Broadly neutralizing antibodies against SARS-CoV-2 variants

Antibody response plays a critical role in protective immunity against SARS-CoV-2 infection and disease progression[1–3].As the current COVID-19 pandemic continues to rage around the world,there is growing concern that new SARS-CoV-2 variants may emerge that are antigenically distinct from the prototype strain,rendering the current antibody and vaccine strategies ineffective[4–15].

Towards robust immune responses after heterologous COVID-19 vaccination and its application perspectives

The coronavirus disease 2019(COVID-19)pandemic,caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)[1],has seriously impacted the global health and economy.Effective vaccination,with homologous or heterologous prime-boost strategies,is the key to controlling the ongoing COVID-19 pandemic[2].Homologous vaccinations,which are the administration of the same type of COVID-19 vaccine,have been shown to be highly efficient in inducing robust immune responses[3–7].

Real- and momentum-indirect neutral and charged excitons in a multi-valley semiconductor

Excitons dominate the photonic and optoelectronic properties of a material.Although significant advancements exist in understanding various types of excitons,progress on excitons that are indirect in both real-and momentum-spaces is still limited.Here,we demonstrate the real-and momentum-indirect neutral and charged excitons(including their phonon replicas)in a multi-valley semiconductor of bilayer MoS_(2),by performing electric-field/doping-density dependent photoluminescence.Together with first-principles calculations,we uncover that the observed real-and momentum-indirect exciton involves electron/hole from K/Γvalley,solving the longstanding controversy of its momentum origin.Remarkably,the binding energy of real-and momentum-indirect charged exciton is extremely large(i.e.,~59 meV),more than twice that of real-and momentum-direct charged exciton(i.e.,~24 meV).The giant binding energy,along with the electrical tunability and long lifetime,endows real-and momentum-indirect excitons an emerging platform to study many-body physics and to illuminate developments in photonics and optoelectronics.

Clustering of quorum sensing colloidal particles

We propose a simple model of colloidal suspension,whereby individual particles change their diffusivity from high(hot)to low(cold),as the local concentration of their closest peers grows larger than a certain threshold.Such a non-reciprocal interactive mechanism is known in biology as quorum sensing.Upon tuning the parameters of the adopted quorum sensing protocol,the suspension is numerically shown to go through a variety of two-phase(hot and cold)configurations.This is an archetypal model with potential applications in robotics and social studies.

Indirect effects among biodiversity loss of mutualistic ecosystems

Drastic reduction in biodiversity has been a severe threat to ecosystems,which is exacerbated when losing few species leads to disastrous and even irreparable consequences.Therefore,revealing the mechanism underlying biodiversity loss is of uttermost importance.In this study,we show that abundant indirect interactions among mutualistic ecosystems are critical in determining species’status.Combining topological and ecological characteristics,we propose an indicator derived from a dynamic model to identify keystone species and quantify their influence,which outperforms widely-used indicators like degree in realistic and simulated networks.Furthermore,we demonstrate that networks with high modularity,heterogeneity,biodiversity,and less intimate interactions tend to have larger indirect effects,which are more amenable in predicting decline of biodiversity with the proposed indicator.These findings shed some light onto the influence of apposite biodiversities,paving the way from complex network theory to ecosystem protection and restoration.

Climate change reductions in lake ice cover duration and thickness help regulate the carbon sink potential of plateau type lakes

Lake ice changes in winter under the influence of global climate change,but how lake ice changes will regulate water gross primary productivity(GPP)and carbon sequestration capacity is still unclear.Here,we evaluated and analyzed the geographic spatial pattern and dynamic changes of lake ice and GPP on the Qinghai-Tibetan Plateau(QTP)in the past 20 years.Results show that lake ice duration on the QTP is 123.36±2.43 d on average,although longer for lakes at higher altitudes,of moderate size,and with shallower depths.Lake ice thickness is between 55-66 cm on average,and its GPP on the QTP is between 0.17-3.35 g C m^(-2)d^(-1).In the context of global climate change,reductions in lake ice cover duration and changes in ice thickness on the QTP increased phytoplankton GPP during the winter freeze period while decreasing Carbon dioxide(CO_(2))emissions during the melting period.

The electricity,industrial,and agricultural sectors under changing climate:Adaptation and mitigation in China

Climate change is a pressing global concern with far-reaching consequences that vary across sectors.Addressing the adverse impacts of climate change on various sectors is a challenging issue faced by countries worldwide,including China.It is imperative for China to address climate change to foster sustainable development and make meaningful contributions to global climate mitigation efforts.This paper presented a comprehensive analysis of the impacts of climate change on the electricity,agriculture,and industry sectors,which together account for over 80%of the greenhouse gas(GHG)emissions in China.Additionally,the strategies employed by these sectors to address climate change were reviewed,and potential future developments were explored.This review article could shine light on climate change practices and evidence-based policies aimed at addressing climate-related challenges across various sectors in China.

One year of COVID-19 vaccination

The year 2021 saw the development and deployment of COVID-19 vaccines at an unprecedented pace,which is a remarkable success in science and technology.COVID-19 vaccines based on different technology platforms have been given to billions of humans globally to minimize the infection and transmission of SARS-CoV-2,and most importantly,to end the COVID-19 pandemic.Here,we provide a snapshot of the current status and future challenge of COVID-19 vaccination after one year.

Information for Authors

Aims and scope National Science Open(NSO)is an open access bimonthly journal launched in 2022 that disseminates the most influential research of profound impact in advancing human knowledge,covering the full arc of natural sciences and engineering.Papers with transformative originality and pivotal development in multidisciplinary areas,or their distinctive fields are published in this journal with fair,rigorous review&fast production.Led by a global team of distinguished researchers,NSO also publishes timely,insightful commentaries and perspectives,engaging the interest of academic community and wider public.

Preface: physics of disorder, non-equilibrium and non-linearity

Amorphous materials,as indicated by the name,lack long-range crystalline order in their atomic arrangements.Amorphous materials are ubiquitous in nature and our daily life;examples include glasses,colloidal suspensions,granular matter,polymers,active matter and various biomaterials.However,our understanding of such systems lags significantly behind their ordered,crystalline counterparts.As a consequence,the study of amorphous materials is emerging as an exciting branch of modern physics.The essence of research in this field is evidenced by two recent events:the receipt of the 2021 Nobel Prize in physics by Giorgio Parisi for his groundbreaking contributions to the theory of disordered systems,in particular,spin glasses,and the celebration of the year 2022 as the International Year of Glass by United Nations.

Preface to the special topic on SAR microwave vision 3D imaging

Synthetic Aperture Radar(SAR)has significant applications in terrain mapping,environmental monitoring,disaster investigation and many other fields.Traditional SAR acquires two dimensional(2D)images of the observed scenarios,while interferometric SAR(InSAR)can acquire digital surface model(DSM,2.5D images).However,in areas with steep terrain changes or complex infrastructures,there will be severe layover phenomenon,resulting in many targets being difficult to detect and interpret.SAR 3D imaging can solve this problem and significantly enhance the target recognition and 3D modeling capabilities.It has become an important trend in the current development of SAR technology.Currently,SAR 3D imaging techniques mainly utilize multi-incident-angle observations to construct a synthetic aperture in the third dimension,so as to obtain the third dimensional resolution ability.However,dozens of tomographic flights or multi-channel observations are required,leading to long data acquisition cycles or extremely sophisticated radar systems,which restrict its popularization.

Compression induced crystal-to-glass transition in soft colloidal solids

Using colloidal particles with different thermosensitivities,we observe the transition from a crystalline solid to a dis-ordered glass by tuning the size mismatch of the constituent particles in quasi-two-dimensional configurations.The transition is clearly identifiable by the correlation functions of the orientational order parameters and its susceptibilities.Different from typical order-to-disorder transitions such as melting,where the underlying mechanism involves the diffusion of defects,the disordered phase in the crystal-to-glass transition grows via a nucleation process.The disordered clusters grow in size as the particle mismatch increases,and eventually percolate the whole system,which signifies the qualitative change from an ordered crystal to a disordered glass.

2T1C DRAM based on semiconducting MoS_(2) and semimetallic graphene for in-memory computing

In-memory computing is an alternative method to effectively accelerate the massive data-computing tasks of artificial intelligence(AI)and break the memory wall.In this work,we propose a 2T1C DRAM structure for in-memory computing.It integrates a monolayer graphene transistor,a monolayer MoS_(2)transistor,and a capacitor in a two-transistor-onecapacitor(2T1C)configuration.In this structure,the storage node is in a similar position to that of one-transistor-one-capacitor(1T1C)dynamic random-access memory(DRAM),while an additional graphene transistor is used to accomplish the nondestructive readout of the stored information.Furthermore,the ultralow leakage current of the MoS_(2)transistor enables the storage of multi-level voltages on the capacitor with a long retention time.The stored charges can effectually tune the channel conductance of the graphene transistor due to its excellent linearity so that linear analog multiplication can be realized.Because of the almost unlimited cycling endurance of DRAM,our 2T1C DRAM has great potential for in situ training and recognition,which can significantly improve the recognition accuracy of neural networks.

Scalable fabrication of magnetic soft microfiberbots for robotic embolization

Intracranial tumors and aneurysms rank among the foremost causes of mortality globally,presenting a significant public health challenge[1,2].Traditional embolization techniques,which involve the manual navigation of slender catheters and guidewires through complex vascular networks,are highly dependent on the clinician's expertise and the mechanical capabilities of the instruments used.

Preface:special topic on novel optoelectronic devices

The research and development(R&D)in silicon or III/V photonics are booming and emerging as the mainstream platforms for large-scale photonic integration circuits,which offer the well-established advantages of scalable chip-wise integration with low cost at high volume and high yield,following the standard complementary metal oxide semiconductor fabrication processes in the microelectronics industry.However,the co-integration of electronics with photonics is critical for fully exploiting the high bandwidth,reducing power consumption,as well as achieving more compact footprint and lower cost.Optoelectronic devices with novel co-integration schemes and new materials with further improved functionalities are urgently needed to push beyond the limitations posed by the intrinsic material capabilities and speed restrictions at the electro-optical interfaces.Recently,considerable breakthroughs revived our understanding of these fields,providing both opportunities and challenges in this exciting area.

Metagenomic insights into the variation of bacterial communities and potential pathogenic bacteria in drinking water treatment and distribution systems

High-throughput sequencing of 16S rRNA gene amplicons was conducted to characterize the changing patterns of bacterial community and potential pathogens in full-scale drinking water treatment and distribution systems.Results showed that Actinobacteria was the predominant phylum in source water,while Proteobacteria dominated after chlorine disinfection and its relative abundance increased from 40.88%±9.45%to 67.86%±27.10%.The genera Pseudarthrobacter,Arenimonas,and Limnohabitans were effectively removed by chlorination,while Phreatobacter,Undibacterium,Pseudomonas,and Sphingomonas within the Proteobacteria phylum were greatly enriched after chlorination.Metagenomic analyses revealed the occurrence of 56 species of potential pathogenic bacteria within 17 genera in drinking water,mainly including Pseudomonas fluorescens and five mycobacteria species,which were also persistent in tap water samples.The bacteria were found to be involved in various pathways,among which considerable groups were related to human diseases,including infectious diseases and even cancers.

Integrated optoelectronics with two-dimensional materials

As we enter the post-Moore era,heterogeneous optoelectronic integrated circuits(OEICs)are attracting significant attention as an alternative approach to scaling to smaller-sized transistors.Two-dimensional(2D)materials,offering a range of intriguing optoelectronic properties as semiconductors,semimetals,and insulators,provide great potential for developing nextgeneration heterogeneous OEICs.For instance,Fermi levels of 2D materials can be tuned by applying electrical voltages,while their atomically thin geometries are inherently suited for the fabrication of planar devices without suffering from lattice mismatch.Since the first graphene-on-silicon OEICs were demonstrated in 2011,2D-material heterogeneous OEICs have significantly progressed.To date,researchers have a better understanding of the importance of interface states on the optical properties of chip-integrated 2D materials.Moreover,there has been impressive progress towards the use of 2D materials for waveguide-integrated lasers,modulators,and photodetectors.In this review,we summarize the history,status,and trend of integrated optoelectronics with 2D materials.

A machine-learning-enabled approach for bridging multiscale simulations of CNTs/PDMS composites

Benefitting from the interlaced networking structure of carbon nanotubes(CNTs),the composites of CNTs/polydimethylsiloxane(PDMS)have found extensive applications in wearable electronics.While hierarchical multiscale simulation frameworks exist to optimize the structure parameters,their wide applications were hindered by the high computational cost.In this study,a machine learning model based on the artificial neural networks(ANN)embedded graph attention network,termed as AGAT,was proposed.The datasets collected from the micro-scale and the macro-scale simulations are utilized to train the model.The ANN layer within the model framework is trained to pass the information from micro-scale to macro-scale,while the whole model is aimed to predict the electro-mechanical behavior of the CNTs/PDMS composites.By comparing the AGAT model with the original multiscale simulation results,the data-driven strategy is shown to be promising with high accuracy,demonstrating the potential of the machine-learning-enabled approach for the structure optimization of CNT-based composites.

Two-dimensional transition metal dichalcogenides for post-silicon electronics

Rapid advancements in information technology push the explosive growth in data volume,requiring greater computing-capability logic circuits.However,conventional computing-capability improving technology,which mainly relies on increasing transistor number,encounters a significant challenge due to the weak field-effect characteristics of bulk siliconbased semiconductors.Still,the ultra-thin layered bodies of two-dimensional transition metal dichalcogenides(2D-TMDCs)materials enable excellent field-effect characteristics and multiple gate control ports,facilitating the integration of the functions of multiple transistors into one.Generally,the computing-capability improvement of the transistor cell in logic circuits will greatly alleviate the challenge in transistor numbers.In other words,one can only use a small number,or even just one,2DTMDCs-based transistors to conduct the sophisticated logic operations that have to be realized by using many traditional transistors.In this review,from material selection,device structure optimization,and circuit architecture design,we discuss the developments,challenges,and prospects for 2D-TMDCs-based logic circuits.

Supramolecular assembly-derived carbon-nitrogen-based functional materials for photo/electrochemical applications: progress and challenges

Supramolecular chemistry during the synthesis of carbon-nitrogen-based materials has recently experienced a renaissance in the arena of photocatalysis and electrocatalysis.In this review,we start with the discussion of supramolecular assemblies-derived carbon-nitrogen-based materials’regulation from the aspect of morphology,chemical composition,and micro/nanostructural control.Afterwards the recent advances of these materials in energy and environment related applications,including degradation of pollutants,water splitting,oxygen reduction reactions,CO_(2) reduction reactions along with organic synthesis are summarized.The correlations between the structural features and physicochemical properties of the carbonnitrogen-based materials and the specific catalytic activity are discussed in depth.By highlighting the opportunities and challenges of supramolecular assembly strategies,we attempt an outlook on possible future developments for highly efficient carbon-based photo/electrocatalysts.