst the global climate crisis."


The study is titled Green electrospinning for biomaterials and biofabrication.

Authors are: Christopher Z. Mosher (A), Philip A.P. Brudnickia (A), Zhengxiang Gonga (A), Hannah R. Childs (A), Sang Won Lee (A),Romare M. Antrobus (A)Elisa C. Fang (A), Theanne N. Schiros (B,C)and Helen H. Lu (A,B)

A. Biomaterials and Interface Tissue Engineering Laboratory, Department of Biomedical Engineering, Columbia University

B. Materials Research Science and Engineering Center, Columbia University

C. Science and Mathematics Department, Fashion Institute of Technology

This work was supported by the National Institutes of Health (NIH-NIAMS 1R01-AR07352901A), the New York State Stem Cell ESSC Board (NYSTEM C029551), the DoD CDMRP award (W81XWH-15- 1-0685), and the National Science Foundation Graduate Research Fellowship (DGE-1644869, CZM). The CD analysis system was supported by NIH grant 1S10OD025102-01, and TNS was supported as part of the NSF MRSEC program through Columbia in the Center for Precision Assembly of Superstratic and Superatomic Solids (DMR-1420634).

The authors declare no competing interest.

Columbia Engineering

Columbia Engineering, based in New York City, is one of the top engineering schools in the U.S. and one of the oldest in the nation. Also known as The Fu Foundation School of Engineering and Applied Science, the School expands knowledge and advances technology through the pioneering research of its more than 220 faculty, while educating undergraduate and graduate students in a collaborative environment to become leaders informed by a firm foundation in engineering. The Schools faculty are at the center of the Universitys cross-disciplinary research, contributing to the Data Science Institute, Earth Institute, Zuckerman Mind Brain Behavior Institute, Precision Medicine Initiative, and the Columbia Nano Initiative. Guided by its strategic vision, Columbia Engineering for Humanity, the School aims to translate ideas into innovations that foster a sustainable, healthy, secure, connected, and creative humanity.

"Greening Biomaterials and Scaffolds Used in Regenerative Medicine - Newswise

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