Healable and conductive sulfur iodide for solid-state Li-S batteries.

Solid-state Li-S batteries (SSLSBs) are made of low-cost and abundant materials free of supply chain concerns. Owing to their high theoretical energy densities, they are highly desirable for electric vehicles1-3. However, the development of SSLSBs has been historically plagued by the insulating nature of sulfur4,5 and the poor interfacial contacts induced by its large volume change during cycling6,7, impeding charge transfer among different solid components. Here we report an S9.3I molecular crystal with I2 inserted in the crystalline sulfur structure, which shows a semiconductor-level electrical conductivity (approximately 5.9 × 10-7 S cm-1) at 25 °C; an 11-order-of-magnitude increase over sulfur itself. Iodine introduces new states into the band gap of sulfur and promotes the formation of reactive polysulfides during electrochemical cycling. Further, the material features a low melting point of around 65 °C, which enables repairing of damaged interfaces due to cycling by periodical remelting of the cathode material. As a result, an Li-S9.3I battery demonstrates 400 stable cycles with a specific capacity retention of 87%. The design of this conductive, low-melting-point sulfur iodide material represents a substantial advancement in the chemistry of sulfur materials, and opens the door to the practical realization of SSLSBs.

Inorganic carbon is overlooked in global soil carbon research: A bibliometric analysis.

Soils are a major player in the global carbon (C) cycle and climate change by functioning as a sink or a source of atmospheric carbon dioxide (CO2). The largest terrestrial C reservoir in soils comprises two main pools: organic (SOC) and inorganic C (SIC), each having distinct fates and functions but with a large disparity in global research attention. This study quantified global soil C research trends and the proportional focus on SOC and SIC pools based on a bibliometric analysis and raise the importance of SIC pools fully underrepresented in research, applications, and modeling. Studies on soil C pools started in 1905 and has produced over 47,000 publications (>1.7 million citations). Although the global C stocks down to 2 m depth are nearly the same for SOC and SIC, the research has dominantly examined SOC (>96 % of publications and citations) with a minimal share on SIC (<4%). Approximately 40 % of the soil C research was related to climate change. Despite poor coverage and publications, the climate change-related research impact (citations per document) of SIC studies was higher than that of SOC. Mineral associated organic carbon, machine learning, soil health, and biochar were the recent top trend topics for SOC research (2020-2023), whereas digital soil mapping, soil properties, soil acidification, and calcite were recent top trend topics for SIC. SOC research was contributed by 151 countries compared to 88 for SIC. As assessed by publications, soil C research was mainly concentrated in a few countries, with only 9 countries accounting for 70 % of the research. China and the USA were the major producers (45 %), collaborators (37 %), and funders of soil C research. SIC is a long-lived soil C pool with a turnover rate (leaching and recrystallization) of more than 1000 years in natural ecosystems, but intensive agricultural practices have accelerated SIC losses, making SIC an important player in global C cycle and climate change. The lack of attention and investment towards SIC research could jeopardize the ongoing efforts to mitigate climate change impacts to meet the 1.5-2.0 °C targets under the Paris Climate Agreement of 2015. This bibliographic study calls to expand the research focus on SIC and including SIC fluxes in C budgets and models, without which the representation of the global C cycle is incomplete.

Extreme precipitation accelerates nitrate leaching in the intensive agricultural region with thick unsaturated zones.

Nitrate accumulation in the soil profile in the intensive agricultural region has been widely concerned in the world. However, the changes in nitrate accumulation characteristics caused by climate change, such as extremely high precipitation, are not well quantified, particularly for the regions with thick unsaturated zones. Here, we resampled the soil profiles taken in normal year (2020) after extreme precipitation year (2021) (>800 cm) in three regions in the southern Loess Plateau (LP) with three different water managements including rainfed orchards (n = 10), well-irrigated orchards (n = 4) and canal-irrigated orchards (n = 8). The accumulation amounts, peak depths, and accumulation depths of nitrate soil profiles of the different regions of two years were compared. The results showed that average nitrate accumulation in normal year at the rainfed region (800-cm depth), well-irrigated region (800-cm depth) and canal-irrigated region (1400-cm depth) were 5995 kg N ha-1, 9765 kg N ha-1, and 19,608 kg N ha-1, respectively. Compared with 2020, extreme precipitation in 2021 led to 56-91% reductions (2060-3702 kg N ha-1) in nitrate accumulation in 0-200 cm soil layer, and average nitrate leaching into the aquifer was >1390 kg N ha-1 in the canal-irrigated region. Average migration depths of nitrate peak in rainfed, well-irrigated and canal-irrigated regions were 92 cm, 115 cm, and 188 cm, respectively; as for nitrate accumulation depths, they were 10 cm, 80 cm and 108 cm, respectively. Vertically, the dried soil layer and paleosol layer (high clay content) in the canal-irrigated region significantly hindered nitrate deep migration caused by the extreme precipitation. The result highlights that extreme precipitation significantly accelerated nitrate leaching in the deep soil profiles, and future vulnerability and risk assessment studies must account for the impacts of extreme precipitation on nitrate leaching.

Facet-dependent dispersion and aggregation of aqueous hematite nanoparticles.

Nanoparticle aggregates in solution controls surface reactivity and function. Complete dispersion often requires additive sorbents to impart a net repulsive interaction between particles. Facet engineering of nanocrystals offers an alternative approach to produce monodisperse suspensions simply based on facet-specific interaction with solvent molecules. Here, we measure the dispersion/aggregation of three morphologies of hematite (α-Fe2O3) nanoparticles in varied aqueous solutions using ex situ electron microscopy and in situ small-angle x-ray scattering. We demonstrate a unique tendency of (104) hematite nanoparticles to maintain a monodisperse state across a wide range of solution conditions not observed with (001)- and (116)-dominated particles. Density functional theory calculations reveal an inert, densely hydrogen-bonded first water layer on the (104) facet that favors interparticle dispersion. Results validate the notion that nanoparticle dispersions can be controlled through morphology for specific solvents, which may help in the development of various nanoparticle applications that rely on their interfacial area to be highly accessible in stable suspensions.

Locally Saturated Ether-Based Electrolytes With Oxidative Stability For Li Metal Batteries Based on Li-Rich Cathodes.

Li metal batteries applying Li-rich, Mn-rich (LMR) layered oxide cathodes present an opportunity to achieve high-energy density at reduced cell cost. However, the intense oxidizing and reducing potentials associated with LMR cathodes and Li anodes present considerable design challenges for prospective electrolytes. Herein, we demonstrate that, somewhat surprisingly, a properly designed localized-high-concentration electrolyte (LHCE) based on ether solvents is capable of providing reversible performance for Li||LMR cells. Specifically, the oxidative stability of the LHCE was found to heavily rely on the ratio between salt and solvating solvent, where local-saturation was necessary to stabilize performance. Through molecular dynamics (MD) simulations, this behavior was found to be a result of aggregated solvation structures of Li+/anion pairs. This LHCE system was found to produce significantly improved LMR cycling (95.8% capacity retention after 100 cycles) relative to a carbonate control as a result of improved cathode-electrolyte interphase (CEI) chemistry from X-ray photoelectron spectroscopy (XPS), and cryogenic transmission electron microscopy (cryo-TEM). Leveraging this stability, 4 mAh cm-2 LMR||2× Li full cells were demonstrated, retaining 87% capacity after 80 cycles in LHCE, whereas the control electrolyte produced rapid failure. This work uncovers the benefits, design requirements, and performance origins of LHCE electrolytes for high-voltage Li||LMR batteries.

Hydrothermal Pretreatment of KOH for the Preparation of PAC and Its Adsorption on TC.

The environment has been heavily contaminated with tetracycline (TC) due to its excessive use; however, activated carbon possessing well-developed pores can effectively adsorb TC. This study synthesized pinecone-derived activated carbon (PAC) with high specific surface area (1744.659 cm2/g, 1688.427 cm2/g) and high adsorption properties (840.62 mg/g, 827.33 mg/g) via hydrothermal pretreatment methods utilizing pinecones as precursors. The results showed that PAC treated with 6% KOH solution had excellent adsorption properties. It is found that the adsorption process accords with the PSO model, and a large amount of C=C in PAC provides the carrier for π-πEDA interaction. The results of characterization and the isothermal model show that TC plays a key role in the adsorption process of PAC. It is concluded that the adsorption process of TC on PAC prepared by hydrothermal pretreatment is mainly pore filling and π-πEDA interaction, which makes it a promising adsorbent for TC adsorption.

Preparation and properties of lignin-based dual network hydrogel and its application in sensing.

Ionic conductive hydrogels prepared from various biological macromolecules are ideal materials for the manufacture of human motion sensors from the perspective of resource regeneration and environmental sustainability. However, it is now difficult to develop conductive hydrogels including excellent self-healing and mechanical properties, mainly due to their inherent trade-off between dynamic cross-linked healing and stable cross-linked mechanical strength. In this work, alkali lignin-Polyvinyl alcohol-polyacrylic acid double network conductive hydrogels with high mechanical strength and good self-healing properties were prepared. We formed the primary network structure by hydrogen bonding interaction between polyvinyl alcohol, alkali lignin and polyacrylic acid, and the secondary network structure by coordination interaction with polyacrylic acid through the addition of Fe3+. The added lignin acts as a dynamic linkage bridge in a porous network mediated by multiple ligand bonds, imparting superior mechanical properties to the hydrogels. The relationships between the alkali lignin and iron ion dosage and the comprehensive properties of hydrogels (adhesion, antibacterial, self-healing, electrical conductivity and mechanical properties) were studied in detail. On this basis, the hydrogels explored the role of lignin in the regulation of hydrogels properties and revealed the self-healing and conductive mechanism.

Co-Pyrolysis for Pine Sawdust with Potassium Chloride: Insight into Interactions and Assisting Biochar Graphitization.

This effort aimed to explore the activation and catalytic graphitization mechanisms of non-toxic salts in converting biomass to biochar from the perspective of pyrolysis kinetics using renewable biomass as feedstock. Consequently, thermogravimetric analysis (TGA) was used to monitor the thermal behaviors of the pine sawdust (PS) and PS/KCl blends. The model-free integration methods and master plots were used to obtain the activation energy (E) values and reaction models, respectively. Further, the pre-exponential factor (A), enthalpy (ΔH), Gibbs free energy (ΔG), entropy (ΔS), and graphitization were evaluated. When the KCl content was above 50%, the presence of KCl decreased the resistance to biochar deposition. In addition, the differences in the dominant reaction mechanisms of the samples were not significant at low (α ≤ 0.5) and high (α ≥ 0.5) conversion rates. Interestingly, the lnA value showed a linearly positive correlation with the E values. The PS and PS/KCl blends possessed positive ΔG and ΔH values, and KCl was able to assist biochar graphitization. Encouragingly, the co-pyrolysis of the PS/KCl blends allows us to target-tune the yield of the three-phase product during biomass pyrolysis.

Structural Transformation in a Sulfurized Polymer Cathode to Enable Long-Life Rechargeable Lithium-Sulfur Batteries.

Sulfurized polyacrylonitrile (SPAN) represents a class of sulfur-bonded polymers, which have shown thousands of stable cycles as a cathode in lithium-sulfur batteries. However, the exact molecular structure and its electrochemical reaction mechanism remain unclear. Most significantly, SPAN shows an over 25% 1st cycle irreversible capacity loss before exhibiting perfect reversibility for subsequent cycles. Here, with a SPAN thin-film platform and an array of analytical tools, we show that the SPAN capacity loss is associated with intramolecular dehydrogenation along with the loss of sulfur. This results in an increase in the aromaticity of the structure, which is corroborated by a >100× increase in electronic conductivity. We also discovered that the conductive carbon additive in the cathode is instrumental in driving the reaction to completion. Based on the proposed mechanism, we have developed a synthesis procedure to eliminate more than 50% of the irreversible capacity loss. Our insights into the reaction mechanism provide a blueprint for the design of high-performance sulfurized polymer cathode materials.

Counting-loss correction method based on window pulse shaping.

In order to obtain a precise X-ray counting rate, a window shaping algorithm is proposed and is applied. The proposed algorithm shapes original pulses into window pulses with sharp edge and stable width. In the experiment, the measured counting rate at 3.9uA tube current is used to estimate the incoming counting rate. The dead time and corrected counting rate are estimated by the paralyzable dead-time model. The experimental results show that the mean dead time of radiation events is 260ns and the relative mean deviation is 3.44% in the newly designed counting system. While the incoming counting rate is in the range of 100kcps to 2Mcps, the relative error of the corrected counting rate compared with the incoming counting rate is less than 1.78%. The proposed algorithm suppresses the dead time swing and improves the accuracy of the total counting rate of X-ray fluorescence spectrum.

Patterns and controlling factors of soil carbon sequestration in nitrogen-limited and -rich forests in China-a meta-analysis.

Soil organic carbon (SOC) management has the potential to contribute to climate change mitigation by reducing atmospheric carbon dioxide (CO2). Understanding the changes in forest nitrogen (N) deposition rates has important implications for C sequestration. We explored the effects of N enrichment on soil carbon sequestration in nitrogen-limited and nitrogen-rich Chinese forests and their controlling factors. Our findings reveal that N inputs enhanced net soil C sequestration by 5.52-18.46 kg C kg-1 N, with greater impacts in temperate forests (8.37-13.68 kg C kg-1 N), the use of NH4NO3 fertilizer (7.78 kg Ckg-1 N) at low N levels (<30 kg Ckg-1 N; 9.14 kg Ckg-1 N), and in a short period (<3 years; 12.95 kg C kg-1 N). The nitrogen use efficiency (NUE) varied between 0.24 and 13.3 (kg C kg-1 N) depending on the forest type and was significantly controlled by rainfall, fertilizer, and carbon-nitrogen ratio rates. Besides, N enrichment increased SOC concentration by an average of 7% and 2% for tropical and subtropical forests, respectively. Although soil carbon sequestration was higher in the topsoil compared to the subsoil, the relative influence indicated that nitrogen availability strongly impacts the SOC, followed by dissolved organic carbon concentration and mean annual precipitation. This study highlights the critical role of soil NUE processes in promoting soil C accumulation in a forest ecosystem.

Global cross-biome patterns of soil respiration responses to individual and interactive effects of nitrogen addition, altered precipitation, and warming.

Anthropogenic activities have increased atmospheric N, precipitation, and temperature events in terrestrial ecosystems globally, with N deposition increasing by 3- to 5-fold during the previous century. Despite decades of scientific research, no consensus has been achieved on the impact of climate conditions on soil respiration (Rs). Here, we reconstructed 110 published studies across diverse biomes, magnitudes, and driving variables to evaluate how Rs responds to N addition, altered precipitation (both enhanced and reduced precipitation or precipitation changes), and warming. Our findings show that N addition significantly increased Rs by 44 % in forests and decreased it by 19 % and 26 % in croplands and grasslands, respectively (P < 0.05). In forests and croplands, altered precipitation significantly increased Rs by 51 % and 17 % (all, P < 0.05), respectively, whereas impacts on grassland were insignificant. In comparison, warming stimulated Rs by 62 % in forests but inhibited it by 10 % in croplands (all, P < 0.05), whereas impacts on grassland were again insignificant. In addition, across all biomes, the responses of Rs to altered precipitation and warming followed a Gaussian response, increasing up to a threshold of 1800 mm and 25 °C, respectively, above which respiration rates decreased with further increases in precipitation and temperature. Our work suggests that the dual interaction of warming × altered precipitation promotes belowground CO2 emission, thus enhancing global warming. In general, the interactive effect of N addition × altered precipitation decreases Rs. Soil moisture was identified as a primary driver of Rs. Given these findings, we recommend future research on warming vs. changed precipitation to better forecast and understand the interaction between Rs and climate change.

Soil aggregation is more important than mulching and nitrogen application in regulating soil organic carbon and total nitrogen in a semiarid calcareous soil.

Evaluating soil aggregation and microbial activities within soil aggregates contributes to understanding carbon (C) and nitrogen (N) cycling. Here we examined soil aggregate distribution, C and N pools, and extracellular enzymatic activities (EEAs) in soil aggregates after 16-year mulching (CT, no mulch; RF, plastic-mulched ridges and straw-mulched furrows; SM, straw mulch) and N fertilization (0, 120, and 240 kg ha-1). RF and SM significantly increased macroaggregate formation and aggregate stability (MWD, mean weight diameter) but N rate did not. Mulching had similar effects on aggregate-associated SOC (soil organic C) and TN (total N), with the order SM > RF > CT in macroaggregates and macroaggregate-occluded microaggregates. N input significantly increased TN in most cases, whereas its effect on SOC was only significant in SM. Notably, the majority of SOC and TN was isolated in the macroaggregate-occluded silt and clay fractions. SOC, TN, microbial biomass C (MBC), and microbial biomass N (MBN) decreased as aggregate-size decreased, whereas C- and N-acquiring enzymes varied greatly across aggregate fractions. Mulching had greater effects than N-fertilization on soil C and N pools and EEAs, whilst SM performed more beneficial effects than RF on SOC, TN, MBC, MBN, and EEAs. MBC rather than SOC was associated with MWD in bulk soil, while significant relations between MWD and SOC were observed in macroaggregates and macroaggregate-occluded microaggregates. Partial least squares path modeling illustrated that soil aggregation was the most important factor affecting SOC and TN, followed by mulching and N addition. Regression analysis further revealed that α-glucosidase and leucine aminopeptidase were major variables mediating SOC and TN dynamics at the aggregate scale. This study highlights the importance of macroaggregate-occluded microaggregate fraction sensitively evaluating soil C and N dynamics, and straw mulch can effectively increase soil aggregation and stabilization of C and N in semiarid areas with infertile soils.

A Scientometric Review: Biomass Gasification Study from 2006 to 2020.

Biomass gasification represents a significant way to produce energy from biomass. It features renewable properties and offers great potential for utilization. The application of biomass gasification products, design of the gasifier, type of biomass feedstock, gasification agents, and gasification parameters are key for the biomass gasification process. This work applies bibliometric approaches to provide a comprehensive and objective analysis of worldwide biomass gasification study trends over the period from 2006 to 2020 according to the Web Of Science core collection data. A total of 3222 articles associated with biomass gasification was retrieved, and its number grew annually. The subjects of study are diversified, primarily classified into "Energy & Fuels", "Engineering Chemical", and "Green Sustainable Science Technology". Moreover, Energy was a top published journal in the field of biomass gasification. Austrian contributors had the majority of publications, next to China and the USA. Liejin Luo from Xi'an Jiaotong University possessed the greatest H-index. Keyword evaluation showed that biomass gasification is a current hotspot, among which life-cycle assessment, sustainability, and deep processing of gasification products are future research directions. This work is predicted to offer further research interest in biomass gasification.

Trapezoidal pile-up nuclear pulse parameter identification method based on deep learning transformer model.

Pile-up between adjacent nuclear pulses is unavoidable in the actual detection process. Some scholars have tried to apply deep learning techniques to identify pile-up nuclear pulse parameters. However, traditional deep learning recurrent neural networks (RNNs) suffer from inefficient pulse recognition and poor recognition of pile-up nuclear pulses with short intervals between adjacent pulses. In this paper, a Transformer model with an attention mechanism as the core to recognize pile-up nuclear pulses is innovatively applied, aiming to provide a more accurate and efficient method for pile-up nuclear pulse recognition. Thus, it gives a better help for the spectrum correction with a high count rate.

Correction: Ecological restoration stimulates environmental outcomes but exacerbates water shortage in the Loess Plateau.

[This corrects the article DOI: 10.7717/peerj.13658.].

Fabrication of lignin reinforced hybrid hydrogels with antimicrobial and self-adhesion for strain sensors.

Ionic conductive hydrogels prepared from various biological macromolecules are ideal materials for the manufacture of human motion sensors from the perspective of resource regeneration and environmental sustainability. However, it is still challenging to prepare hydrogels with both high toughness and self-healing ability. In this study, lignin-based ß-CD-PVA (LCP) self-healing conductive hydrogels with high tensile properties were prepared by one-step method using alkali lignin as a plasticizer. Compared with PVA hydrogel, the maximum storage modulus and elongation were increased by 2.5 and 20.0 times, respectively. Uniform distribution of lignin can increase the fluidity and distance of polymer molecular chains, thus improving the viscoelastic and tensile properties of the LCP self-healing hydrogel. LCP hydrogels can maintain self-healing ability in both high (45 °C) and low temperature (0 °C) environments, and the self-healing ability is not affected by pH. Moreover, it also has good conductivity, anti-bacterial, thermostability, and anti-UV property, which has a good application prospect in the field of 3D printing and wearable electronic devices, which expands the efficient utilization of lignin in biorefinery.

Ecological restoration stimulates environmental outcomes but exacerbates water shortage in the Loess Plateau.

Restoration is the natural and intervention-assisted set of processes designed to promote and facilitate the recovery of an ecosystem that has been degraded, damaged, or destroyed. However, it can also have an adverse effect on the environment. Thus, assessing an ecological restoration project's impact is crucial to determining its success and optimum management strategies. We performed a meta-analysis concerning the environmental outcomes during the years 2000-2015 resulting from the "Grain for Green" Project (GFGP) implementation in the Loess Plateau (LP). Data were gathered from 40 peer-reviewed English-language articles chosen from a pool of 332 articles. The results showed that, on average, GFGP increased forest coverage by 35.7% (95% CI [24.15-47.52%]), and grassland by 1.05% (95% CI [0.8-1.28%]). At the same time, GFGP has a positive impact on soil carbon (C) sequestration, net ecosystem production (NEP), and net primary production (NPP), from the years 2000 to 2015 by an average of 36% (95% CI [28.96-43.18%]), 22.7% (95% CI [9.10-36.79%]), and 13.5% (95% CI [9.44-17.354%]), respectively. Soil erosion, sediment load, runoff coefficient, and water yield were reduced by 13.3% (95% CI [0.27-25.76%]), 21.5% (95% CI [1.50-39.99%]), 22.4% (95% CI [5.28-40.45%]) and 43.3% (95% CI [27.03-82.86%]), respectively, from the years 2000 to 2015. Our results indicate that water supply decreased with the increase of vegetation coverage. Therefore, to balance the needs for green space, GFGP policies and strategies should recover, enhance, and sustain more resilient ecosystems.

A fast gamma-ray source localization method for mobile robots.

A method for fast estimation of radioactive source parameters is presented. Full use was made of multiple continuous count values, combined with triangulation with four-point sampling method to solve high-dimensional optimization to obtain initialized estimates, which converge to maximum likelihood estimation using an improved hill-climbing algorithm. Cobalt-60 search experiments were conducted in the laboratory using a mobile robot carrying a NaI(TI) detector. Experimental results showed that the method can significantly improve the computational speed.