ABSTRACT
PURPOSE: The aim of this qualitative study was to investigate resilience among adults with Osteogenesis Imperfecta (OI). MATERIALS AND METHODS: Semi-structured interviews were conducted with 15 adults with OI. Transcripts were coded and subsequently abstracted, yielding themes specific to resilience and coping. Interview guides covered broad topics including pain challenges specific to OI, mental health issues related to OI, and priorities for future interventions for individuals with OI. RESULTS: Participants described resilience in the context of OI as the ability to grow from adversity, adapt to challenges resulting from OI-related injuries, and find identities apart from their condition. Psychological coping strategies included acceptance, self-efficacy, cognitive reframing, perspective-taking, and positivity. Behavioral factors that helped participants develop resilience included developing new skills, pursuing meaningful goals, practicing spirituality, and seeking external resources such as psychotherapy, education, and connection with community. CONCLUSION: Having identified how adults with OI define resilience and the strategies they use to cope, we can now develop interventions and guide healthcare providers in improving psychological wellbeing in this population.
Adults with Osteogenesis Imperfecta (OI) employ resilience factors to combat mobility and pain-related issues.Adults with OI report developing adaptive skills to cope with their disease, including forming one's identity outside of OI, growing through adversity, overcoming challenges resulting from OI-related injury, employing psychological adaptations, and practicing behavioral coping strategies.Resiliency factors such as behavioral and psychological coping (e.g., exercise, breathing strategies, acceptance) may buffer against OI-related challenges, and treatment modalities that foster these activities may be beneficial for adults with OI.
ABSTRACT
Moiré quantum materials host exotic electronic phenomena through enhanced internal Coulomb interactions in twisted two-dimensional heterostructures1-4. When combined with the exceptionally high electrostatic control in atomically thin materials5-8, moiré heterostructures have the potential to enable next-generation electronic devices with unprecedented functionality. However, despite extensive exploration, moiré electronic phenomena have thus far been limited to impractically low cryogenic temperatures9-14, thus precluding real-world applications of moiré quantum materials. Here we report the experimental realization and room-temperature operation of a low-power (20 pW) moiré synaptic transistor based on an asymmetric bilayer graphene/hexagonal boron nitride moiré heterostructure. The asymmetric moiré potential gives rise to robust electronic ratchet states, which enable hysteretic, non-volatile injection of charge carriers that control the conductance of the device. The asymmetric gating in dual-gated moiré heterostructures realizes diverse biorealistic neuromorphic functionalities, such as reconfigurable synaptic responses, spatiotemporal-based tempotrons and Bienenstock-Cooper-Munro input-specific adaptation. In this manner, the moiré synaptic transistor enables efficient compute-in-memory designs and edge hardware accelerators for artificial intelligence and machine learning.
ABSTRACT
Solution-processed graphene is a promising material for numerous high-volume applications including structural composites, batteries, sensors, and printed electronics. However, the polydisperse nature of graphene dispersions following liquid-phase exfoliation poses major manufacturing challenges, as incompletely exfoliated graphite flakes must be removed to achieve optimal properties and downstream performance. Incumbent separation schemes rely on centrifugation, which is highly energy-intensive and limits scalable manufacturing. Here, cross-flow filtration (CFF) is introduced as a centrifuge-free processing method that improves the throughput of graphene separation by two orders of magnitude. By tuning membrane pore sizes between microfiltration and ultrafiltration length scales, CFF can also be used for efficient recovery of solvents and stabilizing polymers. In this manner, life cycle assessment and techno-economic analysis reveal that CFF reduces greenhouse gas emissions, fossil energy usage, water consumption, and specific production costs of graphene manufacturing by 57%, 56%, 63%, and 72%, respectively. To confirm that CFF produces electronic-grade graphene, CFF-processed graphene nanosheets are formulated into printable inks, leading to state-of-the-art thin-film conductivities exceeding 104 S m-1 . This CFF methodology can likely be generalized to other van der Waals layered solids, thus enabling sustainable manufacturing of the diverse set of applications currently being pursued for 2D materials.
ABSTRACT
Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circuits that seek to emulate the energy-efficient information processing of the brain. While non-volatile memory (NVM) based on resistive switches, phase-change memory, and magnetic tunnel junctions has shown potential for implementing neural networks, additional multi-terminal device concepts are required for more sophisticated bio-realistic functions. Of particular interest are memtransistors based on low-dimensional nanomaterials, which are capable of electrostatically tuning memory and learning behavior at the device level. Herein, a conceptual overview of the memtransistor is provided in the context of neuromorphic circuits. Recent progress is surveyed for memtransistors and related multi-terminal NVM devices including dual-gated floating-gate memories, dual-gated ferroelectric transistors, and dual-gated van der Waals heterojunctions. The different materials systems and device architectures are classified based on the degree of control and relative tunability of synaptic behavior, with an emphasis on device concepts that harness the reduced dimensionality, weak electrostatic screening, and phase-changes properties of nanomaterials. Finally, strategies for achieving wafer-scale integration of memtransistors and multi-terminal NVM devices are delineated, with specific attention given to the materials challenges for practical neuromorphic circuits.