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Showing papers by "Massachusetts Institute of Technology published in 2022"


Journal ArticleDOI
Tracy Hussell1, Ramsey Sabit2, Rachel Upthegrove3, Daniel M. Forton4  +524 moreInstitutions (270)
TL;DR: The Post-hospitalisation COVID-19 study (PHOSP-COVID) as mentioned in this paper is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID19 across the UK.

118 citations



Journal ArticleDOI
TL;DR: In this article , a family of nanometre-thick, two-dimensional (2D) ferroelectric semiconductors, where the individual constituents are well-studied non-ferroelectric monolayer transition metal dichalcogenides (TMDs), namely WS2, MoSe2, WS2 and MoS2, are presented.
Abstract: van der Waals materials have greatly expanded our design space of heterostructures by allowing individual layers to be stacked at non-equilibrium configurations, for example via control of the twist angle. Such heterostructures not only combine characteristics of the individual building blocks, but can also exhibit physical properties absent in the parent compounds through interlayer interactions1. Here we report on a new family of nanometre-thick, two-dimensional (2D) ferroelectric semiconductors, where the individual constituents are well-studied non-ferroelectric monolayer transition metal dichalcogenides (TMDs), namely WSe2, MoSe2, WS2 and MoS2. By stacking two identical monolayer TMDs in parallel, we obtain electrically switchable rhombohedral-stacking configurations, with out-of-plane polarization that is flipped by in-plane sliding motion. Fabricating nearly parallel-stacked bilayers enables the visualization of moiré ferroelectric domains as well as electric field-induced domain wall motion with piezoelectric force microscopy. Furthermore, by using a nearby graphene electronic sensor in a ferroelectric field transistor geometry, we quantify the ferroelectric built-in interlayer potential, in good agreement with first-principles calculations. The new semiconducting ferroelectric properties of these four new TMDs opens up the possibility of studying the interplay between ferroelectricity and their rich electric and optical properties2-5.

87 citations


Journal ArticleDOI
TL;DR: A comprehensive review of the recent progress achieved with photonic metamaterials whose properties stem from their modulation in time can be found in this article , where the basic concepts underpinning temporal switching and its relation with spatial scattering are discussed.
Abstract: Time-varying media have recently emerged as a new paradigm for wave manipulation, due to the synergy between the discovery of highly nonlinear materials, such as epsilon-near-zero materials, and the quest for wave applications, such as magnet-free nonreciprocity, multimode light shaping, and ultrafast switching. In this review, we provide a comprehensive discussion of the recent progress achieved with photonic metamaterials whose properties stem from their modulation in time. We review the basic concepts underpinning temporal switching and its relation with spatial scattering and deploy the resulting insight to review photonic time-crystals and their emergent research avenues, such as topological and non-Hermitian physics. We then extend our discussion to account for spatiotemporal modulation and its applications to nonreciprocity, synthetic motion, giant anisotropy, amplification, and many other effects. Finally, we conclude with a review of the most attractive experimental avenues recently demonstrated and provide a few perspectives on emerging trends for future implementations of time-modulation in photonics.

78 citations


Journal ArticleDOI
TL;DR: In this paper, the authors provide a balanced perspective on the impacts on climate change associated with blue hydrogen and show that such impacts may indeed vary over large ranges and depend on only a few key parameters: the methane emission rate of the natural gas supply chain, the CO2 removal rate at the hydrogen production plant, and the global warming metric applied.
Abstract: Natural gas based hydrogen production with carbon capture and storage is referred to as blue hydrogen. If substantial amounts of CO2 from natural gas reforming are captured and permanently stored, such hydrogen could be a low-carbon energy carrier. However, recent research raises questions about the effective climate impacts of blue hydrogen from a life cycle perspective. Our analysis sheds light on the relevant issues and provides a balanced perspective on the impacts on climate change associated with blue hydrogen. We show that such impacts may indeed vary over large ranges and depend on only a few key parameters: the methane emission rate of the natural gas supply chain, the CO2 removal rate at the hydrogen production plant, and the global warming metric applied. State-of-the-art reforming with high CO2 capture rates combined with natural gas supply featuring low methane emissions does indeed allow for substantial reduction of greenhouse gas emissions compared to both conventional natural gas reforming and direct combustion of natural gas. Under such conditions, blue hydrogen is compatible with low-carbon economies and exhibits climate change impacts at the upper end of the range of those caused by hydrogen production from renewable-based electricity. However, neither current blue nor green hydrogen production pathways render fully “net-zero” hydrogen without additional CO2 removal.

72 citations


Journal ArticleDOI
TL;DR: In this article , the discovery of type-II multiferroic order in a single atomic layer of the transition metal-based van der Waals material NiI2 was reported.
Abstract: Multiferroic materials have garnered wide interest for their exceptional static and dynamical magnetoelectric properties. In particular, type-II multiferroics exhibit an inversion-symmetry-breaking magnetic order which directly induces a ferroelectric polarization through various mechanisms, such as the spin-current or the inverse Dzyaloshinskii-Moriya effect. This intrinsic coupling between the magnetic and dipolar order parameters results in record-strength magnetoelectric effects. Two dimensional materials possessing such intrinsic multiferroic properties have been long sought for harnessing magnetoelectric coupling in nanoelectronic devices. Here, we report the discovery of type-II multiferroic order in a single atomic layer of the transition metal-based van der Waals material NiI2. The multiferroic state of NiI2 is characterized by a proper-screw spin helix with given handedness, which couples to the charge degrees of freedom to produce a chirality-controlled electrical polarization. We use circular dichroic Raman measurements to directly probe the magneto-chiral ground state and its electromagnon modes originating from dynamic magnetoelectric coupling. Using birefringence and second-harmonic generation measurements, we detect a highly anisotropic electronic state simultaneously breaking three-fold rotational and inversion symmetry, and supporting polar order. The evolution of the optical signatures as a function of temperature and layer number surprisingly reveals an ordered magnetic, polar state that persists down to the ultrathin limit of monolayer NiI2. These observations establish NiI2 and transition metal dihalides as a new platform for studying emergent multiferroic phenomena, chiral magnetic textures and ferroelectricity in the two-dimensional limit.

51 citations


Journal ArticleDOI
20 Jun 2022
TL;DR: The DarTG toxin-antitoxin (TA) system as discussed by the authors protects bacteria against phage infection via ADP-ribosylation of the viral DNA, and this can be evaded by phages via mutation of their DNA polymerase or the gp61.2 anti-DarT factor.
Abstract: Toxin-antitoxin (TA) systems are broadly distributed, yet poorly conserved, genetic elements whose biological functions are unclear and controversial. Some TA systems may provide bacteria with immunity to infection by their ubiquitous viral predators, bacteriophages. To identify such TA systems, we searched bioinformatically for those frequently encoded near known phage defence genes in bacterial genomes. This search identified homologues of DarTG, a recently discovered family of TA systems whose biological functions and natural activating conditions were unclear. Representatives from two different subfamilies, DarTG1 and DarTG2, strongly protected E. coli MG1655 against different phages. We demonstrate that for each system, infection with either RB69 or T5 phage, respectively, triggers release of the DarT toxin, a DNA ADP-ribosyltransferase, that then modifies viral DNA and prevents replication, thereby blocking the production of mature virions. Further, we isolated phages that have evolved to overcome DarTG defence either through mutations to their DNA polymerase or to an anti-DarT factor, gp61.2, encoded by many T-even phages. Collectively, our results indicate that phage defence may be a common function for TA systems and reveal the mechanism by which DarTG systems inhibit phage infection. The DarTG toxin-antitoxin system protects bacteria against phage infection via ADP-ribosylation of the viral DNA, and this can be evaded by phages via mutation of their DNA polymerase or the gp61.2 anti-DarT factor.

44 citations


Journal ArticleDOI
TL;DR: In this paper, the deformation micro-mechanisms including texture-facilitated prismatic 〈 a 〉 slip activation together with the near-ideal slip transfer conditions across the α/β phase boundaries are found to be predominant in the strain localization regions.

38 citations


Journal ArticleDOI
TL;DR: In this article , the authors demonstrate cell-type specificity in the tumor-suppressive functions of SMARCA4 in the lung, pointing toward a critical role of the cell-of-origin in driving SWI/SNF-mutant lung adenocarcinoma.
Abstract: SMARCA4/BRG1 encodes for one of two mutually exclusive ATPases present in mammalian SWI/SNF chromatin remodeling complexes and is frequently mutated in human lung adenocarcinoma. However, the functional consequences of SMARCA4 mutation on tumor initiation, progression, and chromatin regulation in lung cancer remain poorly understood. Here, we demonstrate that loss of Smarca4 sensitizes club cell secretory protein-positive cells within the lung in a cell type-dependent fashion to malignant transformation and tumor progression, resulting in highly advanced dedifferentiated tumors and increased metastatic incidence. Consistent with these phenotypes, Smarca4-deficient primary tumors lack lung lineage transcription factor activities and resemble a metastatic cell state. Mechanistically, we show that Smarca4 loss impairs the function of all three classes of SWI/SNF complexes, resulting in decreased chromatin accessibility at lung lineage motifs and ultimately accelerating tumor progression. Thus, we propose that the SWI/SNF complex via Smarca4 acts as a gatekeeper for lineage-specific cellular transformation and metastasis during lung cancer evolution. SIGNIFICANCE: We demonstrate cell-type specificity in the tumor-suppressive functions of SMARCA4 in the lung, pointing toward a critical role of the cell-of-origin in driving SWI/SNF-mutant lung adenocarcinoma. We further show the direct effects of SMARCA4 loss on SWI/SNF function and chromatin regulation that cause aggressive malignancy during lung cancer evolution.This article is highlighted in the In This Issue feature, p. 275.

37 citations


Journal ArticleDOI
TL;DR: The Beam Energy Scan Theory (BEST) Collaboration was formed with the goal of providing a theoretical framework for analyzing data from the BES program at the relativistic heavy ion collider (RHIC) at Brookhaven National Laboratory as mentioned in this paper.

36 citations


Journal ArticleDOI
TL;DR: Differentiable Projective Dynamics (DiffPD) as mentioned in this paper is a differentiable soft-body simulator based on PD with implicit time integration, which uses the prefactorized Cholesky decomposition in forward PD simulation.
Abstract: We present a novel, fast differentiable simulator for soft-body learning and control applications. Existing differentiable soft-body simulators can be classified into two categories based on their time integration methods: Simulators using explicit time-stepping scheme require tiny time steps to avoid numerical instabilities in gradient computation, and simulators using implicit time integration typically compute gradients by employing the adjoint method and solving the expensive linearized dynamics. Inspired by Projective Dynamics (PD), we present Differentiable Projective Dynamics (DiffPD), an efficient differentiable soft-body simulator based on PD with implicit time integration. The key idea in DiffPD is to speed up backpropagation by exploiting the prefactorized Cholesky decomposition in forward PD simulation. In terms of contact handling, DiffPD supports two types of contacts: a penalty-based model describing contact and friction forces and a complementarity-based model enforcing non-penetration conditions and static friction. We evaluate the performance of DiffPD and observe it is 4-19 times faster compared to the standard Newton's method in various applications including system identification, inverse design problems, trajectory optimization, and closed-loop control. We also apply DiffPD in a real-to-sim example with contact and collisions and show its capability of reconstructing a digital twin of real-world scenes.

Journal ArticleDOI
TL;DR: In this paper , a group contribution method (SoluteGC) was used to predict Abraham solute parameters, as well as a machine learning model (DirectML) to predict solvation free energy and enthalpy at 298 K. The results show that the DirectML model is superior to SoluteGC and SoluteML models for both predictions and can provide accuracy comparable to that of advanced quantum chemistry methods.
Abstract: We present a group contribution method (SoluteGC) and a machine learning model (SoluteML) to predict the Abraham solute parameters, as well as a machine learning model (DirectML) to predict solvation free energy and enthalpy at 298 K. The proposed group contribution method uses atom-centered functional groups with corrections for ring and polycyclic strain while the machine learning models adopt a directed message passing neural network. The solute parameters predicted from SoluteGC and SoluteML are used to calculate solvation energy and enthalpy via linear free energy relationships. Extensive data sets containing 8366 solute parameters, 20,253 solvation free energies, and 6322 solvation enthalpies are compiled in this work to train the models. The three models are each evaluated on the same test sets using both random and substructure-based solute splits for solvation energy and enthalpy predictions. The results show that the DirectML model is superior to the SoluteML and SoluteGC models for both predictions and can provide accuracy comparable to that of advanced quantum chemistry methods. Yet, even though the DirectML model performs better in general, all three models are useful for various purposes. Uncertain predicted values can be identified by comparing the three models, and when the 3 models are combined together, they can provide even more accurate predictions than any one of them individually. Finally, we present our compiled solute parameter, solvation energy, and solvation enthalpy databases (SoluteDB, dGsolvDBx, dHsolvDB) and provide public access to our final prediction models through a simple web-based tool, software packages, and source code.

Journal ArticleDOI
TL;DR: In this article, Li et al. used deep neural networks with a special convolutional training strategy to predict the residual life of a battery to a mean absolute percentage error of 6.46%, using only one cycle of testing.

Journal ArticleDOI
TL;DR: In this article, a nucleic acid amplification-free electrochemical biosensor based on four-way junction (4-WJ) hybridization is presented for the detection of SARS-CoV-2.

Journal ArticleDOI
TL;DR: In this paper, the authors review the prospects for quarkonium-production studies in proton and nuclear collisions accessible during the upcoming phases of the CERN Large Hadron Collider operation after 2021, including the ultimate high-luminosity phase, with increased luminosities compared to LHC runs 1 and 2.

Journal ArticleDOI
TL;DR: In this article , a state-of-the-art systematic review of academic papers and a Machine Learning-based analysis of grey literature on the social implications of Industry 4.0 are presented.

Journal ArticleDOI
TL;DR: In this paper , the deformation micro-mechanisms including texture-facilitated prismatic 〈a〉 slip activation together with the near-ideal slip transfer conditions across the α/β phase boundaries are found to be predominant in the strain localization regions.

Journal ArticleDOI
TL;DR: In this paper , a framework for integrating single-cell RNA-sequencing, epigenomic SNP-to-gene maps and genome-wide association study summary statistics to infer the underlying cell types and processes by which genetic variants influence disease.
Abstract: Genome-wide association studies provide a powerful means of identifying loci and genes contributing to disease, but in many cases, the related cell types/states through which genes confer disease risk remain unknown. Deciphering such relationships is important for identifying pathogenic processes and developing therapeutics. In the present study, we introduce sc-linker, a framework for integrating single-cell RNA-sequencing, epigenomic SNP-to-gene maps and genome-wide association study summary statistics to infer the underlying cell types and processes by which genetic variants influence disease. The inferred disease enrichments recapitulated known biology and highlighted notable cell-disease relationships, including γ-aminobutyric acid-ergic neurons in major depressive disorder, a disease-dependent M-cell program in ulcerative colitis and a disease-specific complement cascade process in multiple sclerosis. In autoimmune disease, both healthy and disease-dependent immune cell-type programs were associated, whereas only disease-dependent epithelial cell programs were prominent, suggesting a role in disease response rather than initiation. Our framework provides a powerful approach for identifying the cell types and cellular processes by which genetic variants influence disease.

Journal ArticleDOI
TL;DR: In this paper, a miniaturized split-phase half-turn transformer is demonstrated, which leverages the well-established parallelization benefit of employing multiple phases, as in a matrix transformer, with the dramatic reduction in copper loss associated with the relatively new Variable Inverter/Rectifier Transformer (VIRT) architecture.
Abstract: High step-down, high output current converters are required in many common and emerging applications, including data center server power supplies, point-of-load converters, and electric vehicle charging. Miniaturization is desirable but challenging owing to the high step-down transformer ubiquitously used in these converters. In this work, a miniaturized split-phase half-turn transformer is demonstrated, which leverages the well-established parallelization benefit of employing multiple phases, as in a matrix transformer, with the dramatic reduction in copper loss associated with the relatively new Variable Inverter/Rectifier Transformer (VIRT) architecture. While these techniques have been described in earlier studies, their combination has not been well explored. A detailed design procedure is described and is used to develop a 97.7% peak efficiency and 97.1% full-load efficiency prototype having a transformer that is 12%–36% smaller than best-in-class designs in the literature at the same power level while also being more efficient. This work showcases the miniaturization benefit of employing multiphase, fractional-turn transformers in high step-down, high output current applications and provides comprehensive guidance to designers interested in applying and extending these techniques.

Journal ArticleDOI
TL;DR: In this article, hybrid semi-conductive nanofillers with MoS2 two-dimensional (2-D) nanosheets and ZnO zero-dimensional nanoparticles in different ratios were fabricated by the wet chemical route and ultrasonic mixing.

Journal ArticleDOI
01 Apr 2022-Joule
TL;DR: Li et al. as discussed by the authors presented a machine learning-guided framework of sequential learning for manufacturing the process optimization of perovskite solar cells, which enabled a faster optimization in comparison with other conventional researcher-driven design-of-experiment methods.

Journal ArticleDOI
25 Feb 2022-Science
TL;DR: In this article , a unified theory of nanophotonic scintillators was developed to account for the key aspects of scintillation: energy loss by high-energy particles and light emission by non-equilibrium electrons in nanostructured optical systems.
Abstract: Bombardment of materials by high-energy particles often leads to light emission in a process known as scintillation. Scintillation has widespread applications in medical imaging, x-ray nondestructive inspection, electron microscopy, and high-energy particle detectors. Most research focuses on finding materials with brighter, faster, and more controlled scintillation. We developed a unified theory of nanophotonic scintillators that accounts for the key aspects of scintillation: energy loss by high-energy particles, and light emission by non-equilibrium electrons in nanostructured optical systems. We then devised an approach based on integrating nanophotonic structures into scintillators to enhance their emission, obtaining nearly an order-of-magnitude enhancement in both electron-induced and x-ray-induced scintillation. Our framework should enable the development of a new class of brighter, faster, and higher-resolution scintillators with tailored and optimized performance.

Journal ArticleDOI
TL;DR: In this article , the authors show that the intratumoural injection of recombinantly expressed cytokines bound tightly to the common vaccine adjuvant aluminium hydroxide (alum) (via ligand exchange between hydroxyls on the surface of alum and phosphoserine residues tagged to the cytokine by an alum-binding peptide) leads to weeks-long retention of the cytokines in the tumours, with minimal side effects.
Abstract: Anti-tumour inflammatory cytokines are highly toxic when administered systemically. Here, in multiple syngeneic mouse models, we show that the intratumoural injection of recombinantly expressed cytokines bound tightly to the common vaccine adjuvant aluminium hydroxide (alum) (via ligand exchange between hydroxyls on the surface of alum and phosphoserine residues tagged to the cytokine by an alum-binding peptide) leads to weeks-long retention of the cytokines in the tumours, with minimal side effects. Specifically, a single dose of alum-tethered interleukin-12 induced substantial interferon-γ-mediated T-cell and natural-killer-cell activities in murine melanoma tumours, increased tumour antigen accumulation in draining lymph nodes and elicited robust tumour-specific T-cell priming. Moreover, intratumoural injection of alum-anchored cytokines enhanced responses to checkpoint blockade, promoting cures in distinct poorly immunogenic syngeneic tumour models and eliciting control over metastases and distant untreated lesions. Intratumoural treatment with alum-anchored cytokines represents a safer and tumour-agnostic strategy to improving local and systemic anticancer immunity.

Journal ArticleDOI
TL;DR: For example, the authors showed that long highly expressed genes form open-ended transcription loops with polymerases moving along the loops and carrying nascent RNAs, similar to lampbrush loops and polytene puffs.
Abstract: Despite the well-established role of nuclear organization in the regulation of gene expression, little is known about the reverse: how transcription shapes the spatial organization of the genome. Owing to the small sizes of most previously studied genes and the limited resolution of microscopy, the structure and spatial arrangement of a single transcribed gene are still poorly understood. Here we study several long highly expressed genes and demonstrate that they form open-ended transcription loops with polymerases moving along the loops and carrying nascent RNAs. Transcription loops can span across micrometres, resembling lampbrush loops and polytene puffs. The extension and shape of transcription loops suggest their intrinsic stiffness, which we attribute to decoration with multiple voluminous nascent ribonucleoproteins. Our data contradict the model of transcription factories and suggest that although microscopically resolvable transcription loops are specific for long highly expressed genes, the mechanisms underlying their formation could represent a general aspect of eukaryotic transcription.

Journal ArticleDOI
01 Jan 2022-Matter
TL;DR: In this paper , a general inverse design framework was proposed to generate new crystals with user-defined formation energies, bandgap, thermoelectric (TE) power factor, and combinations thereof.

Journal ArticleDOI
TL;DR: In this article , it was shown that swimming starfish embryos spontaneously assemble into chiral crystals that span thousands of spinning organisms and persist for tens of hours, and that the formation, dynamics and dissolution of these living crystals are controlled by the hydrodynamic properties and the natural development of embryos.
Abstract: Active crystals are highly ordered structures that emerge from the self-organization of motile objects, and have been widely studied in synthetic1,2 and bacterial3,4 active matter. Whether persistent crystalline order can emerge in groups of autonomously developing multicellular organisms is currently unknown. Here we show that swimming starfish embryos spontaneously assemble into chiral crystals that span thousands of spinning organisms and persist for tens of hours. Combining experiments, theory and simulations, we demonstrate that the formation, dynamics and dissolution of these living crystals are controlled by the hydrodynamic properties and the natural development of embryos. Remarkably, living chiral crystals exhibit self-sustained chiral oscillations as well as various unconventional deformation response behaviours recently predicted for odd elastic materials5,6. Our results provide direct experimental evidence for how non-reciprocal interactions between autonomous multicellular components may facilitate non-equilibrium phases of chiral active matter. Experiments show that swimming starfish embryos spontaneously assemble into large chiral crystals that exhibit self-sustained chiral oscillations and unconventional deformation responses characteristic of odd elastic materials.

Book ChapterDOI
07 Jan 2022
TL;DR: In this paper , the authors discuss two widely deployed ways of trying to ameliorate morally costly disabilities, i.e., being excluded from interpersonal life is to be exempted from accountability, and vice versa.
Abstract: According to a popular line of thought, being excluded from interpersonal life is to be exempted from accountability, and vice versa. In ordinary life, this is most often illustrated by the treatment of people with serious psychological disorders. When people are excluded from valuable domains on the basis of their arbitrary characteristics (such as race and sex), they are discriminated against, prevented from receiving the benefits of participation in those domains for morally irrelevant reasons. Exemption from accountability—via exclusion from the interpersonal domain—seems to prevent exempted parties from receiving crucial human goods for morally irrelevant reasons. This chapter discusses two widely deployed ways of trying to ameliorate morally costly disabilities. Both fail to apply viably to various psychopathologies. The solution involves disentangling accountability and interpersonality in a way that also provides insights into our shared human nature.

Journal ArticleDOI
TL;DR: In this article , the authors present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States, which profiles 55 locations with at least six months of sampling from April 2020 to May 2021.
Abstract: Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Journal ArticleDOI
TL;DR: In this article , the discovery of a giant Josephson diode effect in Josephson junctions formed from a type-II Dirac semimetal, NiTe2, was reported.
Abstract: Cooper pairs in non-centrosymmetric superconductors can acquire finite centre-of-mass momentum in the presence of an external magnetic field. Recent theory predicts that such finite-momentum pairing can lead to an asymmetric critical current, where a dissipationless supercurrent can flow along one direction but not in the opposite one. Here we report the discovery of a giant Josephson diode effect in Josephson junctions formed from a type-II Dirac semimetal, NiTe2. A distinguishing feature is that the asymmetry in the critical current depends sensitively on the magnitude and direction of an applied magnetic field and achieves its maximum value when the magnetic field is perpendicular to the current and is of the order of just 10 mT. Moreover, the asymmetry changes sign several times with an increasing field. These characteristic features are accounted for by a model based on finite-momentum Cooper pairing that largely originates from the Zeeman shift of spin-helical topological surface states. The finite pairing momentum is further established, and its value determined, from the evolution of the interference pattern under an in-plane magnetic field. The observed giant magnitude of the asymmetry in critical current and the clear exposition of its underlying mechanism paves the way to build novel superconducting computing devices using the Josephson diode effect.

Journal ArticleDOI
TL;DR: In this article, the authors discuss recent advances in large-scale quantum mechanical (QM) modeling of biochemical systems that have reduced the cost of high-accuracy models and tradeoffs between sampling and accuracy have motivated modeling with molecular mechanics in a multiscale QM/MM or iterative approach.