Plenary Session Featuring The Fred Kavli Distinguished Lectureship in Materials Science

Dario-gilDarío Gil, IBM T. J. Watson Research Center
Scaling the Scientific Method to Enter the Era of Accelerated Materials Discovery

“Right now is the most exciting time in computing in probably the last 60 years,” said Darío Gil, director of research at IBM T. J. Watson Research Center, “where we are witnessing the convergence of different ways to represent and process information.”

Gil is referring to the convergence of bits, neurons, and qubits enabled by the “cloud” programming environment with the help of artificial intelligence (AI) that changes the way problems can be solved. It is ushering us into the era of accelerated discovery. This is particularly critical for addressing global problems such as the current pandemic and climate change. 

To put this in perspective, Gil said the discovery of a new material—from the design concept to commercialization—takes about a decade, using capital of USD$10 million to USD$100 million. IBM wants to cut this effort by 90 percent.

Gil said, “We envision in the future inserting this technology [of quantum computing] to work in tandem with the AI-enriched simulation step of materials discovery loop.”

As our society is getting more and more digitalized, materials discovery in the field of semiconductors needs to accelerate significantly. IBM is aware that all of the materials going into computer chips must be as sustainable as possible. Gil focused his talk on the R&D of photoresists. Photoresists are a light-sensitive material used for forming semiconductor patterning.

Currently, photoresists carry potential toxic risks, so the research community needs to search for new photoacid generators (PAG). Gil showed step-by-step the advantages of using, first, the deep search method, which can complete complex queries on a photoacid generator—38 million edges (connections between entities or nodes that hold information that can also hold information)—in 0.1 s. This process led researchers to a PAG that was used for other applications but never tested for extreme ultra-violet (EUV) lithography.

AI-enriched simulation was then used to augment the material dataset with predicted properties. Generative modeling—a new capability in AI—accepted the information on materials properties and design constraints and filled in the gaps by generating 1000 PAG cation candidates with targeted properties. The next step is autonomous chemical synthesis in order to reduce trial and error and increase reliability and achieve scalability. This is where Cloud-based AI-driven autonomous laboratories become useful and IBM was able to show, on November 19, 2020, the first PAG material formed through this process.

Quantum computing works in tandem with AI, offering another revolution in discovery acceleration. A classical computer can be used for solving easy problems. However, for hard problems such as simulating materials, classical computers can provide only an approximation. “But there’s another technology that alters the equation between what’s possible to solve and what will be possible to solve,” said Gil, “and that is the world of quantum computers.”

IBM uses superconducting qubits, and has made its quantum computing accessible worldwide from the Cloud. In a nutshell, researchers write their programs which they send to the quantum computer that converts the 0s and 1s into microwave pulses that travel to the quantum processor. “We perform superposition, entanglement, and interference operations to perform the computation,” Gil said, then send the information back. Gil said that over 360 billion quantum circuits have been executed by quantum computers to date over the past four years with over 260k users. 

The Kavli Foundation is dedicated to advancing science for the benefit of humanity, promoting public understanding of scientific research and supporting scientists and their work.


Plenary Session Featuring The Fred Kavli Distinguished Lectureship in Materials Science

John-rogersJohn A. Rogers, Northwestern University
Functional Materials for Bioelectronic Neural Interfaces

John A. Rogers’ research has expanded from bendable, stretchable electronic systems that mount on the surface of the skin like temporary tattoos to include cellular-scale electronic/optoelectronic devices that inject into the deep brain and thin microfluidic cuffs that softly encircle the surfaces of peripheral nerves.

Much of the motivation for this work is that some medical disorders are difficult to treat with traditional pharmaceutical approaches, Rogers said, which has led to the rise of the concept of bioelectronic medicines. Addressing these disorders with various engineering platforms—such as deep brain stimulators to treat depression and Parkinson’s—is becoming possible because of the collaborations of researchers in different fields, in many cases with materials science in the lead. Rogers himself has appointments in the department of materials science and engineering, electrical and computer engineering, chemistry, biomedical engineering, mechanical engineering—and neurological surgery.

Rogers foresees a major continuing role for materials scientists, not only in systems that offer electronic interfaces but also optical, microfluidic, thermal coupling schemes, and others. In terms of functional capabilities, advances in materials for these multimodal platforms could lead to approaches in restoring or extending organ function through interfaces that include both diagnostic and therapeutic capabilities, in closed feedback loops. New approaches to patterning and processing known materials and in combining them together in unusual ways serve as additional routes for further miniaturizing implantable devices of these types, and for developing soft, stretchable platforms that more naturally interface with soft biological tissues. Related advances in materials science enable complex, extended network architectures and associated capabilities for “full 3D volumetric integration” with living organisms. Other directions include bioresorbable active and passive materials for implantable devices that function for a time period that matches a biological process such as wound healing, and then naturally disappear to remove unnecessary device load from the body without a secondary surgery.

Creating electronic materials and integrated circuits that can interface with the brain, biology’s most sophisticated electronic system, serves as an example of work in this broader area, where biocompatible semiconductors and other supporting materials must come together to support high performance operation. “Our feeling is that the ultimate solution is a hybrid one, where diverse classes of both organic and inorganic materials heterogeneously integrate into systems where the best properties of the best materials enable the highest levels of function and performance at the biotic/abiotic interface.”

This concept of hybrid electronics requires attention not only to materials but also to materials structures and materials interfaces. In his talk, Rogers showed examples of nanoscale forms of device-grade monocrystalline silicon—as nanomembranes and nanoribbons created directly from bulk wafers. He demonstrated routes for forming bulk quantities of such materials and concepts in manufacturing science that allow their deterministic assembly into layouts and formats that serve as starting points for constructing functional systems. He demonstrated how devices formed in this fashion can interface across large areas of the brain to record extended electrical processes associated with seizures, as well as responses to auditory and visual stimuli, in a range of animal models, from rodents to non-human primates. “The unmatched spatio-temporal resolution of these systems allows their use as tools to facilitate research into fundamental aspects of neuroscience,” Rogers said, “and, potentially in the future, as advanced diagnostics for various kinds of surgical operations like those used to treat chronic forms of epilepsy.”

Rogers also detailed some research that supports the use of optical forms of neuromodulation, as cellular-scale, injectable light sources that operate in a wireless fashion to turn on or off targeted neural circuits in freely behaving animal models—for studies that improve our understanding of basic processes in the brain. He believes that this broader frontier in neuroscience will rely critically on advanced neurotechnologies built upon innovation in materials science.

The Kavli Foundation is dedicated to advancing science for the benefit of humanity, promoting public understanding of scientific research and supporting scientists and their work.


Plenary Session Featuring the Fred Kavli Distinguished Lectureship in Materials Science

IMG_8542_800x800Sharon C. Glotzer, University of Michigan

Engineering Matter Across Scales

Written by Arthur L. Robinson

The ability to design and make the perfect material with just the right properties to do what we want, how we want, and when we want is the holy grail of materials research says Sharon Glotzer of the University of Michigan. Such “materials on demand” require control over thermodynamics, kinetics, nonequilibrium behavior and structure across many length and timescales. In her Fred Kavli Distinguished Lecture in Materials Science during Monday evening’s Plenary Session, Glotzer took it upon herself to demonstrate how atomic and molecular crystal structures—made possible by chemical bonds at Angstrom scales—can be realized with noninteracting nanoparticles and colloids via entropic bonds at nanometer to micron scales. Beyond their importance in understanding and engineering the self-assembly of colloidal crystals and nanoparticle superlattices, Glotzer says, the fact that some of the most complex structures in metallurgy and in molecular crystals can be realized without explicit attraction of any kind, reveals fundamental insights into what is needed to engineer matter across scales.

Physical matter is held together by chemical bonds (ionic, covalent, hydrogen, metallic, and so on). It is a combination of quantum theory, which describes interatomic interactions, and statistical thermodynamics, which governs free-energy minimization, that determine all possible crystal structures in nature. Stable crystals can be predicted if we know all the interatomic forces and can minimize the free energy subject to thermodynamic constraints. In principle, the chemical bonding structure of any set of N atoms can be computed, with varying degrees of accuracy depending on the approximations used.

Shifting to soft matter, Glotzer explains that the entities playing the role of “atoms,” being big and complex, are different. Examples are dendrimers molecular, DNA, proteins, micelles, nanoparticles, including those functionalized with ligands, and viruses. Scores of three-dimensional crystal structures can self-assemble in solution from soft-matter building blocks. Most are isostructural to atomic crystals, though with larger lattice spacings. In every case, interparticle interactions combined with thermodynamics dictate crystal morphologies.

IMG_8580_800x800

Particle shape plays a big role in dictating colloidal crystal structure because the anisotropy can create an effective “valence” that dictates the number and bond orientation of neighboring particles. Clathrates, structures consisting of polyhedral cages with large pores that can be used for host-guest chemistry, represent a challenging target for colloidal assembly. Here, particles of sizes ranging from a few nanometers to a couple of microns self-assemble in solution to form crystals where the “atoms” are replaced by particles made of atoms. Typically these particles are metals like Au or Ag, semiconductors like CdTe or CdS, or polymer like PS or PMMA, and functionalized with molecular organic ligands or DNA. The particles can be charged or neutral, be magnetic or not, spherical or rod-like or polyhedral. Particles can interact via electrostatic interactions mediated by the solvent, van der Waals interactions, magnetic dipole interactions, h-bonds between ligands, and excluded-volume interactions.  Regardless of what interactions are present, they conspire to produce net interparticle repulsion and attraction that—combined with thermodynamics—dictate the preferred arrangement of particle positions and orientations. Today these colloidal crystals can be predicted, designed, and synthesized.

Very counterintuitive, says Glotzer, is that even in the absence of any explicit interparticle interactions, colloidal particle can form crystals due solely to particle shape and excluded-volume interactions. In these cases, free energy minimization is the same thing as entropy maximization. Entropy alone can drive self-assembly of an incredible diversity of colloidal crystal structures and with extraordinary complexity, both with and without atomic or molecular analogues. Upon crowding, hard particles organize to maximize the system entropy by maximizing the number of allowed microstates. Lots of questions remain: What else is possible with entropy alone? What crystals structures are not possible with entropy alone; if not, why not? What about multi-atomic systems of shapes that are not necessarily hard? To what extent is entropy helping to order nanoparticles into colloidal crystals? Can we engineer entropy to engineer target crystals?

Finishing up, Glotzer described entropic bonding as a process that selects for the set of interparticle orientations and positions that maximizes system entropy in analogy with chemical bonding as a process that selects for the set of interatomic orientations and positions that minimizes the total energy among atoms. In this analogy, entropy creates an emergent “valence.” With an entropic analog to the Schrödinger equation based on “shape orbitals” that can be placed on a lattice and optimized for maximum overlap to find the bonding orbital and free energy of a unit cell, Glotzer and colleague Thi Vo developed a predictive microscopic theory of entropic bonding based on a pseudopotential between a quasiparticle and a hard shape. They replaced the electron probability density (wave function) in the Schrödinger equation with the quasiparticle probability density, where quasiparticles serve as a proxy for an effective entropic attraction between shapes in a Schrödinger-like equation. Applying their theory to a hard-shape system of two hard cubes in a box at a density of 0.55, they found their model predicted a simple cubic “lattice” that would have lower energy than fcc or bcc, whereas for a system of truncated tetrahedra, the preferred lattice would progress from that of a quasicrystal to diamond to -Sn to bcc as the degree of truncation increases. These predictions match those from molecular-assembly simulations made in 2012.

For takeaways, Glotzer noted that entropic forces can be directional, effect valence, and act as bonds; there is now a predictive microscopic theory of entropic bonds; and this allows the use of approaches used for atomic crystals to be used for colloidal crystals.

The Kavli Foundation is dedicated to advancing science for the benefit of humanity, promoting public understanding of scientific research and supporting scientists and their work.