The effects of long-term ammunition pollution on microecological characteristics were analyzed to formulate microbial remediation strategies. Specifically, the response of enzyme systems, N/O stable isotopes, ion networks, and microbial community structure/function levels were analyzed in long-term (50 years) ammunition-contaminated water/sediments from a contamination site, and a compound bacterial agent capable of efficiently degrading trinitrotoluene (TNT) while tolerating many heavy metals was selected to remediate the ammunition-contaminated soil. The basic physical and chemical properties of the water/sediment (pH (up: 0.57-0.64), nitrate (up: 1.31-4.28 times), nitrite (up: 1.51-5.03 times), and ammonium (up: 7.06-70.93 times)) were changed significantly, and the significant differences in stable isotope ratios of N and O (nitrate nitrogen) confirmed the degradability of TNT by indigenous microorganisms exposed to long-term pollution. Heavy metals, such as Pb, Zn, Cu, Cd, Cs, and Sb, have synergistic toxic effects in ammunition-contaminated sites, and significantly decreased the microbial diversity and richness in the core pollution area. However, long-term exposure in the edge pollution area induced microorganisms to use TNT as a carbon and nitrogen sources for life activities and growth and development. The Bacteroidales microbial group was significantly inhibited by ammunition contamination, whereas microorganisms such as Proteobacteria, Acidobacteriota, and Comamonadaceae gradually adapted to this environmental stress by regulating their development and stress responses. Ammunition pollution significantly affected DNA replication and gene regulation in the microecological genetic networks and increased the risk to human health. Mg and K were significantly involved in the internal mechanism of microbial transport, enrichment, and metabolism of TNT. Nine strains of TNT-utilizing microbes were screened for efficient TNT degradation and tolerance to typical heavy metals (copper, zinc and lead) found in contaminated sites, and a compound bacterial agent prepared for effective repair of ammunition-contaminated soil significantly improved the soil ecological environment.

In this work, the characteristics of the exothermic reaction between ammonium nitrate and sulfide ores were explored using COMSOL Multiphysics. This reaction can cause an increase in temperature within the blast holes of sulfide mines and can potentially induce premature explosions of the explosives. Initially, simulations were conducted to observe temperature variations in blast holes before and after the loading of explosives. Then, the impact of blast hole diameter and initial temperature on the thermal environment was assessed. Subsequent analysis focused on the fluid field\'s dynamics, examining flow rate changes and the concentration of signature gases produced by the reaction. Additionally, the influence of blast hole diameter on these parameters was evaluated. The results show that the blast hole temperature is positively related to its diameter and initial temperature. When the diameter of the blast hole is 120 mm and 165 mm, a significant change in flow rate is observed, with a trend of being rapidly increased and then rapidly decreased. The production of NH3 is always found to be greater than that of the other two gases. As for NO and SO2, their production is characterized by an approximate ratio of 1:2. The numerical simulation results can provide important theoretical guidance for the spontaneous detonation of blast hole in sulfide mines.

Faced with rising threats of terrorism, environmental and health risks, achieving sensitive and selective detection of peroxide-based explosives (PEs) has become a global focus. In this study, a turn-on fluorescent probe (BOD) based on benzil (H2O2-recognition element) and 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivative (fluorophore) was developed to sensitively and specifically detect hydrogen peroxide (H2O2). The synthesized BOD had a very weak fluorescence due to intramolecular donor-excited photo-induced electron transfer (d-PET) effect; however, it could emit a strong fluorescence since H2O2 selectively oxidized the benzil moiety and released free BODIPY fluorophore (BOD-COOH). As a result, the proposed BOD detected H2O2 in linear detection ranged from 25 to 125 µM with a detection limit of 4.41 µM. Meanwhile, the proposed BOD showed good selectivity toward H2O2, which is not affected by other common reactive oxygen species (ROS) and ions from explosive residues. In addition, a blue shift from 508 to 498 nm was observed in the absorption spectra upon addition of H2O2. More importantly, the BOD was successfully applied for rapid detection of H2O2 vapor with good sensitivity (down to 7 ppb), which holds great potential for practical use in public safety, forensic analysis and environmental monitoring.

Residual explosives in conflicting zones have caused irreversible damage to human safety and the environment. Whole-cell biosensors can to detect remnants of buried explosives, such as 2,4-dinitrotoluene (DNT), a stable and highly volatile compound in explosives. However, all the reported whole-cell biosensors utilize fluorescence or luminescence as the biological markers, making their detection difficult in real minefields. Here, we presented a lycopene-based whole-cell biosensor in Escherichia coli to output visible signals in response to DNT, which can help in the visual detection of buried explosives. To construct the whole-cell biosensor, the DNT-responsive promoter yqjF was used as the sensing element, and the lycopene synthetic gene cassette crtEBI was served as the reporting element. Then, the metabolic flux for lycopene production was enhanced to improve the output signal of the whole-cell biosensor, and a terminator was utilized to reduce the background interference. The optimized biosensor LSZ05 could perceive at least 1 mg/L DNT. The DNT-specificity and robust performance of the biosensor under different environmental factors were confirmed. Our results showed that converting the biosensor into a lyophilized powder was an effective storage method. The biosensor LSZ05 could effectively detect DNT in two kinds of soil samples. The lycopene-based whole-cell biosensor could also be used to visually detect heavy metals. Our findings laid the foundation for visually detecting buried explosives in minefields, which was a valuable supplement to the reported biosensors. The methods used for optimizing the lycopene-based whole-cell biosensor, including the improvement of the output signal and reduction of background interference, were quite effective.

Detecting unexploded landmines is critical due to the environmental pollution and potential humanitarian risks caused by buried landmines. Therefore, this study focused on developing a biosensor system capable of detecting explosives safely and efficiently. A novel transcription factor-based Escherichia coli biosensor was designed to detect 1,3-dinitrobenzene (1,3-DNB). The MexT transcription factor from Pseudomonas putida (P. putida) was identified as the fundamental sensing element in this biosensor. The study found that MexT positively regulated the transcription of PP_2827 by binding to the bidirectional promoter region between them, and significantly enhanced the expression of downstream genes under the condition of 1,3-DNB. The MexT-based biosensor for 1,3-DNB was developed by adopting different combinations of the mexT gene and promoters. The optimized biosensor demonstrated adequate sensitivity for detecting 0.1 μg/mL of 1,3-DNB in a liquid solution with satisfactory specificity and long-term stability. Subsequently, the MexT-based biosensor was integrated into a detection device to simulate the in-field exploration of explosives. The system exhibited a detection sensitivity of 0.5 mg/kg for 1,3-DNB in the sand, and realized the detection of on-site and large-scale area and the location of buried 1,3-DNB under the soil. The study provided a novel transcription factor-based bacterial biosensor and a complete system (China Earth Eye, CEE) for sensitive detection of 1,3-DNB. The good performance of this biosensor system can facilitate the development of accurate, on-site, and high-efficient exploration of explosives in real extensive minefields. Moreover, this 1,3-DNB biosensor can be complementary to the 2,4-DNT biosensor reported before, demonstrating its potential applications in military situations.

Surface-enhanced Raman spectroscopy (SERS), well acknowledged as a fingerprinting and sensitive analytical technique, has exerted high applicational value in a broad range of fields including biomedicine, environmental protection, food safety among the others. In the endless pursuit of ever-sensitive, robust, and comprehensive sensing and imaging, advancements keep emerging in the whole pipeline of SERS, from the design of SERS substrates and reporter molecules, synthetic route planning, instrument refinement, to data preprocessing and analysis methods. Artificial intelligence (AI), which is created to imitate and eventually exceed human behaviors, has exhibited its power in learning high-level representations and recognizing complicated patterns with exceptional automaticity. Therefore, facing up with the intertwining influential factors and explosive data size, AI has been increasingly leveraged in all the above-mentioned aspects in SERS, presenting elite efficiency in accelerating systematic optimization and deepening understanding about the fundamental physics and spectral data, which far transcends human labors and conventional computations. In this review, the recent progresses in SERS are summarized through the integration of AI, and new insights of the challenges and perspectives are provided in aim to better gear SERS toward the fast track.

With the evolution of artificial intelligence, the explosive growth of data from sensory terminals gives rise to severe energy-efficiency bottleneck issues due to cumbersome data interactions among sensory, memory, and computing modules. Heterogeneous integration methods such as chiplet technology can significantly reduce unnecessary data movement; however, they fail to address the fundamental issue of the substantial time and energy overheads resulting from the physical separation of computing and sensory components. Brain-inspired in-sensor neuromorphic computing (ISNC) has plenty of room for such data-intensive applications. However, one key obstacle in developing ISNC systems is the lack of compatibility between material systems and manufacturing processes deployed in sensors and computing units. This study successfully addresses this challenge by implementing fully CMOS-compatible TiN/HfOx-based neuristor array. The developed ISNC system demonstrates several advantageous features, including multilevel analogue modulation, minimal dispersion, and no significant degradation in conductance (@125 °C). These characteristics enable stable and reproducible neuromorphic computing. Additionally, the device exhibits modulatable sensory and multi-store memory processes. Furthermore, the system achieves information recognition with a high accuracy rate of 93%, along with frequency selectivity and notable activity-dependent plasticity. This work provides a promising route to affordable and highly efficient sensory neuromorphic systems.

The synthesis of the new energetic material 4-amino-3-hydrazino-5-methyl-1,2,4-triazole, which shows excellent performance and reliable safety, has drawn attention recently. To fully characterize this material, a comprehensive analysis was performed using various techniques, including differential scanning calorimetry (DSC), infrared spectroscopy (IR), elemental analysis, and 1H and 13C NMR spectroscopy. Additionally, three compounds, 3, 5 and 9, were further characterized using single X-ray diffraction. The X-ray data suggested that extensive hydrogen bonds affect molecular structure by means of intermolecular interactions. In order to evaluate the explosive properties of these synthesized compounds, detonation pressures and velocities were calculated using EXPLO5 (V6.01). These calculations were carried out utilizing experimental data, including density and heat of formation. Among the explosives tested, compounds 7 and 8 exhibited zero oxygen balance and demonstrated exceptional detonation properties. Compound 7 achieved the highest recorded detonation pressure, at 34.2 GPa, while compound 8 displayed the highest detonation velocity, at 8887 m s-1.

Aeration is an effective approach to sustainable landfilling but may lead to elevated temperatures within landfills, resulting in landfill fires or explosions. Therefore, aeration is usually combined with leachate recirculation to control the elevated temperatures within landfills. To predict landfill temperatures during aeration and recirculation, a local thermal non-equilibrium model is developed considering the heat generation of biodegradation, the heat removal due to evaporation and leachate-gas flow, and the effects of the capillary. The solver is implemented in OpenFOAM based on the finite volume method and validated against a waste-column experiment and an in-situ aeration test. The simulation results demonstrate that the assumption of local thermal equilibrium will distinctly overestimate the temperature, maximally by 15 °C in the studied case. The model is then used to simulate a typical aerobic landfill unit to investigate the formation of explosive gas mixtures and elevated temperatures under different operating conditions. The simulation results of gas composition suggest that aeration will not result in explosive gas within landfills. A reasonable recirculation method for temperature control with corresponding operating parameters under a group of values of aeration pressure (2000-4000 Pa) and recirculation rate (0.0001-0.0008 m/s) are proposed, which can provide some guides for the design of an aeration and recirculation combined system. For a given total volume of added leachate, a higher recirculation rate does not always mean better cooling, and the cooling effect of continuous recirculation is better than that of intermittent recirculation.

The structure and properties of nano-carbon materials formed in explosives detonation are always a challenge, not only for the designing and manufacturing of these materials but also for clearly understanding the detonation performance of explosives. Herein, we study the dynamic evolution process of condensed-phase carbon involved in 2,4,6-Triamino-1,3,5-trinitrobenzene (TATB) detonation using the quantum-based molecular dynamics method. Various carbon structures such as, graphene-like, diamond-like, and \"diaphite\", are obtained under different pressures. The transition from a C sp2- to a sp3-hybrid, driven by the conversion of a hexatomic to a non-hexatomic ring, is detected under high pressure. A tightly bound nucleation mechanism for diamond-like carbon dominated by a graphene-like carbon layer is uncovered. The graphene-like layer is readily constructed at the early stage, which would connect with surrounding carbon atoms or fragments to form the tetrahedral structure, with a high fraction of sp3-hybridized carbon. After that, the deformed carbon layers further coalesce with each other by bonding between carbon atoms within the five-member ring, to form the diamond-like nucleus. The complex \"diaphite\" configuration is detected during the diamond-like carbon nucleation, which illustrates that the nucleation and growth of detonation nano-diamond would accompany the intergrowth of graphene-like layers.