Integrated Calendar

Not a day goes by when we don’t hear about the “climate crisis”; some effects are well documented, like the rise in the average global temperature and the shrinking of the polar ice caps. Undoubtedly, carbon dioxide levels in the atmosphere have been increasing, but what does “science” say about the potential consequences? The combination of the atmosphere, oceans, cryosphere and biosphere is the ultimate non-linear coupled complex system. How well do we understand what might happen? In the first part of my talk, I shall review my exploration of the original literature to try and separate out speculation, hypothesis, results of computational models, and most significantly actual observations. In the second part of my talk, I shall discuss what will actually work to reduce carbon dioxide emissions (complete elimination or Net Zero is an impossibility). Although it has become fashionable for governments to impose mandates enshrined in laws, the only laws that matter are the laws of thermodynamics and Ohm’s law.

We are interested in the organization and function of neural circuits for sensory processing and behavior. A main goal of the lab is to integrate complementary approaches of system interrogation: we study the molecular diversity of cell types, their connectivity and functional properties; we investigate network dynamics and core computational principles; and we explore how learning and experience shapes behavioral decisions.
I will discuss ongoing work aimed at characterizing molecular maps for odor processing in the mouse olfactory bulb. I will present preliminary data using spatial transcriptomics to generate a comprehensive map of glomerular identity and domain structure of the olfactory bulb. Furthermore, I will discuss single cell sequencing experiments and gene regulatory network models that define the diversity and connectivity of olfactory bulb projection neurons.
I will try to illustrate how the early olfactory system of mice provides an ideal model system to integrate molecular biology, functional imaging, and behavioral experiments to address fundamental questions in sensory processing and behavior.

From a perovskite photovoltaic device standpoint, the Al2O3 ALD can be thought of as a thin film encapsulate to protect the underlined material from the extrinsic entities. However, as per the literature is concerned, the role of Al2O3 ALD in the perovskite photovoltaic devices is much beyond a mare passive component. This raises a severe ambiguity over the choice of surface (or interface) on which ALD needs to be done for optimized device performance, in terms of the device efficiency and stability.

In my presentation, I would like to elucidate the characteristic differences between the surface limited and substrate enhanced ALD processes which is important to perovskite devices. The objective here is to discuss a unified correlation between the role of the Al2O3 ALD mechanism with the perovskite device performance by excluding popular overestimated assumption about the conformality on non-ideal surface, like perovskite or organic thin films. In addition, I would like to emphasize on the fact that how the ALD process can be used to passivate the buried interfacial defect and enhancing the VOC, PL and ELQE.

Neuromorphic computing designs have an important role in the modern ‘big data’ era, as they are suitable for processing large amount of information in short time, eliminating the von Neumann (VN) bottleneck. The neuromorphic hardware, taking its inspiration from the human brain, is designed to be used for artificial intelligence tasks via physical neural networks, such as speech or image recognition, bioinformatics, visual art processing and much more. The memristor (memory + resistor), is one of the promising building blocks for this hardware, as it mimics the behavior of a human synapse, and can be used as an analog non-volatile memory. The memristor has been proven as a viable memory element and has been used for constructing resistive random access memory (RRAM) as a replacement for current VN hardware. However, the mechanism of operation and the conducting bridge formation mechanisms in electrochemical metallization memristors still require further investigation. A planar single-nanowire (NW) based memristor is a good solution for elucidating the mechanism of operation, thanks to the high localization of switching events, allowing in-situ investigation as well as post-process analysis. Our group, which has developed the guided-growth approach to grow guided planar NWs on different substrates, has used this method to integrate guided epitaxial NWs into functional devices such as field-effect transistors (FETs), photodetectors and even address decoders. However, the guided-growth approach has not been used for creating memristors up to date.
In this work, I successfully synthesized guided NWs of two metal-oxides on flat and faceted sapphire substrates – ZnO and β-Ga2O3 were successfully grown in the VLS mechanism as surface guided NWs. I successfully grew planar guided β-Ga2O3 NWs on six different sapphire substrates, for the first time as far as we know. We characterized the newly grown β-Ga2O3 NWs with SEM, TEM, EDS and Raman spectroscopy. The monoclinic NWs grew along surprising directions on the flat sapphire surfaces and I demonstrated a new mode of growth – epitaxy favored growth on a faceted surface, when graphoepitaxy is also possible. I created electrochemical metallization memristors with the obtained NWs and successfully demonstrated the effect of resistive switching for β-Ga2O3 guided NW based devices. With the abovementioned achievements, we expanded the guided-growth approach on flat and faceted sapphire surfaces, and opened the opportunity for creating surface guided-NW based neuromorphic hardware.

Animals generate complex patterns of behavior across life that can be modified over days, months, or even years. Across these long timescales individuals within the same population may show stereotyped behaviors, but also unique behaviors that distinguish them from each other. How are long-term patterns of behavior organized and regulated across development? And what are the underlying processes that establish and modify individual-to-individual behavioral variation?
By utilizing parallel long-term behavioral monitoring at high spatiotemporal resolution of multiple C. elegans individuals across their complete development time we demonstrate temporal regulation of behavioral plasticity by neuromodulators across developmental stages, structuring shared and unique individual responses to early-life experiences. I will further describe our development of unsupervised analyses of individual biases across development based on locomotion trajectory and individual postures which uncovered a large spectrum of individuality types within the isogenic populations. Lastly, I will present preliminary results suggesting that specific neuronal pathways are required to robustly synchronize long-term behavior with development time.