Energy dissipation mechanism and ballistic characteristic optimization in foam sandwich panels against spherical projectile impact

This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels(FSP)under high-velocity impact using the explicit non-linear finite element method.Based on the geometric topology of the FSP system,three FSP configurations with the same areal density are derived,namely multi-layer,gradient core and asymmetric face sheet,and three key structural parameters are identified:core thickness(t_(c)),face sheet thickness(t_(f))and overlap face/core number(n_(o)).The ballistic performance of the FSP system is comprehensively evaluated in terms of the ballistic limit velocity(BLV),deformation modes,energy dissipation mechanism,and specific penetration energy(SPE).The results show that the FSP system exhibits a significant configuration dependence,whose ballistic performance ranking is:asymmetric face sheet>gradient core>multi-layer.The mass distribution of the top and bottom face sheets plays a critical role in the ballistic resistance of the FSP system.Both BLV and SPE increase with tf,while the raising tcor noleads to an increase in BLV but a decrease in SPE.Further,a face-core synchronous enhancement mechanism is discovered by the energy dissipation analysis,based on which the ballistic optimization procedure is also conducted and a design chart is established.This study shed light on the anti-penetration mechanism of the FSP system and might provide a theoretical basis for its engineering application.

Reconfigurable memlogic long wave infrared sensing with superconductors

Optical sensors with in-cell logic and memory capabilities offer new horizons in realizing machine vision beyond von Neumann architectures and have been attempted with two-dimensional materials,memristive oxides,phasechanging materials etc.Noting the unparalleled performance of superconductors with both quantum-limited optical sensitivities and ultra-wide spectrum coverage,here we report a superconducting memlogic long-wave infrared sensor based on the bistability in hysteretic superconductor-normal phase transition.Driven cooperatively by electrical and optical pulses,the device offers deterministic in-sensor switching between resistive and superconducting(hence dissipationless)states with persistence>105 s.This results in a resilient reconfigurable memlogic system applicable for,e.g.,encrypted communications.Besides,a high infrared sensitivity at 12.2μm is achieved through its in-situ metamaterial perfect absorber design.Our work opens the avenue to realize all-in-one superconducting memlogic sensors,surpassing biological retina capabilities in both sensitivity and wavelength,and presents a groundbreaking opportunity to integrate visional perception capabilities into superconductor-based intelligent quantum machines.

Remote sensing of soil degradation:Pro gress andperspective

Soils constitute one of the most critical natural resources and maintaining their health is vital for agricultural development and ecological sustainability,providing many essential ecosystem services.Driven by climatic variations and anthropogenic activities,soil degradation has become a global issue that seriously threatens the ecological environment and food security.Remote sensing(RS)technologies have been widely used to investigate soil degradation as it is highly efficient,time-saving,and broad-scope.This review encompasses recent advances and the state-of-the-art of ground,proximal,and novel Rs techniques in soil degradation-related studies.We reviewed the RS-related indicators that could be used for monitoring soil degradation-related properties.The direct indicators(mineral composition,organic matter,surface roughness,and moisture content of soil)and indirect proxies(vegetation condition and land use/land cover change)for evaluating soil degradation were comprehensively summarized.The results suggest that these above indicators are effective for monitoring soil degradation,however,no indicators system has been established for soil degradation monitoring to date.We also discussed the RS's mechanisms,data,and methods for identifying specific soil degradation-related phenomena(e.g.,soil erosion,salinization,desertification,and contamination).We investigated the potential relations between soil degradation and Sustainable Development Goals(SDGs)and also discussed the challenges and prospective use of RS for assessing soil degradation.To further advance and optimize technology,analysis and retrieval methods,we identify critical future research needs and directions:(1)multi-scale analysis of soil degradation;(2)availability of RS data;(3)soil degradation process modelling and prediction;(4)shared soil degradation dataset;(5)decision support systems;and(6)rehabilitation of degraded soil resource and the contribution of RS technology.Because it is difficult to monitor or measure all soil properties in the large scale,remotely sensed characterization of soil properties related to soil degradation is particularly important.Although it is not a silver bullet,RS provides unique benefits for soil degradation-related studies from regional to global scales.

Surface water and aerosol spatiotemporal dynamics and influence mechanisms over drylands

Under the background of global warming and excessive human activities,much surface water in drylands is experiencing rapid degradation or shrinkage in recent years.The shrinkage of surface water,especially the degradation of lakes and their adjacent wetlands in drylands,may lead to the emergence of new salt dust storm hotspots,which causes greater danger.In this paper,based on high spatial resolution global surface water(GSW)and multiangle implementation of atmospheric correction(MAIAC)AOD data,we systematically analyze the dynamic characteristics of surface water and aerosols in typical drylands(Central Asia,CA)between 2000 and 2018.Simultaneously,combined with auxiliary environment variables,we explore the driving mechanisms of surface water on the regional salt/sand aerosols on different spatial scales.The results show that the seasonal surface water features an increasing trend,especially a more dramatic increase after 2015,and the permanent surface water indicates an overall decrease,with nearly 54.367%at risk of receding and drying up.In typical lakes(Aral Sea and Ebinur Lake),the interannual change feature of the surface water area(WA)is that a continuous decrease during the study period occurs in Aral Sea area,yet a significant improvement has occurred in Ebinur Lake after 2015,and the degradation of Ebinur Lake takes place later and its recovery earlier than Aral Sea.The aerosol optical depth(AOD)in CA shows obvious seasonal variation,with the largest in spring(0.192±0173),next in summer(0.169±0.106),and the smallest in autumn(0.123±0.065).The interannual variation of AOD exhibits an increase from 2000 to 2018 in CA,with high AOD areas mainly concentrated in the Taklamakan Desert and some lake beds resulting from lake degradation,including Aral Sea and Ebinur Lake.The AOD holds a similar trend between Aral Sea and Ebinur Lake on an interannual scale.And the AOD over Ebinur Lake is lower than that over Aral Sea in magnitude and lags behind in reaching the peak compared with Aral Sea.The WA change can significantly affect aerosol variation directly or indirectly on the aerosol load or mode size,but there are obvious differences in the driving mechanisms,acting paths,and influence magnitude of WA on aerosols on different spatial scales.In addition,the increase of WA can significantly directly suppress the increase ofÅngström exponent(AE),and the effects of WA on AOD are realized majorly by an indirect approach.From the typical lake perspective,the effects of WA on aerosol in Aral Sea are achieved via an indirect path;and the decrease of WA can indirectly promote the AOD rise,and directly stimulate the AE growth in Ebinur Lake.