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The dual coupling between intrinsic magnetism and electronic properties garners enormous attention nowadays, due to their influence on quantum technologies. The talk will elaborate on the mentioned topic in van der Waals transition metal tri-chalcogenides and two-dimensional (2D) perovskites, possessing one or more of the following magnetic properties: A long-range magnetic order (ferromagnetism, anti-ferromagnetism), an interfacial/structure driven Rashba spin-orbit, Overhauser magnetic polaron effects.
The lamellar metal phosphor tri-chalcogenides (MPX3; M=metal, X=chalcogenide) possess a honeycomb arrangement of metal ions within a single layer, producing a ferromagnetic or anti-ferromagnetic arrangement, with a consequence influence on magneto-optical properties. The talk will display magneto-optical measurements, exposing routes for the long-range magnetism and the existence of valley degree of freedom in a few MPX3 (M= Mn, Fe). The results suggest that magnetism protects the spin helicity of each valley however, the coupling to anti-ferromagnetism lifts the valleys' energy degeneracy.
2D perovskite structures (e.g., (PEA)2PbI4) are composed of alternating organic-inorganic constituents. The talk will describe the most recent work, exposing the co-existence of a Rashba and the Overhauser effects, in a structure with an inversion of symmetry. The unexpected effect is explained theoretically by the breakage of symmetry through the exchange between structural configurations.

An essential trait of plants is the ability to change intrinsic programs to align with external signals. Plants can sense their environment and respond by refining their development program. A good example of sensing and response is the behavior of stomata. Plant stomata optimize the assimilation of carbon dioxide (CO2) for use in photosynthesis while minimizing water loss. They do this in two ways: by physiological control of when they are open or closed and by developmental regulation of their abundance and pattern. Both modes of control can be regulated by the environment, and as we face future climate change, with an increase in average global temperatures and water limitation, the understanding of how plants optimize stomatal production and patterns with the environment has fundamental importance. Our fullest understanding of the genetic control of stomatal development is from work in Arabidopsis. Here, development involves a core set of transcription factors whose expression and activity are regulated by signals from neighbor cells, from distant parts of the plant and from environmental cues like light, temperature, osmotic stress, and CO2 levels. But while Arabidopsis is a powerful model for stomatal development, this research showed that tomatoes often lean on different cellular and genetic strategies to achieve optimal stomatal distributions. Using novel genetically encoded reporters and custom microscopy for developmental time-course analysis, we found that, like in Arabidopsis, tomato undergoes a series of asymmetric and symmetric cell divisions to produce stomata. However, we found that not all asymmetric divisions (ACDs) are the same; certain classes of ACDs are missing in the tomato epidermis, and instead other types of ACDs are used to generate non-stomatal cells. ACDs have been shown in both plant and animal systems to enable tunable development. This findings in tomato indicate that there are new types of ACDs that could mediate species-specific control of cell production and tissue organization.

Methodologies that rely on the addition and removal of molecular hydrogen from organic
compounds are one of the most oft-employed transformations in modern organic chemistry,
representing a highly relevant tactic in synthesis. Despite their overall simplicity, organic chemists
are still pursuing sustainable and scalable processes for such transformations.
In this regard, electrochemical techniques have long been heralded for their innate sustainability
as efficient methods to perform redox reactions. In our first report, we discovered a new oxidative
electrochemical process for the a,b-desaturation of carbonyl functionalities. The described
desaturation method introduces a direct pathway to desaturated ketones, esters, lactams and
aldehydes simply from the corresponding enol silanes/phosphates, and electricity as the primary
reagent. This electrochemically driven desaturation exhibits high functional group tolerance, is
easily scalable (1–100 g), and can be predictably implemented into synthetic pathways using
experimentally or computationally derived NMR shifts.
Our second report demonstrated the reductive electrochemical cobalt-hydride generation for
synthetic organic applications inspired by the well-established cobalt-catalyzed hydrogen
evolution chemistry. We have developed a silane- and peroxide-free electrochemical cobalthydride
generation for formal hydrogen atom transfer reactions reliant on the combination of a
simple proton source and electricity as the hydride surrogate. Thus, a versatile range of tunable
reactivities involving alkenes and alkynes can be realized with unmatched efficiency and
chemoselectivity, such as isomerization, selective E/Z alkyne reduction, hydroarylation,
hydropyridination, strained ring expansion, and hydro-Giese.

The architecture of the primate visual system is based on the fovea-fixation-saccade system for high-acuity vision. This talk will describe an analogous system in night vision of monkeys. Processing is based not on the fovea but on a ‘scotopic center’. Unlike the fovea, which is fixed in the retina, the scotopic center relocates over a ‘scotopic band’, according to the intensity of the ambient light and, more generally, perceptual uncertainty. The eye movements involved have sensorimotor transformations specific to night vision. The discussion will touch on the evolution of vision, including relevance for humans.
Link: https://weizmann.zoom.us/j/95406893197?pwd=REt5L1g3SmprMUhrK3dpUDJVeHlrZz09
Meeting ID: 954 0689 3197
Password: 750421

 

I will demonstrate how neural representation geometry may hold the key to linking animal behavior and learning to circuit mechanisms. We will proceed in three steps. 1) We will start by establishing a connection between the sequential dynamics of complex behavior and geometrical properties of neural representations. 2) We will then link these geometrical properties to underlying circuit components. Specifically, we will uncover connectivity mechanisms that allow the circuit to control the geometry of its representations. 3) Finally, we will investigate how key geometrical structures emerge, de novo, through learning. To answer this, we will analyze the learning of representations in feedforward and recurrent neural networks trained to perform predictive tasks using machine learning techniques. As a result, we will show how both learning mechanisms and behavioral demands shape the geometry of neural representations.