Research Highlights
Glass Transition Temperature from the Chemical Structure of Conjugated Polymers
February 7, 2023 | E. Gomez, R. Colby
The Tg demarks the transition into a brittle glassy state, making its accurate prediction for conjugated polymers crucial for the design of soft, stretchable, or flexible electronics.
Glass Sponges Inspire Mechanically Robust Lattice
February 5, 2023 | K. Bertoldi, J. Aizenberg
The predominantly deep-sea hexactinellid sponges are known for their ability to construct remarkably complex skeletons from amorphous hydrated silica. Here, using a combination of finite element simulations and mechanical tests on 3D-printed specimens of different lattice geometries, we show that the sponge’s diagonal reinforcement strategy achieves the highest buckling resistance for a given amount of material.
Machine-learning Spectral Indicators of Topology
October 1, 2022
Topological materials are promising for next-generation energy and information applications. However, the experimental determination of topology can be painstaking, with a few limitations such as limited sample types, high technical barriers, and limited sample environment.
Composition Gradient High-Throughput Polymer Libraries Enabled by Passive Mixing and Elevated Temperature
July 1, 2022 | E. Reichmanis, C. Meredith, M. Grover
High-throughput experimentation (HTE) methods are key to enabling informatics-driven workflows to accelerate discovery of high-performance multicomponent materials. Here, we designed a solution coating system able to operate at temperatures over 110 °C to deposit composition gradient polymer libraries. The methodology provides an avenue for efficiently screening multiparameter spaces of a wide range of materials relevant to today’s applications.
SrNbO3 as Transparent Conductor in the Visible and UV
June 1, 2020 | R. Engel-Herbert, V. Gopalan
It has been a long-standing challenge to find a material that combines the mutually exclusive properties of high electrical conductivity and high optical transmission in the visible, and even harder, in the ultraviolet spectrum. A new class of transparent conductors – correlated metals – was recently discovered and found suitable.
SrNbO3 as Transparent Conductor in the Visible and UV
June 1, 2020 | R. Engel-Herbert
It has been a long-standing challenge to find a material that combines the mutually exclusive properties of high electrical conductivity and high optical transmission in the visible, and even harder, in the ultraviolet spectrum. A new class of transparent conductors – correlated metals – was recently discovered and found suitable.
Stability of Excitons at Room Temperature in GaN Quantum Wells
May 1, 2019
The effects of extreme confinement on the electronic, excitonic, and radiative properties of atomically thin GaN quantum wells were studied through use of first-principles calculations
Achieving a New Generation of 3D Nanostructures in Organic Electronics
April 1, 2019
Rigid 3D polycyclic aromatic hydrocarbons (PAHs) have garnered interest due to their potential use in semiconductor applications and as models to study through-bond and through-space electronic interactions.
A Simple and Robust Approach to Reducing Contact Resistance in Organic Transistors
December 1, 2018
Contact effects limit device performance, even in the case of high-mobility semiconductors. We developed a strategy for drastically reducing contact effects: it consists in creating high work function domains at the surface of the injecting electrodes to promote channels of enhanced injection.
Data Mining for Parameters Affecting Polymorph Selection
April 1, 2018
The macroscopic properties of molecular materials can be drastically influenced by their solid-state packing arrangements, of which there can be many (e.g., polymorphism). Strategies to controllably and predictively access select polymorphs are desired, but predicting the conditions necessary to access a given polymorph is challenging with the current state of the art.
Strain at Interfaces in Organic Devices
July 1, 2017
The impact of inhomogeneous strain induced in an organic semiconductor was evaluated by virtue of the mismatch in the coefficients of thermal expansion of the consecutive layers on the transistor properties.
Extreme Quantum Confinement Heterostructures
December 1, 2016
In conventional semiconductor quantum heterostructures such as quantum wells based on GaAs or InAs that power today’s high-speed transistors in our cell phones, or the lasers in fiber-optic communication systems that carry our emails across the globe, it is necessary to precisely tune the energy of the electrons by quantum confinement
Predicting Anisotropic Performance in Thermoelectrics
Anisotropic properties yield anisotropic thermoelectric performance. Heat maps show lattice thermal conductivity (kL), mobility (uH) and ultimate thermoelectric performance (b)
Super-slick Coatings: Data Driven Design to Application
(Top left) Slices of a machine learning model designed to capture self-assembly of molecular monolayers on perovskite surfaces. (Top right) Photograph of a superslick surface comprising ZnO tetrapods functionalized with a molecular monolayer. (Lower) Lacy Douglas, Bill Tolar, Erick Braham, and Sarbajit Banerjee at I-corps Kick-off in Chicago.
Emergent Network of Narrow Transport Channels
(a) Crystal structure of 1T-TiSe2 with Pt substituting for Ti; (b) temperature-dependent transport, STM showing topography (c) and spectroscopy (e), (d) schematic of domain walls, ARPES showing pseudogap formation at the L point.
Interpretable Molecular Models for MoS2
J. Miao, Y. Huang, H. Heinz
MoS2 is a layered material with outstanding electrical and optical properties. Here, parameters for MoS2 with record accuracy are introduced, including validation and application to explain specific binding of peptides and amino acid residues.
Crystallographic Distribution of Curvatures in Steel
How is the motion of an interface between two solid crystals related to its shape? This is a question that was impossible to address in the past because we were not able to see within solids
Predicting the Rubbery Response of Polymer Liquids
S. Milner
Our work describes how different kinds of polymer entangle. The key insight is simple to state intuitively: polymer chains entangle as often as they can, limited only by how often they can closely approach each other. We turn this deceptively simple statement into a unified scaling theory for different kinds of polymer fluids.
A New Pathway to Stable, Low-cost, Flexible Electronics
C. Risko, J. Anthony, O. Jurchescu
While progress in material and device design has been astonishing, low environmental and operational stabilities remain longstanding problems obstructing their immediate deployment in real world applications.
Machine-assisted Discovery of Polymer-enzyme Complexes for Sustained Neural Regeneration
Among the many molecules that contribute to glial scarring, chondroitin sulfate proteoglycans (CSPGs) are known to be potent inhibitors of neuronal regeneration. Chondroitinase ABC (ChABC) degrades the glycosaminoglycan (GAG) side chains of CSPGs and promotes tissue regeneration. However, ChABC is thermally unstable and loses all activity within a few hours at 37 °C.
Common Perovskite Superfluoresces at High Temperatures
F. So, K. Gundogdu
Results of this study show that the creation and manipulation of collective coherent states in hybrid perovskites can be used as the basic building blocks for quantum applications.
An AI-driven, Cloud-based, Materials Discovery Platform for Nanomaterial Structure: PDFitc
We have developed a cloud-based, AI driven, platform for nanomaterial structure determination: “PDF in the cloud” (PDFitc.org), which consists of various applications for nanostructure determination, including a ML-based classifier for discovering material symmetry from a measured dataset, a high-throughput structure screening tool for predicting the structure of a measured signal, and a data-similarity visualization tool for finding changes in a signal in a time or temperature series.
Creating Novel Magnetic Compounds with Complementary Experimental and Computational Methods
The search for new magnetic materials with high saturation magnetic polarization (Js), magnetocrystalline anisotropy (K1), and Curie temperature (Tc) is important for a wide range of applications including information and energy processing.
Color, Structure, and Rheology of a Bottlebrush Copolymer Solution
D. Guironnet, S. Rogers
A combination of high-end microscopy, rheology, and neutron scattering was used to show how the shear rate alters the structure and color of these bottlebrush polymer
Enhanced Room Temperature Infrared LEDs
V. Podolskiy, D. Wasserman
Plasmonic-enhanced emission has been moved toward practical application by the demonstration of an electrically pumped light emitting diode (LED) whose emission properties far exceed state-of-the-art.
Computationally Driven Genetically Engineered Materials
Development of protein biomaterials that are capable of self-assembly into hydrogels has potential in biomedical applications including drug delivery and tissue engineering. A two-stage architecture, called DeepFRI, has been recently developed where functional salinity is established by training its algorithm on annotated structures from PDB and SWISS-MODEL and applying weighted class activation mapping of residues that are critical to function.
Recovery of Crude Oil from Aqueous Environments
K. Wooley
A nanoscopic sugar-based magnetic hybrid material was designed that is capable of tackling environmental pollution posed by marine oil spills while minimizing potential secondary problems that may occur from microplastic contamination.
Excitons and Polarons in Organic Materials
F. Spano
In this effort, the DMREF team has developed a new theory for deciphering the features of the optical absorption spectra of conjugated polymers and organic aggregates.
A Neural Network Approach for Catalysis
A. Heyden, G. Terejanu
A neural network predictive model has been developed that combines an established additive atomic contribution-based model with the concepts of a convolutional neural network that, when extrapolating, achieves a statistically significant improvement over the previous models.
Photonic Funnels
V. Podolskiy, D. Wasserman
Efficient optical coupling between nano- and macroscale areas is strongly suppressed by the diffraction limit. This work presents a possible solution to this fundamental problem via the experimental fabrication, characterization, and comprehensive theoretical analysis of structures referred to as ‘photonic funnels’.
Enhancing the Electrocatalytic Activity of Molybdenum Disulfide
A) Illustration of the step-wise synthetic process comprising drop-casting, thermal annealing, and hydrothermal sulfidation/selenization used to grow MoS2-xSex/MoO3 nanosheets on carbon fiber paper. (B) SEM image of sample where Se:S=0.48 showing the homogeneous distribution of the nanosheets on carbon filter paper. (C) Raman spectra (514.5 nm excitation) acquired for MoS2-xSex/MoO3 samples with increasing concentration of Se. (D) Low-magnification and HRTEM images of a sample with a Se:S ratio of 0.62 illustrating the layered structure of MoS2/MoSe2. The left inset shows a SAED pattern of the chalcogenide layers.
Flexible Crystalline b-Ga2O3 Solar-blind Photodetectors
Wide bandgap (WBG) semiconductor-based solar-blind photodetectors (PDs) have attracted considerable attention as an emerging technology due to their unique spectral working region, which covers the deep ultra-violet (UV), and significant potential in many applications, such as secure data communication.
Closed-loop Design of Heterostructures for Solar Energy Conversion
Schematic illustration of CdSe/β-SnxV2O5 heterostructures that enable photocatalytic water splitting; Right: illustration of design of MxV2O5 compounds with p-block cations that yield mid-gap states.
Materials from Mathematics
Austenite/martensite interface in Cu69.5Al27Ni3.5. Zero elastic energy austenite/martensite interfaces possible under the co-factor conditions. Red is austenite and blue/green are two variants of martensite. These pictures exhibit large deformations, zero elastic energy, and perfect fitting of the phases under continuous variation of the volume fraction f.
Discovering Rare-earth-free Magnetic Materials
An open-access database is designed to facilitate machine learning.
Tuning Organic Solar Cell Domain Properties
Despite having achieved the long sought-after performance of 10% power conversion efficiency, high performance organic solar cells are still constrained to small devices fabricated by spin coating. Efforts to scale up via printing lag considerably behind, revealing an extreme sensitivity to different fabrication methods.
Machine Learning Accelerated Design and Discovery of Rare-earth Phosphates as Next Generation Environmental Barrier Coatings
Researchers from Rensselaer Polytechnic Institute synthesized single phase multiple component rare-earth phosphate as potential environmental barrier coatings of structure materials for space and aerospace application.
Designing Materials to Revolutionize Our Engineering FutureIntellectual MeritCombining Experiment and Computation to Control Doping in Thermoelectric Materials
The structural evolution along the alloy between the ordered vacancy compound Hg2GeTe4 and Cu2HgGeTe4 was quantified as this alloy space is correlated with major changes in the carrier concentration. The alloy shows strong local ordering despite four distinct cationic species (Cu, Ge, Hg, vacancies) at high concentration. Further, the results indicated that the CuHg defects are driving the carrier concentration in the Cu2xHg2−xGeTe4 alloy
Resolving Order in Ternary Semiconductors via Resonant X-ray Diffraction
M. Toney, E. Toberer
By effectively characterizing the cation site order in ZnGeP2, we have demonstrated an example of the tunability of properties in II-IV-V2 materials at nearly fixed lattice parameters—making these materials promising for integration into current technologies. This could have a beneficial impact on devices such as LEDs and solar cells.
Ultrahard WB2 Superconducts under Pressure
A unique combination of high-pressure structure and transport experiments, with crystal structure simulations has led to the discovery that ultrahard boride WB2becomes a superconductor under pressure.
Ultrahard WB2 Superconducts under Pressure
A unique combination of high-pressure structure and transport experiments, with crystal structure simulations has led to the discovery that ultrahard boride WB2becomes a superconductor under pressure.
A New Paradigm for Accessing Chemical Information
In the 1960s work began toward the personal computer – a landmark in information processing. Since then, devices to access and analyze information have become smaller, faster, cheaper, easier to use and more powerful.
Extending Reverse Engineering to Biology
In our research, we are developing novel experimental methods to characterize the redox-properties of our thin films. These characterization methods can also be extended to probe the properties of biological materials.
Enlisting Synbio for Molecular Communication
Divergent approaches to process information: •Electronics use electrons •Biology uses ions & molecules
Reconfiguring Hydrogels by Switching Crosslinks
In order for biological systems to grow, heal and adapt they must be able to dynamically reconfigure. Using biology as a model, we created a hydrogel with reversibly reconfigurable mechanical properties based on the switching between two physical crosslinking mechanisms. Specifically, we used the renewable aminopolysaccharide chitosan and switched this hydrogel between an elastic crystalline network and a viscoelastic electroastatically crosslinked network.
Elucidating Salt Effects on Chitosan Dynamics
Using molecular dynamics simulations, we explored the solution salt effect on the conformational dynamics of chitosan chains. Our data revealed that the chitosan glycosidic bonds can rotate to an extended syn and the so-called anti-Ψ conformations.
Reverse Engineering of Materials Properties
Traditional materials science approaches to characterize materials from nature or to develop new polymeric materials start by resolving chemical structure. Yet this approach fails for materials that have complex and ill-defined structures or that undergo dynamic changes as part of their function. This is the case for melanin a ubiquitous pigment in nature that is believed to offer protective antioxidant and radical scavenging properties.
Unique Properties of One-Dimensional Materials
We synthesized and investigated MoI3, a van der Waals material with a “true one-dimensional” crystal structure that can be exfoliated to individual atomic chains. Machine learning allowed to establish the existence of MoI3 with 1D crystal structure as opposed to the previously suggested 2D structure.
Data Driven Discovery of Conjugated Polyelectrolytes for Neuromorphic Computing
Dual mode transistors, the type of transistors that work in both depletion mode and enhancement mode, were reported more than 50 years ago using inorganic semiconductors, such as Silicon, but have not been shown in organic electronics
Tunable Semiconductors: Organic-inorganic Hybrids
We use high-level computational theory to demonstrate how a novel class of crystalline semiconductor materials, so-called layered hybrid organic-inorganic perovskites (HOIPs), can be designed at the atomic scale to provide targeted semiconductor properties. The tun-ability of the materials arises from the atomic-scale combination of an inorganic semi-conductor integrated with functionalized organic molecules that offer a wide range of properties.
2D Iodide-based Double Perovskite Templatedby Oligothiophene Spacer Cation
In an effort to identify lead-free 2D hybrid organic-inorganic perovskites (HOIPs), double perovskites (DPs) with mixed-valent dual metals such as Ag and Bi are attractive. Additionally, replacing chloride and bromide anions with iodide represents an important target in these systems, due to associated lower bandgaps. So far iodide 2D DPs have proven inaccessible in bulk form when using traditional spacer cations, due to intrinsic instability or formation of competing non-perovskite phases.
Resolving Stacking Disorder in Layered Peovskites
The exceptional properties of 2D hybrid organic-inorganic perovskites (HOIPs) are strongly correlated with atom-level structural details. Stacking disorder (SD) often arises in 2D HOIPs due to quasi-random stacking of inorganic and organic layers, i.e., with no long-range correlations of structural configurations. SD manifests as diffuse X-ray scattering and substantially complicates an accurate crystal structure description
Room-temperature Superfluorescence in Hybrid Perovskites
Semiconducting perovskites that exhibit superfluorescence at room temperature do so through built-in thermal “shock absorbers” which protect dipoles within the material from thermal interference.
Self-assembled Peptide-p-electron Supramolecular Polymers
Non-natural peptides containing electron-rich aromatic subunits have demonstrated the remarkable ability to spontaneously assemble into long fibers with optical and electronic responses similar to conventional silicon electronics. These molecules have the potential to serve as new biocompatible organic electronics with uses in medical interventions and clean energy.
Controlling Supramolecular Chirality in Peptide-p-peptide Networks
Synthetic peptide libraries to probe chiroptical properties.We found that carbon spacers between pi-conjugated electronic units and flanking peptide sequences had a profound impact on the superstructural chirality of the nanomaterials that form after self-assembly. The origins of this control were elucidated through computational analysis. These findings are of importance for chiroptical applications such as circularly polarized luminescence.
Discovery of Tunable Quantum Anomalous Hall Octet
Bernal bilayer graphene is a naturally occurring system with neither spin-orbit coupling nor moiré complex. •Quantum anomalous Hall (QAH) octet, i.e., eight states exhibiting quantum Hall effect at zero magnetic field, was theoretically predicted and experimentally observed.
Machine Learning-enabled Computational Discovery of Self-assembling Biocompatible Nanoaggregates
Designing Materials to Revolutionize Our Engineering FutureIntellectual MeritMachine Learning-enabled Computational Discovery of Self-assembling Biocompatible NanoaggregatesElectronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from p-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate.
Conductive Organic-inorganic Nanostructures
Dendritic structures assembled via connections between mineralizing KCl crystallites initiated by pH-triggered self-assembly of peptide materials was demonstrated. Connected structures were found to be the most important factor for producing highly conductive nanowire assemblies that showed conductivity comparable to that of a metal (~1800 S/cm). Measurements of conductivity over time and conductivity quenching by ammonia suggested the conductivity of these dendritic networks was derived from proton doping of the central π-electron units in strong acid environment and was facilitated by closely spaced chromophores leading to facile π-electron transfer along the interconnected dendritic pathways. It is expected that more electrically relevant materials may be able to be templated through this approach.
Self-assembled Peptide-p-electron Supramolecular Polymers for Bioinspired Energy Harvesting, Transport, and Management
This project integrates experiment, simulation, and data-science to engineer supramolecular optoelectronic peptidic semiconductors.
Self-assembled Peptide-p-electron Supramolecular Polymers for Bioinspired Energy Harvesting, Transport and Management
Organic electronics offer a route toward electronically active biocompatible soft materials capable of interfacing with biological and living systems. Discovering new organic molecules capable of high charge mobility is challenging due to the vast size of molecular design space and the multi-scale nature of charge transport that requires modeling electrons, molecules, and supramolecular assemblies.
Quasi 2D Perovskite Laser
The So and Gundogdu groups demonstrated a highly efficient, low threshold optically pumped perovskite laser. In quasi 2D perovskites, exciton funneling into low energy 3D domains functions as the gain medium.
Self-assembled Block Polymers with Complete Photonic Band Gaps
We have developed a workflow that allows for theoretical prediction of photonic crystals formed from bottom-up self assembly of block polymers. Using established self-consistent field theory (SCFT) methods, we are able to predict the symmetries of stable periodic structures formed at lengths scales of 10s-100s nm by such materials. Following structure prediction, photonic band structures are predicted by solving Maxwell’s equations on the resulting periodic dielectric profile.
New Topology & Tunable Superconductivity in a-Bi4I4
Given that 𝜷-Bi4I4 is the first weak topological insulator (TI) (identified by us, but not shown here), that 𝜶-Bi4I4 is a prototype higher-order TI (highlighted here), and that there is a room-temperature transition between the two structural phases (also identified by us, but not shown here), we have established a new (quasi-1D) TI paradigm that unifies the first and second order topological insulators.
Evidence of a Room-temperature Quantum Spin Hall Edge State in a Higher-order Topological Insulator
Room-temperature realization of macroscopic quantum phases is one of the major pursuits in fundamental physics. A topological insulator is a material that behaves as an insulator in its interior but whose surface contains protected conducting states.
From Insulator to Metal:Chemical Design of Electronic Transitions
We identified the relationship between local structural distortions, induced by chemical ordering of cations, and the interactions governing the electronic state (insulator or metal) of LaSrAlO4. The structure of this compound hosts a broad range of chemistries known to exhibit metal-to-insulator (MIT) transitions and will enable future materials design.
Learning from Correlations:Rare-earth Nickelates Revisited
We conducted a statistical study of the correlations between local structural distortions and critical transition temperatures of the RNiO3 family of compounds (R=rare earth). We showed gaps in scientific understanding of the reported structures of these materials known to exhibit metal-insulator and magnetic transitions and explained the discrepancies with DFT calculations.
Structure Matters: Expanding the Origin of the Insulator-metal Transition in BaCo1-xNixS2
We find that structural distortions play a pivotal role in the insulator-to-metal transition (IMT), in BaCo1-xNixS2despite the average structure remaining unchanged. We demonstrated that the Jahn-Teller (JT) effect, stemming from degenerate dxzand dyz orbitals sharing a single electron, is consistent with anomalous sulfide displacements observed in X-ray diffraction studies.
Featureless Optimization of Material Properties for Small Data Sets in Complex Ceramics
Electronic materials that exhibit phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine learning methods display limited predictive capability due to data scarcity and the absence of features that impede model training. In this work, we developed an adaptive optimization engine that overcomes these limitations
Learning Stability of AB2X6 Compounds to Guide Synthesis of Trirutile Oxides
We used machine learning and density functional theory (DFT) simulations to study crystal structure formation in the AB2X6 oxide and fluoride composition space.
Magnetoentropic Mapping of GaV4S8 and GaV4Se8
The development of next-generation spintronic devices relies in a large part on engineering subtle magnetic phase transitions which control the formation of long-wavelength spin textures.
The Synthesis Genome: Data Mining for Synthesis of New Materials
Interpretable machine-learning (ML) models were developed to predict two key solid-state synthesis conditions that must be specified for any reaction: heating temperature and heating time.
Large Anomalous Nernst Effect in a van der Waals Ferromagnet Fe3GeTe2
Anomalous Nernst effect (ANE), a result of charge current driven by temperature gradient, provides a probe of the topological nature of materials due to its sensitivity to the Berry curvature near the Fermi level. Of particular interest is the ANE in topological materials because the special band topology in these materials could introduce a very large ANE.
Charge Disproportionation and Complex Magnetism in a PbMnO3Perovskite Synthesized under High Pressure
Because of the possible crossover of Pb and 3d transition-metal (TM) redox levels, a charge transfer between Pb and TM leads to a continuous evolution from Pb2+Ti4+O3 to Pb4+Ni2+O3 in the perovskite family of PbTMO3.
Evidence for Spin Swapping in an Antiferromagnet
In the past decades, climate change and an energy crisis have prompted researchers to focus on improving the efficiency of power-saving and energy conversion devices. Thermoelectric generation is a key materials-based idea with great potential in applications.
Measurement of a Magnon Chemical Potential
For a system in equilibrium, the chemical potential of particles whose numbers are not conserved (e.g. phonons, magnons) is zero. However, for a system out-of-equilibrium, such as one where a temperature gradient is applied, there are length and time scales over which the phonon and magnon numbers are approximately conserved. For these length and time scales one may define a chemical potential for the excitations.
Double Doping of Organic Semiconducting Polymers
Molecular doping is a crucial tool for controlling the number of charge carriers in organic semiconductors, which in turn tunes the conductivity of the materials.
High Conductivity N-doped Polymers
The Marder/Silva groups have been collaborating with Jian Pei’s group at Peking University on understanding the role of dopant on the electrical and thermal conductivities of n-dopable polymers.
Controlled 3D Assembly of Graphene Sheets
A. Dobrynin, D. Adamson
Self-assembled peptide-pi-electron supramolecular polymers for bioinspired energy harvesting, transport and management
Organic electronics offer a route toward electronically active biocompatible soft materials capable of interfacing with biological and living systems. Discovering new organic molecules capable of high charge mobility is challenging due to the vast size of molecular design space and the multi-scale nature of charge transport that requires modeling electrons, molecules, and supramolecular assemblies.
Nitride Semiconductor’s Family Expanded
The group III-nitrides (Al,Ga,In)N form the basis for the white LED lighting revolution, honored with the Nobel Prize in Physics in 2014.
Data-mining our Way to Better Nanoparticle Structures
D. Hsu, S. Billinge, Q. Du
Taking inspiration from genomics based data-mining approaches, we showed how large databases of candidate structures can be generated algorithmically and then mined efficiently and robustly to screen for candidate nanoparticle structures.
Informing Zeolite Synthesis Enabled by Natural Language Processing
E. Olivetti
We have built an automated way to extract and combine body text and table information from published literature on the synthesis of zeolites, an industrially significant catalyst material. These tools are important as they move the field closer to the ability to predict and design synthesis routes for zeolites.
Hydroxide Diffusion in Anion Exchange Membranes
M. Hickner, S. Paddison, C. Bae, M. Tuckerman
The development of reliable, cost-effective polymer architectures for use as anion exchange membranes (AEMs) is an important challenge facing emerging electrochemical device technologies.
Designing the World’s Brightest Fluorescent Materials
K. Raghavachari, A. Flood
The brightest fluorescent material has been created, solving a problem that’s persisted in the field for more than a century. While fluorescent dyes are potential key components of materials needed for applications including efficient solar cells, medical diagnostics, and organic light emitting diodes (LEDs), electronic coupling between them in the solid state quenches their emission. Small-molecule Ionic Isolation Lattices (SMILES) provide a solution to this long-standing problem.
Designing Exceptional Gas-separation Membranes with Machine Learning
S. Kumar, B. Benicewicz
The field of polymer membrane design is primarily based on empirical observation, which limits discovery of new materials optimized for separating a given gas pair. Instead of relying on exhaustive experimental investigations, this team has trained a machine learning algorithm, through use of a topological, path-based hash of the polymer repeating unit.
Grain Boundary Velocity Distributions
Polycrystalline metals and ceramics are opaque to most forms of radiation. Because of this, it has not been possible to observe the motion of grain boundaries within a polycrystalline network.
MOVCD of Complex Nitride Semiconductors
A unique, custom-designed research instrument for metal-organic chemical vapor deposition (MOCVD) is enabling the synthesis and study of complex nitride semiconductors, such as ZnGeN21, and alloys and heterostructures of these materials, alone and in combination with the binary nitrides (Al,Ga,In)
Machine Learning on a Robotic Platform for the Design of Polymer-Protein Hybrids
Polymer–protein hybrids are intriguing materials that can bolster protein stability in non-native environments, thereby enhancing their utility in diverse medicinal, commercial, and industrial applications
Grain Boundary Velocity and Curvature are Not Correlated
To the eye, most common metals and ceramics used in commercial products appear to be uniformly solid. But at the microscopic level, they are polycrystalline, made up of aggregates of grains that have different sizes, shapes, and crystal orientations.
Theory-guided Discovery of New Two-dimensional Metal-Chalcogenide Alloys with Exceptional Electrocatalytic Activity
R. Mishra, A. Salehi-Khojin, R. Klie
We report the synthesis of new two-dimensional binary alloys of transition-metal dichalcogenides. Some of these alloys show outstanding performance as electrocatalyst in Li-air batteries and for the reduction of CO2.