Enhanced Biodegradation of High-Salinity and Low- Temperature Crude-Oil Wastewater by Immobilized Crude-Oil Biodegrading Microbiota

High salt and low temperature are the bottlenecks for the remove of oil contaminants by enriched crude-oil degrading microbiota in Liaohe Estuarine Wetland(LEW),China.To improve the performance of crude-oil removal,microbiota was further immobilized by two methods,i.e.,sodium alginate(SA),and polyvinyl alcohol and sodium alginate(PVA+SA).Results showed that the crude oil was effectively removed by the enrichment with an average degrading ratio of 19.42-31.45 mg(L d)^(−1).The optimal inoculum size for the n-alkanes removal was 10%and 99.89%.Some members of genera Acinetobacter,Actinophytocola,Aquabac-terium,Dysgonomonas,Frigidibacter,Sphingobium,Serpens,and Pseudomonas dominated in crude-oil degrading microflora.Though the removal efficiency was lower than free bacteria when the temperature was 15℃,SA and PVA+SA immobilization im-proved the resistance to salinity.The composite crude-oil degrading microbiota in this study demonstrated a perspective potential for crude oil removal from surface water under high salinity and low temperature conditions.

Alkyl dimethyl betaine activates the low-temperature collection capacity of sodium oleate for scheelite

The impact of alkyl dimethyl betaine (ADB) on the collection capacity of sodium oleate (NaOl) at low temperatures was evaluated using flotation tests at various scales. The low-temperature synergistic mechanism of ADB and NaOl was explored by infrared spectroscopy, X-ray photoelectron spectroscopy, surface tension measurement, foam performance test, and flotation reagent size measurement.The flotation tests revealed that the collector mixed with octadecyl dimethyl betaine (ODB) and NaOl in a mass ratio of 4:96 exhibited the highest collection capacity. The combined collector could increase the scheelite recovery by 3.48% at low temperatures of 8–12℃. This is particularly relevant in the Luanchuan area, which has the largest scheelite concentrate output in China. The results confirmed that ODB enhanced the collection capability of NaOl by improving the dispersion and foaming performance. Betaine can be introduced as an additive to NaOl to improve the recovery of scheelite at low temperatures.

Low-energy-consumption temperature swing system for CO_(2) capture by combining passive radiative cooling and solar heating

Temperature-swing adsorption(TSA)is an effective technique for CO_(2) capture,but the temperature swing procedure is energy-intensive.Herein,we report a low-energy-consumption system by combining passive radiative cooling and solar heating for the uptake of CO_(2) on commercial activated carbons(CACs).During adsorption,the adsorbents are coated with a layer of hierarchically porous poly(vinylidene fluoride-co-hexafluoropropene)[P(VdF-HFP)HP],which cools the adsorbents to a low temperature under sunlight through radiative cooling.For desorption,CACs with broad absorption of the solar spectrum are exposed to light irradiation for heating.The heating and cooling processes are completely driven by solar energy.Adsorption tests under mimicked sunlight using the CACs show that the performance of this system is comparable to that of the traditional ones.Furthermore,under real sunlight irradiation,the adsorption capacity of the CACs can be well maintained after multiple cycles.The present work may inspire the development of new temperature swing procedures with little energy consumption.

Accelerated Sequential Deposition Reaction via Crystal Orientation Engineering for Low-Temperature,High-Efficiency Carbon-Electrode CsPbBr_(3) Solar Cells

Low-temperature,ambient processing of high-quality CsPbBr_(3)films is demanded for scalable production of efficient,low-cost carbon-electrode perovskite solar cells(PSCs).Herein,we demonstrate a crystal orientation engineering strategy of PbBr_(2)precursor film to accelerate its reaction with CsBr precursor during two-step sequential deposition of CsPbBr_(3)films.Such a novel strategy is proceeded by adding CsBr species into PbBr_(2)precursor,which can tailor the preferred crystal orientation of PbBr_(2)film from[020]into[031],with CsBr additive staying in the film as CsPb_(2)Br_(5)phase.Theoretical calculations show that the reaction energy barrier of(031)planes of PbBr_(2)with CsBr is lower about 2.28 eV than that of(O2O)planes.Therefore,CsPbBr_(3)films with full coverage,high purity,high crystallinity,micro-sized grains can be obtained at a low temperature of 150℃.Carbon-electrode PSCs with these desired CsPbBr_(3)films yield the record-high efficiency of 10.27%coupled with excellent operation stability.Meanwhile,the 1 cm^(2)area one with the superior efficiency of 8.00%as well as the flexible one with the champion efficiency of 8.27%and excellent mechanical bending characteristics are also achieved.

On-Chip Micro Temperature Controllers Based on Freestanding Thermoelectric Nano Films for Low-Power Electronics

Multidimensional integration and multifunctional com-ponent assembly have been greatly explored in recent years to extend Moore’s Law of modern microelectronics.However,this inevitably exac-erbates the inhomogeneity of temperature distribution in microsystems,making precise temperature control for electronic components extremely challenging.Herein,we report an on-chip micro temperature controller including a pair of thermoelectric legs with a total area of 50×50μm^(2),which are fabricated from dense and flat freestanding Bi2Te3-based ther-moelectric nano films deposited on a newly developed nano graphene oxide membrane substrate.Its tunable equivalent thermal resistance is controlled by electrical currents to achieve energy-efficient temperature control for low-power electronics.A large cooling temperature difference of 44.5 K at 380 K is achieved with a power consumption of only 445μW,resulting in an ultrahigh temperature control capability over 100 K mW^(-1).Moreover,an ultra-fast cooling rate exceeding 2000 K s^(-1) and excellent reliability of up to 1 million cycles are observed.Our proposed on-chip temperature controller is expected to enable further miniaturization and multifunctional integration on a single chip for microelectronics.

Temperature inversion enables superior stability for low-temperature Zn-ion batteries

It is challenging for aqueous Zn-ion batteries(ZIBs)to achieve comparable low-temperature(low-T)performance due to the easy-frozen electrolyte and severe Zn dendrites.Herein,an aqueous electrolyte with a low freezing point and high ionic conductivity is proposed.Combined with molecular dynamics simulation and multi-scale interface analysis(time of flight secondary ion mass spectrometry threedimensional mapping and in-situ electrochemical impedance spectroscopy method),the temperature independence of the V_(2)O_(5)cathode and Zn anode is observed to be opposite.Surprisingly,dominated by the solvent structure of the designed electrolyte at low temperatures,vanadium dissolution/shuttle is significantly inhibited,and the zinc dendrites caused by this electrochemical crosstalk are greatly relieved,thus showing an abnormal temperature inversion effect.Through the disclosure and improvement of the above phenomena,the designed Zn||V_(2)O_(5)full cell delivers superior low-T performance,maintaining almost 99%capacity retention after 9500 cycles(working more than 2500 h)at-20°C.This work proposes a kind of electrolyte suitable for low-T ZIBs and reveals the inverse temperature dependence of the Zn anode,which might offer a novel perspective for the investigation of low-T aqueous battery systems.

Origin of the presence/absence variation of the LTIA1/LTIA2 mini-ribonucleaseⅢgenes required for low-temperature growth in rice

A rice low temperature-induced albino variant was determined by the recessive ltia1 and ltia2 genes.LTIA1 and LTIA2 encode highly conserved mini-ribonucleasesⅢlocated in chloroplasts and expressed in aerial parts of the plant.At low temperature,LTIA1 and LTIA2 redundantly affect chlorophyll levels,non-photochemical quenching,photosynthetic quantum yield of PSⅡand seedling growth.LTIA1 and LTIA2 proteins are involved in splicing of atp F and the biogenesis of 16S and 23S rRNA in chloroplasts.Presence/absence variation of LTIA1,the ancestral copy,was found only in japonica but that of LTIA2 in all rice subgroups.Accessions with LTIA2 presence tended to be distributed more remote from the equator compared to those with LTIA2 absence.LTIA2 duplicated from LTIA1 at the early stage of divergence of the AA genome Oryza species but deleted againin O.nivara.In cultivated rice,absence of LTIA2 is derived from O.nivara.LTIA1 absence occurred more recently in japonica.

Current optimization-based control of dual three-phase PMSM for low-frequency temperature swing reduction

In this paper,a control scheme based on current optimization is proposed for dual three-phase permanent-magnet synchronous motor(DTP-PMSM)drive to reduce the low-frequency temperature swing.The reduction of temperature swing can be equivalent to reducing maximum instantaneous phase copper loss in this paper.First,a two-level optimization aiming at minimizing maximum instantaneous phase copper loss at each electrical angle is proposed.Then,the optimization is transformed to a singlelevel optimization by introducing the auxiliary variable for easy solving.Considering that singleobjective optimization trades a great total copper loss for a small reduction of maximum phase copper loss,the optimization considering both instantaneous total copper loss and maximum phase copper loss is proposed,which has the same performance of temperature swing reduction but with lower total loss.In this way,the proposed control scheme can reduce maximum junction temperature by 11%.Both simulation and experimental results are presented to prove the effectiveness and superiority of the proposed control scheme for low-frequency temperature swing reduction.

Record-breaking High-temperature Outlook for 2023: An Assessment Based on the China Global Merged Temperature(CMST) Dataset

According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

A bHLH transcription factor,CsSPT,regulates high-temperature resistance in cucumber

High-temperature stress threatens the growth and yield of crops. Basic helix-loop-helix(bHLH) transcription factors(TFs) have been shown to play important roles in regulating high-temperature resistance in plants. However, the bHLH TFs responsible for high-temperature tolerance in cucumbers have not been identified. We used transcriptome profiling to screen the high temperature-responsive candidate bHLH TFs in cucumber. Here, we found that the expression of 75 CsbHLH genes was altered under high-temperature stress. The expression of the CsSPT gene was induced by high temperatures in TT(Thermotolerant) cucumber plants. However, the Csspt mutant plants obtained by the CRISPR-Cas9 system showed severe thermosensitive symptoms, including wilted leaves with brown margins and reduced root density and cell activity.The Csspt mutant plants also exhibited elevated H_(2)O_(2) levels and down-regulated photosystem-related genes under normal conditions.Furthermore, there were high relative electrolytic leakage(REC), malondialdehyde(MDA), glutathione(GSH), and superoxide radical(O_(2)^(·-)) levels in the Csspt mutant plants, with decreased Proline content after the high-temperature treatment. Transcriptome analysis showed that the photosystem and chloroplast activities in Csspt mutant plants were extremely disrupted by the high-temperature stress compared with wildtype(WT) plants. Moreover, the plant hormone signal transduction, as well as MAPK and calcium signaling pathways were activated in Csspt mutant plants under high-temperature stress. The HSF and HSP family genes shared the same upregulated expression patterns in Csspt and WT plants under high-temperature conditions. However, most bHLH, NAC, and bZIP family genes were significantly down-regulated by heat in Csspt mutant plants. Thus, these results demonstrated that CsSPT regulated the high-temperature response by recruiting photosynthesis components, signaling pathway molecules, and transcription factors. Our results provide important insights into the heat response mechanism of CsSPT in cucumber and its potential as a target for breeding heat-resistant crops.

Competitive oxidation behavior of Ni-based superalloy GH4738 at extreme temperature

A high thrust-to-weight ratio poses challenges to the high-temperature performance of Ni-based superalloys. The oxidation behavior of GH4738 at extreme temperatures has been investigated by isothermal and non-isothermal experiments. As a result of the competitive diffusion of alloying elements, the oxide scale included an outermost porous oxide layer (OOL), an inner relatively dense oxide layer (IOL), and an internal oxide zone (IOZ), depending on the temperature and time. A high temperature led to the formation of large voids at the IOL/IOZ interface. At 1200℃, the continuity of the Cr-rich oxide layer in the IOL was destroyed, and thus, spallation occurred. Extension of oxidation time contributed to the size of Al-rich oxide particles with the increase in the IOZ. Based on this finding,the oxidation kinetics of GH4738 was discussed, and the corresponding oxidation behavior at 900-1100℃ was predicted.

Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Comprehensive analyses of the proteome and ubiquitome revealed mechanism of high temperature accelerating petal abscission in tree peony

Tree peony(Paeonia suffruticosa Andrews)is a well-known ornamental plant with high economic value,but the short fluorescence is a key obstacle to its ornamental value and industry development.High temperature accelerates flower senescence and abscission,but the associated mechanisms are poorly understood.In this study,the tandem mass tag(TMT)proteome and label-free quantitative ubiquitome from tree peony cut flowers treated with 20℃for 0 h(RT0),20℃or 28℃for 60 h(RT60 or HT60)were examined based on morphological observation,respectively.Totally,6970 proteins and 1545 lysine ubiquitinated(Kub)sites in 844 proteins were identified.Hydrophilic residues(such as glutamate and aspartate)neighboring the Kub sites were in preference,and 36.01%of the Kub sites were located on the protein surface.The differentially expressed proteins(DEPs)and Kub-DEPs in HT60 vs RT60 were mainly enriched in ribosomal protein,protein biosynthesis,secondary metabolites biosynthesis,flavonoid metabolism,carbohydrate catabolism,and auxin biosynthesis and signaling revealed by GO and KEGG analysis,accompanying the increase of endogenous abscisic acid(ABA)accumulation and decrease of endogenous indoleacetic acid(IAA)level.Additionally,the expression patterns of six enzymes(SAMS,ACO,YUC,CHS,ANS and PFK)putatively with Kub modifications were analyzed by proteome and real-time quantitative RT-PCR.The cell-free degradation assays showed PsSAMS and PsACO proteins could be degraded via the 26 S proteasome system in tree peony flowers.Finally,a working model was proposed for the acceleration of flower senescence and abscission by high temperature.In summary,all results contributed to understanding the mechanism of flower senescence induced by high temperature and prolonging fluorescence in tree peony.

Revealing the key role of non-solvating diluents for fast-charging and low temperature Li-ion batteries

Fast-charging and low temperature operation are of vital importance for the further development of lithium-ion batteries(LIBs),which is hindered by the utilization of conventional carbonate-based electrolytes due to their slow kinetics,narrow operating temperature and voltage range.Herein,an acetonitrile(AN)-based localized high-concentration electrolyte(LHCE)is proposed to retain liquid state and high ionic conductivity at ultra-low temperatures while possessing high oxidation stability.We originally reveal the excellent thermal shielding effect of non-solvating diluent to prevent the aggregation of Li^(+) solvates as temperature drops,maintaining the merits of fast Li transport and facile desolvation as at room temperature,which bestows the graphite electrode with remarkable low temperature performance(264 mA h g^(-1) at-20 C).Remarkably,an extremely high capacity retention of 97%is achieved for high-voltage high-energy graphite||NCM batteries after 250 cycles at-20 C,and a high capacity of 110 mA h g^(-1)(71%of its room-temperature capacity)is retained at-30°C.The study unveils the key role of the non-solvating diluents and provides instructive guidance in designing electrolytes towards fast-charging and low temperature LIBs.

Electrolyte Design for Low‑Temperature Li‑Metal Batteries:Challenges and Prospects

Electrolyte design holds the greatest opportunity for the development of batteries that are capable of sub-zero temperature operation.To get the most energy storage out of the battery at low temperatures,improvements in electrolyte chemistry need to be coupled with optimized electrode materials and tailored electrolyte/electrode interphases.Herein,this review critically outlines electrolytes’limiting factors,including reduced ionic conductivity,large de-solvation energy,sluggish charge transfer,and slow Li-ion transportation across the electrolyte/electrode interphases,which affect the low-temperature performance of Li-metal batteries.Detailed theoretical derivations that explain the explicit influence of temperature on battery performance are presented to deepen understanding.Emerging improvement strategies from the aspects of electrolyte design and electrolyte/electrode interphase engineering are summarized and rigorously compared.Perspectives on future research are proposed to guide the ongoing exploration for better low-temperature Li-metal batteries.

Attribution of Biases of Interhemispheric Temperature Contrast in CMIP6 Models

One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.

Room Temperature Synthesis of Vertically Aligned Amorphous Ultrathin NiCo-LDH Nanosheets Bifunctional Flexible Supercapacitor Electrodes

Developing a simple scalable method to fabricate electrodes with high capacity and wide voltage range is desired for the real use of electrochemical supercapacitors.Herein,we synthesized amorphous NiCo-LDH nanosheets vertically aligned on activated carbon cloth substrate,which was in situ transformed from Co-metal-organic framework materials nano-columns by a simple ion exchange process at room temperature.Due to the amorphous and vertically aligned ultrathin structure of NiCo-LDH,the NiCo-LDH/activated carbon cloth composites present high areal capacities of 3770 and 1480 mF cm^(-2)as cathode and anode at 2 mA cm^(-2),and 79.5%and 80%capacity have been preserved at 50 mA cm^(-2).In the meantime,they all showed excellent cycling performance with negligible change after>10000 cycles.By fabricating them into an asymmetric supercapacitor,the device achieves high energy densities(5.61 mWh cm^(-2)and 0.352 mW cm^(-3)).This work provides an innovative strategy for simplifying the design of supercapacitors as well as providing a new understanding of improving the rate capabilities/cycling stability of NiCo-LDH materials.

Analysis of piezoelectric semiconductor fibers under gradient temperature changes

Piezoelectric semiconductors(PSs)possess both semiconducting properties and piezoelectric coupling effects,making them optimal building blocks for semiconductor devices.PS fiber-like structures have wide applications in multi-functional semiconductor devices.In this paper,a one-dimensional(1D)theoretical model is established to describe the piezotronic responses of a PS fiber under gradient temperature changes.The theoretical model aims to explain the mechanism behind the resistance change caused by such gradient temperature changes.Numerical results demonstrate that a gradient temperature change significantly affects the physical fields within the PS fiber,and can induce changes in its surface resistance.It provides important theoretical guidance on the development of piezotronic devices that are sensitive to temperature effects.

Deep learning-assisted common temperature measurement based on visible light imaging

Real-time,contact-free temperature monitoring of low to medium range(30℃-150℃)has been extensively used in industry and agriculture,which is usually realized by costly infrared temperature detection methods.This paper proposes an alternative approach of extracting temperature information in real time from the visible light images of the monitoring target using a convolutional neural network(CNN).A mean-square error of<1.119℃was reached in the temperature measurements of low to medium range using the CNN and the visible light images.Imaging angle and imaging distance do not affect the temperature detection using visible optical images by the CNN.Moreover,the CNN has a certain illuminance generalization ability capable of detection temperature information from the images which were collected under different illuminance and were not used for training.Compared to the conventional machine learning algorithms mentioned in the recent literatures,this real-time,contact-free temperature measurement approach that does not require any further image processing operations facilitates temperature monitoring applications in the industrial and civil fields.