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At least 1,153 records · Page 64

Emerging materials intelligence ecosystems propelled by machine learning

We report that the age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its successes and promises, several AI ecosystems are blossoming, many of them within the domain of materials science and engineering. These materials intelligence ecosystems are being shaped by several independent developments. Machine learning (ML) algorithms and extant materials data are utilized to create surrogate models of materials properties and performance predictions. Materials data repositories, which fuel such surrogate model development, are mushrooming. Automated data and knowledge capture from the literature (to populate data repositories) using natural language processing approaches is being explored. The design of materials that meet target property requirements and of synthesis steps to create target materials appear to be within reach, either by closed-loop active-learning strategies or by inverting the prediction pipeline using advanced generative algorithms. AI and ML concepts are also transforming the computational and physical laboratory infrastructural landscapes used to create materials data in the first place. Surrogate models that can outstrip physics-based simulations (on which they are trained) by several orders of magnitude in speed while preserving accuracy are being actively developed. Automation, autonomy and guided high-throughput techniques are imparting enormous efficiencies and eliminating redundancies in materials synthesis and characterization. The integration of the various parts of the burgeoning ML landscape may lead to materials-savvy digital assistants and to a human-machine partnership that could enable dramatic efficiencies, accelerated discoveries and increased productivity. Here, we review these emergent materials intelligence ecosystems and discuss the imminent challenges and opportunities. The materials research landscape is being transformed by the infusion of approaches based on machine learning. This Review discusses the emerging materials intelligence ecosystems and the potential of human-machine partnerships for fast and efficient virtual materials screening, development and discovery.

36 MATERIALS SCIENCE↗

Space-Time Quantum Information from the Entangled States of Magnetic Molecule (STI Product)

This collaborative project combines synthesis, measurement, and theory by three faculty members at the Eddleman Quantum Institute of UC Irvine to effectively investigate the quantum properties of molecules in the space, time, and frequency domains. Through synthetic chemistry, molecules are tailored for their magnetic and coherent properties. By combining femtosecond (fs) terahertz (THz) light and a continuous wave (cw) THz laser with a low temperature scanning tunneling microscope (STM), quantum phenomena are probed with simultaneous femtosecond temporal and atomic-scale spatial resolution. In particular, the invention of the quantum superposition microscope (QSM) advances quantum sensing for enhanced spectroscopy and imaging capabilities. Coupling theory to the experimental efforts offers a deeper understanding and predictive power for the molecular systems. The phenomena of superposition, entanglement, and coherence is central to quantum information science and can be realized in qubit states. Many systems can be modeled by a double-well potential in which two levels are formed in the two lowest energy states interacting with the environment and external radiation. In focusing on molecules as two-level systems, the underlying expectation is that their tunable composition and structure allows an effective parameter space to optimize their use as qubits for quantum sensing and computing. The THz radiation induces the superposition between the two states, appearing as temporal oscillations that damp in amplitude. Enhanced spectroscopy and imaging in the time and frequency domains is achieved through the extreme sensitivity of the frequency and damping of coherence of two-level systems to its environment. A single hydrogen molecule trapped in the STM tunneling gap experiences a double-well potential and absorption of THz femtosecond pulses of light creates the superposition of its two levels, appearing as damped oscillations in the light induced direct current (DC). The oscillation frequency depends sensitively on the electric field distribution of the copper nitride (Cu 2 N) surface, through the Stark effect, and associated with the different charge distributions at the copper and nitrogen sites and in between. This QSM can resolve variation in the surface electric field with 0.02 nanometer resolution. In addition, the single hydrogen molecule entaes with nearby hydrogen molecules as seen in the avoided level crossings of energy (oscillation frequency) versus the voltage across the tunneling gap. Thus, the first application of the QSM senses and images the surface electric field at the atomic scale. Results from this project advance fundamental understanding of quantum phenomena, develop novel synthesis, measurement, and theory, provide the knowledge foundation for molecule-based qubits and sensing that enable the development of the QSM and emergent technologies. This project trained researchers in quantum information science, extended knowledge in classrooms, and outreached to the community.

47 OTHER INSTRUMENTATION↗

Effect of rice husk ash-derived activator on the structural build-up of alkali activated materials

Highlights: • Filtered and unfiltered sodium silicate solutions were synthesised from RHA. • The dissolution efficiency of RHA in NaOH solution was 76.3%. • RHA-derived activator showed a structural build-up comparable to the commercial activator in AAM pastes. • The undissolved residues in the unfiltered RHA-derived activator increased the yield stress. • Comparable compressive strength and early age gel formation were observed from both commercial and RHA-derived solutions. Waste-derived sodium silicates (SSs) were synthesised from rice husk ash (RHA) to produce alkali activated materials (AAMs) using fly ash and slag as precursors. The effects of these SSs on the structural build-up were investigated by monitoring the evolution of the viscoelasticity, ultrasonic pulse waves, setting time, and infrared spectra. Two types of RHA derived SSs (filtered SS and unfiltered SS) were prepared to investigate the effect of the undissolved residue on the hardening process. The derived SS contained a large portion of monomer silicate species. The results showed that the structural build-up mechanism was comparable between the AAMs activated by the filtered SS and a commercial SS. The unfiltered SS increased the yield stress of the paste by up to 10 times. However, the residues in the unfiltered SS had insignificant impacts on the gel formation and compressive strength when using identical SiO{sub 2}/Na{sub 2}O and Na{sub 2}O/binder ratios in the mix design.

36 MATERIALS SCIENCE↗

Permanent Magnets Featuring Heavy Main Group Elements for Magnetic Anisotropy

Permanent magnets are the functional component of electric motors and generators found in numerous renewable energy applications. To improve energy conversion in such applications, we require fundamentally new magnets that generate higher magnetic flux per volume while retaining the properties conferred by rare-earth elements incorporated into current technologies. We hypothesize that by engendering a covalent interaction between two elements, we can access a new regime of magnetic materials where the two components of a magnetic moment—spin and orbital angular momentum—come from two separate atoms to form a complete magnetic moment. Our previous research utilized high-pressure conditions to discover two new candidate materials ideal for assessing this hypothesis. The first material, FeBi 2 , enables the study of an unprecedented solid state metal-metal bonding interaction. The second, MnBi 2 represents the second member of the promising Mn–Bi family known for its magnetic properties. Importantly, MnBi 2 is isostructural to FeBi 2 . Together these chemically simple but magnetically rich materials provide an elegant platform for elucidating fundamental design principals of magnetic anisotropy while inspiring the synthesis of new magnetic materials. More generally, solid-state chemistry remains a synthetic black box. To fully harness the potential of such new materials, it is vital to create a window into both the structure and the properties of our high-pressure materials. One missing area of importance to energy science is high-pressure magnetometry. To this end, we assessed the magnetic structure of these materials through two objectives: (1) we performed magnetometry measurements at high-pressures, including performing high-pressure X-ray Magnetic Circular Dichroism (XMCD) experiments on these materials that are only synthesized at high-pressure and cannot be recovered to ambient conditions and (2) we targeted the recovery of these materials using dynamic compression approaches, starting with laser shock techniques. Future directions include expanding our focus to ternary phase space, employing high-throughput computational approaches to direct our search for magnetic materials across the Periodic Table. This award was originated at Northwestern, and reopened as a new grant at MIT. This is the close out for Northwestern.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting Mission Success in Small Satellite Missions

In our global society with its increasing international competition and tighter financial resources, governments, commercial entities and other organizations are becoming critically aware of the need to ensure that space missions can be achieved on time and within budget. This has become particularly true for the National Aeronautics and Space Administration's (NASA's) Office of Space Science (OSS) which has developed their Discovery and Explorer programs to meet this need. As technologies advance, space missions are becoming smaller and more capable than their predecessors. The ability to predict the mission success of these small satellite missions is critical to the continued achievement of NASA science mission objectives. The NASA Office of Space Science, in cooperation with the NASA Langley Research Center, has implemented a process to predict the likely success of missions proposed to its Discovery and Explorer Programs. This process is becoming the basis for predicting mission success in many other NASA programs as well. This paper describes the process, methodology, tools and synthesis techniques used to predict mission success for this class of mission.

Saunders, Mark↗

Predicting Mission Success in Small Satellite Missions

In our global society with its increasing international competition and tighter financial resources, governments, commercial entities and other organizations are becoming critically aware of the need to ensure that space missions can be achieved on time and within budget. This has become particularly true for the National Aeronautics and Space Administration's (NASA) Office of Space Science (OSS) which has developed their Discovery and Explorer programs to meet this need. As technologies advance, space missions are becoming smaller and more capable than their predecessors. The ability to predict the mission success of these small satellite missions is critical to the continued achievement of NASA science mission objectives. The NASA Office of Space Science, in cooperation with the NASA Langley Research Center, has implemented a process to predict the likely success of missions proposed to its Discovery and Explorer Programs. This process is becoming the basis for predicting mission success in many other NASA programs as well. This paper describes the process, methodology, tools and synthesis techniques used to predict mission success for this class of mission.

Saunders, Mark↗

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML) and silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.

Gonski, Julia [SLAC]↗

Rapid Postgrafting Reaction to Prepare Quaternized Polycarbazoles

We report a rapid postgrafting reaction to prepare alkyl ammonium functionalized polycarbazoles from a commercially available monomer. This novel synthetic approach provides benefit to preparing the high molecular weight quaternized polycarbazoles within 1 h of Friedel–Crafts polycondensation, avoiding the synthesis and purification step to prepare a functionalized monomer. The postgrafting reaction produces hexyl alkyl ammonium functionalized polycarbazole with 100% grafting degree. However, the postgrafting reaction produced only 60% grafting with propyl alkyl ammonium due to the competitive elimination reaction because of the higher acidity of β-hydrogen in the propyl alkyl group resulting from the proximity of the bromide and ammonium groups. The hexyl alkyl ammonium functionalized polycarbazole has a high hydroxide conductivity of 103 mS cm –1 at 80 °C and showed excellent alkaline stability with less than 3% loss of ion group after 1 M NaOH treatment at 80 °C for 500 h. In conclusion, this study highlights that the postgrafting reaction provides a pathway for the scale-up synthesis of quaternized aryl ether-free polyaromatics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Progress, Challenges, and Opportunities in the Synthesis, Characterization, and Application of Metal-Boride-Derived Two-Dimensional Nanostructures

Two-dimensional (2D) metal-boride-derived nanostructures have been a focus of intense research for the past decade, with an emphasis on new synthetic approaches, as well as on the exploration of possible applications in next-generation advanced materials and devices. Their unusual mechanical, electronic, optical, and chemical properties, arising from low dimensionality, present a new paradigm to the science of metal borides that has traditionally focused on their bulk properties. This Perspective discusses the current state of research on metal-boride-derived 2D nanostructures, highlights challenges that must be overcome, and identifies future opportunities to fully utilize their potential.

metals↗

On-Chip Tuning of Superconductivity in Fullerides via Current-Driven Rb + Intercalation

An in-operando electro-intercalation method for the on-chip synthesis of alkali-metal-intercalated materials and their Raman spectroscopic and transport characterization in ultrahigh vacuum (UHV) is developed. We apply this method to synthesize fulleride superconductors via Rb + intercalation into a C 60 film. During the intercalation, we monitor the stoichiometry via UHV-Raman spectroscopy and probe superconductivity via transport measurements. An increase of the superconducting transition temperature from 7.0 K to 14.5 K is observed when the stoichiometry is tuned from Rb 2.7 C 60 to Rb 3 C 60 . In our experiment, an ionic Rb+ flux into the host material is induced by an applied electronic current via a Butler–Volmer-type mechanism. Electro-intercalation captivates through improved stoichiometric precision, the ability to smoothly vary stoichiometry via duration of current application, and the absence of a lower limit of the volume of the host material. It represents a powerful concept for the on-chip synthesis of intercalated materials, battery research, and beyond.

Raman↗

Sterols are required for the coordinated assembly of lipid droplets in developing seeds

Abstract Lipid droplets (LDs) are intracellular organelles critical for energy storage and lipid metabolism. They are typically composed of an oil core coated by a monolayer of phospholipids and proteins such as oleosins. The mechanistic details of LD biogenesis remain poorly defined. However, emerging evidence suggest that their formation is a spatiotemporally regulated process, occurring at specific sites of the endoplasmic reticulum defined by a specific set of lipids and proteins. Here, we show that sterols are required for formation of oleosin-coated LDs in Arabidopsis. Analysis of sterol pathway mutants revealed that deficiency in several ∆ 5 -sterols accounts for the phenotype. Importantly, mutants deficient in these sterols also display reduced LD number, increased LD size and reduced oil content in seeds. Collectively, our data reveal a role of sterols in coordinating the synthesis of oil and oleosins and their assembly into LDs, highlighting the importance of membrane lipids in regulating LD biogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Mosaic lateral heterostructures in two-dimensional perovskite

Lateral heterostructures are important for exploring exotic physics, developing new devices and achieving device miniaturization. Endo-epitaxial growth occurring in patterned templates presents a promising strategy to realize extensive patterned areas in heterostructures, as recently demonstrated with two-dimensional (2D) covalent materials. However, the conventional lithography and etching processes used to prepare patterned templates are too aggressive for 2D lead halide perovskites, owing to their inherently soft and unstable ionic lattice. Here we create square holes of controllable size within 2D lead halide perovskites, enabling the fabrication of continuous lateral heterostructures over large areas. We demonstrate that the square holes form through spontaneous etching, a process initiated by internal strain and stabilized along the [100]/[010] crystallographic direction. Furthermore, the size of the square holes can be controlled by adjusting the etching time and temperature. Moreover, by incorporating a rapid solvent evaporation growth technique, the edges of the square holes act as templates for epitaxial growth of another type of perovskite, incorporating different halide or metal ions. Finally, we realized a series of mosaic lateral heterostructures that can emit various colours for light-emitting devices. As a result, this synthesis of diverse 2D perovskite mosaic lateral heterostructures provides valuable insights into the structural characteristics of perovskites and offers a versatile material platform for the development of complex integrated emitting devices.

Organic–inorganic nanostructures↗

Synthesis of monodisperse high entropy alloy nanocatalysts from core@shell nanoparticles

We report that high-entropy alloy (HEA) nanoparticles (NPs) hold great promise in electrocatalysis because of their nearly unlimited compositions, tailorable active sites, and high durability. However, the synthesis of these compositionally complex structures as monodisperse NPs remains a challenge by colloidal routes because the different rates of metal precursor reduction lead to phase separation. Here, we report the conversion of core@shell NPs into HEA NPs through annealing, with conservation of sample monodispersity. This potentially general route for high-quality HEA NPs was demonstrated by preparing PdCu@PtNiCo NPs via seed-mediated co-reduction, wherein Pt, Ni, and Co were co-deposited on PdCu seeds in solution. These multimetallic NPs were then converted to single-crystalline and single-phase PdCuPtNiCo NPs through annealing. On account of their small particle size, highly dispersed Pt/Pd content, and low elemental diffusivity, these HEA NPs were found to be a highly efficient and durable catalyst for the oxygen reduction reaction. They were also highly selective for the four-electron transfer pathway. We expect that this new synthetic strategy will facilitate the synthesis of new HEA NPs for catalysis and other applications.

36 MATERIALS SCIENCE↗