Thank you!

While the 2022 MRS Fall Meeting & Exhibit came to conclusion with the end of The Virtual Experience on December 8th, Meeting content will be available online to registered participants through January 31, 2023.

Our congratulations go to the 2022 MRS Fall Meeting Chairs Will DichtelJulia R. GreerLaura HerzLane W. Martin, and Haimei Zheng for putting together an excellent technical program along with various special events. MRS would also like to thank all the Symposium Organizers and Session Chairs for their part in the success of this Meeting. A thank you goes to the Exhibitors, Symposium Support, and to the sponsors of the Meeting and of the special events and activities.

Contributors to news on the 2022 MRS Fall Meeting & Exhibit include Meeting Scene reporters Henry Quansah Afful, Mohamed Atwa, Rosemary Calabro, Sophia Chen, Alison Hatt, Yasir Mahmood, Judy Meiksin, Aashutosh Mistry, Don Monroe, Rahul Rao, Senam Tamakloe, and Vineeth Venugopal; bloggers Rohit Pratyush Behera and Kathy Liu; and graphic artist Stephanie Gabborin; with newsletter production by Jason Zimmerman.

Thank you for subscribing to the MRS Meeting Scene newsletters. We hope you enjoyed reading them and continue your subscription as we launch into the MRS Spring Meeting & Exhibit in 2023, the 50th anniversary of MRS. The conversation already started at #S23MRS! Also follow #MRS50YEARS! We welcome your comments and feedback.


Symposium SB12: Novel Soft Materials and Systems for Artificial Skin, Soft Robotics and Haptics

Marcia O’Malley, Rice University

Delivering Multi-Sensory and Multi-Scale Haptic Cues through Wearables

Written by Senam Tamakloe

The sense of touch involves skin receptors that detect various forms of stimuli. While scientists continue to recreate the sense of touch in virtual reality, a common design approach is stimulating touch sensations in the hands. However, unveiled robotic designs like the HaptX VR gloves are often bulky and cumbersome. Marcia O’Malley and her research group introduce an alternative approach for designing novel wearable devices that uses several haptic feedbacks (skin stretch, squeeze, and vibration cues) to the wrist and arm. These devices that simultaneously provide multiple cutaneous cues are a vast design improvement compared to everyday wearables that focus on a single vibration modality of feedback. O’Malley discussed the efforts to design novel wearable haptic devices (e.g., Tasbi and MISSIVE) that deliver the reliable perception of multi-sensory haptic cues. She presented ongoing challenges along with the current venture of exploring soft textile-based materials for constructing wearable haptic devices.


Symposium NM05: Challenges and Opportunities in Solution Synthesis of Functional Nanomaterials

Stefano Toso, Istituto Italiano di Tecnologia

Lead Chalcohalides Nanocrystals and Chalcohalide-Perovskite Heterostructures

Written by Senam Tamakloe

Chalcohalides are considered promising candidates for the next generation of photocatalysis and photovoltaic applications. The chalcohalide compounds, formed by one or more metals, a halide, and a chalcogenide, can offer different structures and properties. Despite widespread studies, lead chalcohalides are an example of less understood nanocrystals (NC) in terms of stochiometry and optoelectronic properties. Stefano Toso and his colleagues addressed this in their studies. Toso outlined a phase-selective synthesis approach that yielded two novel lead sulfochloride materials (Pb3S2Cl2 and Pb4S3Cl2). The synthesis of these two different yet competitive products relied on the formation of an intermediate heterostructure. The findings in this talk signify significant progress in understanding the directional design of novel nanomaterial synthesis.


Symposium SB06: Structure-Function Relationships and Optoelectronic Processes in Organic and Organic/Inorganic Hybrid Materials for Flexible Electronics and Photovoltaics

Satoru Ohisa, Japan Broadcasting Corporation

Organic Light-Emitting Devices Using Common Uneven Aluminum Foil as the Electrode

Written by Senam Tamakloe

In recent decades, organic light-emitting diodes (OLED) have become competitive participants in advancing solid-state light devices. However, their limiting constraints involve shorter lifespans, high manufacturing costs and insufficient conductivity of their components, such as the indium tin oxide (ITO) electrode. An essential requirement is having smooth electrodes that achieve a low surface roughness (Ra < several nm) which mitigates severe electric leakage. Satoru Ohisa proposed aluminum foil as a viable candidate for OLED electrode substrates due to their low cost, high conductivity, high thermal tolerance, and gas barrier performance. However, their increased surface roughness (Ra > 200 nm) causes these substrates to be absent in OLEDs. Ohisa and his colleagues fabricated a thick buffer layer electrode by covering and planarizing the aluminum foil surface with a phosphotungstic acid (H3PW12O40) (PWA) with a noticeably reduced surface roughness (Ra = 0.5 nm). As a result, Ohisa has successfully achieved an aluminum foil-based OLED with stable light emission.


Symposium EN06: Silicon for Photovoltaics

Stephanie Essig, University of Stuttgart

Challenges in the Realization of Perovskite/Si Tandem Solar Cells

Written by Henry Quansah Afful

Silicon-based solar cells have much higher efficiency when combined with other top cells having much wider bandgap, referred to as tandem solar cell design. Increasing the number of junctions (cells) increases the efficiency beyond 30 percent. However, the efficiency does not increase indefinitely as 6-junction devices were found to have comparable efficiency as the three-junction devices. This results from the extra complexity associated with the increase in number of top cells. These cells can be interconnected via different designs most notable of which is a 2-terminal tandem design. Stephanie Essig showed how the solar cell efficiency could also be increased via the 3-terminal and 4-terminal tandem designs. A 4-terminal GaInP/Si 2-junction tandem device had efficiency improved to beyond 30 percent. Essig demonstrated also that the challenges associated with the 3- and 4-terminal designs can be overcome by having an optimal voltage ratio between the top and bottom cells.


Symposium EQ06: Two-Dimensional (2D) van der Waals Materials—Quantum Properties and Electronic and Photonic Devices

Whan Kyun Kim, Sungkyunkwan University

Probing Magnetism in Cobalt-Intercalated MoTe2

Written by Senam Tamakloe

Ionic diffusion in layer lattices is a critical mechanism for controlling the electronic and magnetic properties of a system. The intercalation for two-dimensional (2D)-layered systems can be executed using the solid phase diffusion, vapor phase method and wet chemical method for applications such as electrochemical energy storage, 2D materials fabrication, and property tuning via the doping effect. In terms of magnetism, an intercalation technique where an extra element is inserted between the van der Waals (vdW) planes of 2D transition metal dichalcogenide (TMD) has not been actively explored. Whan Kyun Kim outlines a two-step intercalation reaction where lithium and cobalt ions intercalate TMD using the wet chemical method. Kim showed that the MoTe2 intercalated with Co involves the insertion of Co between the vdW layers of 2H-MoTe2 led to a phase transition to 1T´-MoTe2 after the Li-intercalation. We learned that Kim's intercalation reaction obtained a 2D material with ferromagnetic ordering. This study can serve as an active fabrication technique for acquiring improved 2D TMD-based spintronic systems.


Symposium NM02: Nanotubes, Graphene and Related Nanostructures

Shun Muroga, National Institute of Advanced Industrial Science and Technology

Multimodal Artificial Intelligence System for Virtual Screening of Complex Nanocomposite Materials

Written by Henry Quansah Afful

Artificial intelligence (AI) has been very instrumental in the search for new materials having properties meeting different application requirements. Conventionally used models employ atoms and chemical bonds as materials descriptors, which cannot be readily extended to complex materials structures such as composites. Composite materials structures involve highly complex interactions between the fillers and matrix resulting from such phenomena as crosslinking, phase separation, and filler orientation amongst others. Shun Muroga introduced a multimodal AI model that integrates conventional AI with other materials descriptors such as the physical and chemical structure. Muroga studied over 80 polymer matrix composites from five matrices, two additives, and three fillers all with different volume fractions. The materials were characterized using optical microscopy, infrared spectroscopy, and Raman spectroscopy and the results fed into the AI model. The model was able to self-generate characterization data and predict the properties of over 100,000 composite materials conditions after the training process. This demonstrates how the multimodal AI approach efficiently accounts for the interplay of complex interactions in composite materials, rendering it more effective at materials prediction than the conventional models.

 


Symposium EQ01: Progress in Thermoelectrics—From Traditional to Novel Materials

Eric Toberer, Colorado School of Mines

Defect Design in Thermoelectric Materials—Uniting Computation and Experiment for Tailored Synthesis and Transport Properties

Written by Henry Quansah Afful

The search for application-tailored thermoelectric materials often requires collaborations between experimentalists and computationalists. Eric Toberer points out that for these collaborations to be more fruitful, a deeper understanding of defect phyics is required to calculate native defect energetics and concentrations prior to experiments. This enables more productive efforts at predicting suitable compounds with desired properties. The considerations space in theoretical defect calculations exceed those of experiments. Experiments are mostly limited to nominal stoichiometry and processing parameters, whereas theory considers bandgaps, band masses, and elemental chemical potentials amongst others. This results in scenarios in which expected phase diagrams may differ between the two approaches. Toberer asserts the importance of ensuring not necessarily perfect agreement between the two approaches but rather close enough agreement within the same order of magnitude. This ensures that predicted defect concentrations in different compounds will be close enough to reality. He points out that, in the absence of these defect calculations, defect compensation by antisite defects for similar sites with different charges needs to be critically considered.


Symposium DS02: Integrating Machine Learning with Simulations for Accelerated Materials Modeling

Seunghwa Ryu, Korea Advanced Institute of Science & Technology

Machine Learning Based Design of Composite Structures

Written by Henry Quansah Afful

Composite materials have been explored for a myriad of applications owing to their superior properties over their individual constituents. These materials can be grouped, based on the available models, as particulate-reinforced, random microstructure, and periodic structures. There is a limitation in the frameworks available for designing materials systems with more predictable and superior properties. Machine learning (ML) is being employed to help predict and design much better composite materials based on available experimental and computational data. However, ML-based design faces challenges in extrapolation into unknown design spaces and limited datasets. To solve the extrapolation problem, Seunghwa Ryu proposed an active learning approach where the ML models were gradually updated with more data until the global optimum mechanical property was found. For this to be effective, results from the ML model need to be validated with experiments and simulations and new data fed into the neural network. Ryu demonstrated how the Bayesian optimization can be used to tackle the problem of limited datasets and low quality data by identifying regions with largest uncertainty and working to decrease the uncertainty. Ryu employed this approach to improve the toughness of a nacre-inspired composite.


Symposium SB10: New E-Textile Materials and Devices for Wearable Electronics

Felice Torrisi, Imperial College London

Two-Dimensional Field-Effect Heterostructures for Wearable and Textile Electronics

Written by Henry Quansah Afful

Wearable electronics are required to be, amongst other things, highly stretchable, biocompatible, and washable. Considering all these requirements, textiles are the most optimal substrates being used for these electronics. Employing two-dimensional (2D) material inks such as graphene and other layered materials for the electronic circuit design reduces the cost of production. These 2D materials show a lot of promise in tunability and multifunctionality. Using microfluidic exfoliation, graphene platelets can be obtained from graphite and the aspect ratio of these platelets can be tuned to have corresponding changes in electrical conductivity. In addition, bandgaps of the wearable electronics can be tuned by designing layered materials. Felice Torrisi demonstrated an inkjet printing approach for printing graphene oxide on a cotton substrate. The surface of the cotton was modified with cations to develop a positive charge whereas that of the graphene oxide ink was negatively charged. This was found to improve the adhesion of the ink on the cotton substrate considerably, resulting in stable electronic properties over 20 wash cycles. In addition, Torrisi showed how cotton wool could be mixed with graphene ink to produce graphene-cotton fiber via a wet-spinning approach. This significantly improved the flexibility of graphene.