Weizmann Institute of Science

Nuclear magnetic resonance (NMR) is a spectroscopy technique widely used by chemists and physicists to determine the chemical structure of molecules that was adapted to generate imaging, known as nuclear magnetic resonance imaging (MRI), which is widely used in medical diagnosis. The importance of NMR in chemistry, physics, medicine, materials, and agriculture has been recognized with several Nobel Prizes in Physics, 1952, Chemistry, 1991 and 2002, and Medicine in 2003. Therefore, NMR can be applied to obtain: i) imaging of the human body, animal and materials; ii) high-resolution spectra to obtain structural and dynamical information of chemicals, materials etc.; and iii) quantitative and qualitative information of chemical composition of products such as food and agricultural products, using low-resolution relaxometry. High-resolution NMR and MRI have been applied in agri-food products, mostly as a research tool as they typically rely on expensive and bulk instruments, which restrict their uses in routine applications. The NMR sensors that have been more frequently used in agri-food products are based on low-resolution or low-field or time-domain NMR (TD-NMR) instruments. These low-cost instruments have been used for qualitative and quantitative analysis of agri-food products such as intact seeds and grains, intact fruits, meat, oils, and processed foods. In this paper, an overview of the NMR techniques and its main instrumentation aspects are presented, and some applications of TD-NMR and MRI in the non-invasive analysis of food, seeds, and others agricultural products are discussed. Key words: nuclear magnetic resonance; time domain; seed analysis

The branched metal‐organic frameworks (MOFs) are the first superstructures of this kind, and the growth mechanism may explain crystal shapes of other materials. The mechanism of the formation of fascinating structures having a hedrite, sheaf or spherulite appearance are detailed. The branching can be controlled, resulting in crystals that either exhibit multiple generations of branching or a single generation. These structures might result from an increasing number of defects on fast‐grown rods. As the basal facets become less reactive, material is added to the prism facets, leading to secondary nucleation and triangular branches. These triangular structures are connected to the rod surface, growing longer than the central rod. Electron diffraction analyses show that the sheafs are polycrystalline structures with their fantails consisting of single‐crystalline nanorods deviating gradually from each other in their orientation. The crystallographic structure consists of channels with opposite handedness. The accessibility of the nanochannels and the porosity of the superstructures are demonstrated by chromophore diffusion into the channels. The confinement and alignment of the chromophores inside the channels resulted in polarized‐light dependent coloration of the crystals; the polycrystallinity generated areas having different optical properties.

Chemical waves represent one of the fundamental behaviors that emerge in nonlinear, out-of-equilibrium chemical systems. They also play a central role in regulating behaviors and development of biological organisms. Nevertheless, understanding their properties and achieving their rational synthesis remains challenging. In this work, we obtained traveling chemical waves using synthetic organic molecules. To accomplish this, we ran a thiol-based reaction network in an unstirred flow reactor. Our observations revealed single or multiple waves moving in either the same or opposite directions, a behavior controlled by the geometry of our reactor. A numerical model can fully reproduce this behavior using the proposed reaction network. To better understand the formation of waves, we varied the diffusion coefficient of the fast inhibitor component of the reaction network by attaching polyethylene glycol tails with different lengths to maleimide and studied how these changes affect the properties of the waves and conditions for their sustained production. These studies point towards the importance of the molecular titration network motif in controlling the production of chemical waves in this system. Furthermore, we used machine learning (ML) tools to identify phase boundaries for classes of dynamic behaviors of this system, thus demonstrating the applicability of ML tools for the study of experimental nonlinear reaction-diffusion systems.

The discovery of two-dimensional (2D) materials has opened a new era of scientific research and industrial application. From the field effect transistor to the optoelectronic devices, 2D materials have surpassed their 3D counterparts in many ways. This all started with the successful exfoliation of the graphene from the bulk graphite sample by the Andre Geim group long back in 2004 Novoselov (2004). Soon after the discovery of graphene, a wide variety of 2D materials were discovered. These includes but not limited to semiconductors (${\text {MoSe}}_2, {\text {WSe}}_2, {\text {MoS}}_2, {\text {WS}}_{2}$), insulators (hBN), superconductors (${\text {NbSe}}_2, {\text {TaS}}_{2}$), ferromagnets (${\text {Cr}}_2{\text {Ge}}_2{\text {Te}}_6, {\text {FePS}}_3, {\text {CrI}}_3, {\text {MnPS}}_{3}$). In this chapter, we discuss the low-energy electronic properties of single-layer graphene. We further extend our discussion to bilayer and trilayer graphene. Next, we discuss the effect of the other substrate on graphene’s band structure. In particular, we will discuss the effect of moire potential imprinted due to rotational alignment between graphene and the hBN layer. All electronic properties studied in this chapter will be at zero magnetic fields. The zero magnetic field properties discussed in this chapter form the basis for understanding what happens in the finite magnetic field, which is discussed in Chap. 2.

In the previous chapter, we discussed the thermal conductance measurement of integer ($\nu =1, 2, 6$) and a particle-like fractional ($\nu =4/3$) quantum Hall states of the single-layer graphene, where the edge structures harbour only downstream edge modes. The measured values of quantized thermal conductance for these fillings were consistent with the expected theoretical limit of $G_Q = N_d\kappa _0 T$, where $N_d$ is the number of downstream edge modes. However, for a certain class of fractional quantum Hall states, called hole-conjugate states, in addition to the downstream edge modes, the edge structure harbours the upstream edge modes propagating anti-parallel to the downstream edge modes. In the presence of such counter-propagating edge modes, measured electrical and thermal conductances depend on the extent of the ‘equilibration’ between the counter-propagating edge modes. In this chapter, we focus on measurements of electrical and thermal conductances of integer and fractional QH phases, realized in hexagonal boron nitride encapsulated graphite-gated bilayer graphene devices for both electron and hole-doped sides with different valley and orbital symmetries. Remarkably, for complex edges at filling factors $\nu =\frac{5}{3}$ and $\frac{8}{3}$, closely related to the paradigmatic hole-conjugate $\nu =\frac{2}{3}$ phase, we find quantized thermal conductance whose values ($3\kappa _{0}T$ and $4\kappa _{0}T$, respectively where $\kappa _{0}T$ is the thermal conductance quantum) are markedly inconsistent with the values dictated by topology ($1\kappa _{0}T$ and $2\kappa _{0}T$, respectively). The measured thermal conductance values remain insensitive to different symmetries, suggesting its universal nature. A theoretical analysis further supports these findings, which indicates that while charge equilibration at the edge is established over a finite length scale, the thermal equilibration length diverges for strong electrostatic interaction. These results elucidate the subtle nature of crossover from coherent, mesoscopic to topology-dominated transport.

The relative twist angle in heterostructures of two-dimensional materials with similar lattice constants dramatically alters the electronic properties. Here, we investigate the electrical and magnetotransport properties in bilayer graphene encapsulated between two hexagonal boron nitride (hBN) crystals, where the top and bottom hBN are rotationally aligned with the bilayer graphene with a twist angle $\theta _t\sim 0^{\circ }$ and $\theta _b < 1^{\circ }$, respectively. This results in the formation of two moiré superlattices, with the appearance of satellite resistivity peaks at carrier densities $n_{s1}$ and $n_{s2}$, in both hole- and electron-doped regions, together with the resistivity peak at zero carrier density. Furthermore, we measure the temperature (T) dependence of the resistivity ($\rho$). The resistivity shows a linear increment with temperature within the range 10 to 50 K for the density regime $n_{s1} <n<n_{s2}$ with a large slope d$\rho$/dT $\sim$ 8.5 $\Omega$/K. The large slope of d$\rho$/dT is attributed to the enhanced electron-phonon coupling arising from the suppression of Fermi velocity in the reconstructed minibands, theoretically predicted recently in doubly aligned graphene with top and bottom hBN. Our result establishes the uniqueness of a doubly aligned moire system to tune the strength of electron-phonon coupling and to modify the electronic properties of multilayered heterostructures.

As discussed earlier in the Chapter, 2, the universal quantization of thermal conductance provides information on the topological order of a state beyond the conventional electrical conductance measurement. Although the traditional electrical conductance measurement has been performed extensively in quantum Hall phases of “graphene” and GaAs/AlGaAs two-dimensional electron gas systems, thermal conductance measurement has been lacking since the experimental discoveries of the quantum Hall states. It (thermal conductance) has only become possible recently in GaAs/AlGaAs two-dimensional electron gas systems, demonstrating the universal quantization of thermal conductance for integer and Jain-sequence of the fractional quantum Hall states. In particular, the experimentally measured value of the thermal conductance of the 5/2 state in GaAs/AlGaAs based system raises several essential points, motivating further to reconsider the initial theoretical claims of the ground state of this novel electronic phase. More importantly, the thermal conductance measurement analysis has been complicated by the presence of counter-propagating edge channels arising from edge reconstruction, an inevitable consequence of separating the dopant layer from the GaAs quantum well and the resulting soft confining potential. Fortunately, graphene, a two-dimensional allotrope of carbon, has emerged as a novel two-dimensional material. The edge reconstruction issue is believed to be avoided due to its sharp confining potential. In this Chapter, we present the measurement of the thermal conductance in graphene having atomically sharp confining potential by using sensitive noise thermometry on hexagonal boron nitride encapsulated graphene devices, gated by either SiO$_{2}$/Si or graphite back gate. We find the quantization of thermal conductance within $5\%$ accuracy for $\nu =1, 4/3, 2,$ and 6 plateaus, emphasizing the universality of the flow of information. These graphene quantum Hall thermal transport measurements will allow us to look into more complex hole-like and even denominator FQH states in “graphene”.

In previous chapters, we have studied the electrical and thermal conductance of the topological edge modes of integer and fractional quantum Hall (QH) phases, which emerges by applying a large perpendicular magnetic field to the plane of the “graphene” layer. These edge modes’ topological protection makes them unique and prone to back-scattering. As a result, these quantum Hall edge modes become very important from the fundamental physics point of view and also become the host of exotic quasi-particles like Majorana fermion and para-fermion. However, in addition to these QH edge modes, edge modes also exist at zero magnetic fields at the boundary of several two-dimensional materials. These are also important for many possible applications and should be explored in detail. Many exciting phenomena, including electric-field-tunable magnetism and valley-dependent transport, have been predicted theoretically based on the characteristics of edge states in graphene layers. Although significant efforts have been made to understand the edge transport in single and bilayer graphene, a similar study is lacking in trilayer graphene, which has recently re-emerged as an exciting two-dimensional material, offering many interesting electronic phases. In this chapter, we report the detection of the edge states in bernal stacked trilayer graphene. We report the observation of the large non-local signal in dual-gated bernal stacked (ABA) trilayer graphene devices. The measured non-local signal is much larger than the classical ohmic contribution. We further did the scaling analysis of the non-local resistance and found that it scales linearly with the local resistance, suggesting the presence of edge-mediated non-local charge transport. The scaling exponent of unity was over the range of displacement fields and the temperature range. The experimental findings are attributed to the presence of the nontrivial valley Hall state, which emerges on applying the displacement fields predicted long back by Morimoto et al. (2013). In this phase, the energy gap at the Dirac points is filled by the chiral edge modes, which propagate in opposite directions between the two valleys.

The major part of this thesis was dedicated to understanding the edge structures of the integer and fractional quantum Hall (QH) phases realized in hBN-encapsulated “graphene” devices by measuring the quantized thermal and electrical conductance. These works are reported in chapter 4, 5, and 6. In the last two working chapters of this thesis, we study two different problems which are not related to the thermal conductance measurement. In chapter 7, we have reported the detection of the dispersive edge modes in bernal stacked trilayer graphene using the nonlocal transport measurement. In chapter 8, we report the enhanced electron-phonon coupling in a doubly aligned hBN/BLG moiré device.

This chapter will discuss the details of the device fabrication and measurement techniques. We will start our discussion with the mechanical exfoliation and characterization of atomically thin two-dimensional (2D) materials, like “graphene” and few-layer hexagonal boron nitride (hBN) flakes. Further, we will discuss the heterostructure assembly process. Later on, we will discuss the process used to make the electrical contacts. The second section of this chapter will discuss the measurement techniques and setup used in the electrical and thermal conductance measurement reported in this thesis.

We consider a search problem on trees aiming to find a treasure that an adversary places at one of the nodes. The algorithm can query nodes and extract directional information from them. That is, each node holds a pointer, termed advice , to one of its neighbors. Ideally, this advice points to the neighbor that is closer to the treasure, however, with probability q this advice points to a uniformly random neighbor. Crucially, the advice is permanent , hence querying the same node again yields the same answer. Let $\Delta$ denote the maximal degree. Roughly speaking, we show that the expected number of queries incurs a phase transition when q is about $1/\sqrt{\Delta}$ . In a recent paper, at TALG’21, we showed that if q is above the threshold then the expected number of queries is polynomial in n . Here we prove that below the threshold, the expected number of queries is $\mathcal{O}(\sqrt{\Delta}\log\Delta\cdot\log^{2}n)$ , which is tight up to an $\mathcal{O}(\log n)$ factor when $\Delta$ is small. We further show that this factor can be reduced to $\mathcal{O}(\log\log n)$ in the case of regular trees and assuming that $q{\,\lt\,}c/\sqrt{\Delta}$ for sufficiently small $c{\,\gt\,}0$ . In addition, we study the case that the treasure must be found with some given probability. We show that for every fixed $\varepsilon,\delta{\,\gt\,}0$ , if $q{\,\lt\,}1/\Delta^{\varepsilon}$ then there exists a search strategy that with probability $1-\delta$ finds the treasure using $(\delta^{-1}\log n)^{O(\frac{1}{\varepsilon})}$ queries, whereas $(\delta^{-1}\log n)^{\Omega(\frac{1}{\varepsilon})}$ queries are necessary.

Piperine (PIP) has attracted extensive attention due to its diverse biological activities. In this study, we developed two photoaffinity probes PIP-1 and PIP-2, which are biologically safe and retain PIP’s...

This study employs a high-resolution (10m) System for Atmospheric Modeling (SAM) coupled with the Spectral Bin Microphysical (SBM) scheme to thoroughly investigate the processes governing the evolution of aerosol properties within and outside a shallow cumulus cloud. The model encompasses the complete life cycle of cloud droplets, starting from their formation through their evolution until their complete evaporation or sedimentation to the ground. Additionally, the model tracks the aerosols’ evolution both within droplets and in the air. Aerosols are transported within the droplets, grow by droplet coalescence, and are released into the atmosphere after droplet evaporation (regeneration process). The aerosol concentration increases by droplet evaporation and decreases along with falling drops. So, the effects of clouds on the surrounding aerosols depend on the microphysical and dynamic processes, which in turn depend on the amount of background aerosols; here, we compare clean and polluted conditions. It is shown that the regeneration process is highly important and that shallow trade cumulus clouds significantly impact the vertical profile of aerosol concentration in the lower troposphere, as well as their size distribution, and can serve as a source of large cloud condensation nuclei. Furthermore, it is shown that both precipitating and non-precipitating boundary layer clouds contribute to a substantial increase in aerosol concentration within the inversion layer due to intense evaporation.

With immuno-oncology becoming the standard of care for a variety of cancers, identifying biomarkers that reliably classify patient response, resistance, or toxicity becomes the next critical barrier towards improving care. Multi-parametric, multi-omics, and computational platforms generating an unprecedented depth of data are poised to usher in the discovery of increasingly robust biomarkers for enhanced patient selection and personalized treatment approaches. Deciding which developing technologies to implement in clinical settings ultimately, applied either alone or in combination, relies on weighing pros and cons, from minimizing patient sampling to maximizing data outputs, and assessing reproducibility and representativeness of findings, while lessening data fragmentation towards harmonization. These factors are all assessed while taking into consideration the shortest turnaround time. The Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to identify important advances in biomarker technologies and to address advances in biomarker discovery using multiplexed immunohistochemistry and immunofluorescence, their coupling to single cell transcriptomics, along with mass spectrometry-based quantitative and spatially resolved proteomics imaging technologies. We summarize key metrics obtained, ease of interpretation, limitations and dependencies, technical improvements, and outward comparisons of these technologies. By highlighting the most interesting recent data contributed by these technologies, and by providing ways to improve their outputs, we hope to guide correlative research directions and assist in their evolution towards becoming clinically useful in IO.