Large-scale Applications Research Articles

Patient derived cancer organoids model the response to HER2-CD3 bispecific antibody (BsAbHER2) generated from hydroxyapatite gene delivery system

HER2-positive cancer is a prevalent subtype of malignancy with poor prognosis, yet current targeted therapies, like Trastuzumab and pyrotinib, have resulted in remission in patients with HER2-positive cancer. This study provides a novel approach for immunotherapy based on a hydroxyapatite (HA) gene delivery system producing a bispecific antibody for HER2-positive cancer treatment. An HA nanocarrier has been synthesized by the classical hydrothermal method. Particularly, the HA-nanoneedle system was able to mediate stable gene expression of minicircle DNA (MC) encoding a humanized anti-CD3/anti-HER2 bispecific antibody (BsAbHER2) in vivo. The produced BsAbs exhibited a potent killing effect not only in HER2-positive cancer cells but also in patient-derived organoids in vitro. This HA-nanoneedle gene delivery system features simple large-scale preparation and clinical applicability. Hence, the HA-nanoneedle gene delivery system combined with minicircle DNA vector encoding BsAbHER2 reported here provides a potential immunotherapy strategy for HER2-positive tumors.

Effect of 3D-printed polycaprolactone/osteolectin scaffolds on the odontogenic differentiation of human dental pulp cells

Cell-based tissue engineering often requires the use of scaffolds to provide a three-dimensional (3D) framework for cell proliferation and tissue formation. Polycaprolactone (PCL), a type of polymer, has good printability, favorable surface modifiability, adaptability, and biodegradability. However, its large-scale applicability is hindered by its hydrophobic nature, which affects biological properties. Composite materials can be created by adding bioactive materials to the polymer to improve the properties of PCL scaffolds. Osteolectin is an odontogenic factor that promotes the maintenance of the adult skeleton by promoting the differentiation of LepR+ cells into osteoblasts. Therefore, the aim of this study was to evaluate whether 3D-printed PCL/osteolectin scaffolds supply a suitable microenvironment for the odontogenic differentiation of human dental pulp cells (hDPCs). The hDPCs were cultured on 3D-printed PCL scaffolds with or without pores. Cell attachment and cell proliferation were evaluated using EZ-Cytox. The odontogenic differentiation of hDPCs was evaluated by alizarin red S staining and alkaline phosphatase assays. Western blot was used to evaluate the expression of the proteins DSPP and DMP-Results: The attachment of hDPCs to PCL scaffolds with pores was significantly higher than to PCL scaffolds without pores. The odontogenic differentiation of hDPCs was induced more in PCL/osteolectin scaffolds than in PCL scaffolds, but there was no statistically significant difference. 3D-printed PCL scaffolds with pores are suitable for the growth of hDPCs, and the PCL/osteolectin scaffolds can provide a more favorable microenvironment for the odontogenic differentiation of hDPCs.

An ink-free integrated dual electrode assembly for economical proton electrolyzer membrane water electrolysis at ultrahigh current densities

The clean and sustainable “green hydrogen” is highly attractive as an alternative energy. However, the excessive cost of “green hydrogen” hinders its large-scale application, which is limited by the costly membrane electrode assembly (MEA) in proton exchange membrane electrolyzer cells (PEMECs). Herein, we revolutionize the conventional MEA via a facile ink-free and cost-effective integrated dual electrode assembly (IDEA) for reducing the costs and enhancing the performance of PEMECs. IDEA not only greatly simplifies fabrication processes of MEAs from over ten steps to three steps but also significantly increases hydrogen production rate simultaneously (45.26 % more hydrogen at 1.8 V). Benefiting from the nano-thick catalyst layers, the IDEA can achieve an industrial “overload” current density of 6 A/cm2 at a low cell voltage of 1.82 V with an 83.9 % noble catalyst saving, which outperforms most reported PEMECs. Particularly, the degradation rate of IDEA is only 24 μV/h at 1.8 A/cm2.

SLAM for Indoor Mapping of Wide Area Construction Environments

Abstract. Simultaneous localization and mapping (SLAM), i.e., the reconstruction of the environment represented by a (3D) map and the concurrent pose estimation, has made astonishing progress. Meanwhile, large scale applications aiming at the data collection in complex environments like factory halls or construction sites are becoming feasible. However, in contrast to small scale scenarios with building interiors separated to single rooms, shop floors or construction areas require measures at larger distances in potentially texture less areas under difficult illumination. Pose estimation is further aggravated since no GNSS measures are available as it is usual for such indoor applications. In our work, we realize data collection in a large factory hall by a robot system equipped with four stereo cameras as well as a 3D laser scanner. We apply our state-of-the-art LiDAR and visual SLAM approaches and discuss the respective pros and cons of the different sensor types for trajectory estimation and dense map generation in such an environment. Additionally, dense and accurate depth maps are generated by 3D Gaussian splatting, which we plan to use in the context of our project aiming on the automatic construction and site monitoring.

An improved neural operator framework for large-scale CO2 storage operations

Geologic carbon storage (GCS) is a practical solution to mitigate the impact of climate change and achieve net-zero carbon emissions. However, due to complex subsurface characteristics and operational constraints, GCS can potentially induce seismic events and leakage to groundwater resources. Moreover, predicting subsurface response in pressure and saturation changes during GCS requires high-fidelity models with high computational times. Machine learning (ML) offers a promising solution to alleviate these challenges. Yet, ML-driven approaches in subsurface physics face significant obstacles, such as the substantial computational resources required for training large-scale models and the accuracy requirement as a reliable surrogate model. To tackle these issues, we propose an improved neural operator (INO) that has improved a DeepONet architecture to handle a realistic reservoir model efficiently, with computational efficiency and high accuracy.Our proposed INO framework has three key benefits: precision, adaptability, and cost-efficiency. For precision, it achieves an average root mean square error (RMSE) of 0.05% (1.5 psi) compared to the average reservoir pressure (3,150 psi) and a RMSE value of 0.016 in void fraction for CO2 saturation among testing cases. Although it is sensitive to high-error areas with steep state variable gradients, proper domain decomposition, ensemble methods, and/or integrating domain-specific knowledge could improve this limitation. For adaptability, the INO framework can be trained with a subset of the computational domain during each backpropagation to achieve better training adaptability, even for problems with high-dimensional inputs (i.e., heterogeneous fields). For example, it can be trained with random subsampling of only 0.2% of the full domain but can predict pressure and saturation in any space and time within the entire domain. For cost efficiency, training procedures with a subset of the whole computational domain significantly improve computational time. For example, for 90 training cases with 1.73 million cells and 50-time steps, the overall training time was about 2.5 h using a single GPU. A trained INO model takes 1 s per evaluation over 1.73 million and 50 time stamps, much faster than a high-fidelity simulator. Overall, the proposed INO approach with these improved benefits will enable us to perform large-scale GCS applications, enhancing the potential of ML models in the subsurface and other multiphysics problems.

Unbounding the Future: Designing NiAl-based Catalysts for Dry Reforming of Methane.

Dry reforming of methane (DRM), the catalytic conversion of CH4 and CO2 into syngas (H2 + CO), is an important process closely correlated to the environment and chemical industry. NiAl-based catalysts have been reported to exhibit excellent activity, low cost, and environmental friendliness. At the same time, the rapid deactivation caused by carbon deposition, Ni sintering, and phase transformation exerts great challenges for its large-scale applications. This review summarizes the recent advances in NiAl-based catalysts for DRM, particularly focusing on the strategies to construct efficient and stable NiAl-based catalysts. Firstly, the thermodynamics and elementary steps of DRM, including the activation of reactants and coke formation and elimination, are summarized. The roles of Al2O3 and its mixed oxides as the support, and the influences of the promoters employed in NiAl-based catalysts over the DRM performance, are then illustrated. Finally, the design of anti-coking and anti-sintering NiAl-based catalysts for DRM is suggested as feasible and promising by tailoring the structure and states of Ni and the modification of Al-based supports including small Ni size, high Ni dispersion, proper basicity, strong metal-support interaction (SMSI), active oxygen species as well as high phase stability.

Heterostructure design on honeycomb borophene/Mo2C: A novel strategy for nitrogen fixation

In terms of its ecological and sustainable nature, electrochemical nitrogen reduction reaction (e-NRR) is widely recognized as the ideal solution to replace conventional ammonia production techniques. Unfortunately, poor Faraday efficiency (FE) with lower e-NRR selectivity limits its large-scale application. Previous studies have identified Mo2C as an optimistic electrocatalyst for e-NRR, exhibiting great ammonia yield. However, Mo2C suffers from Mo leaching during the electrochemical reaction process, thus reducing the stability of the catalyst. Herein, we propose a new electrocatalyst based on first-principles calculations: HB/α-Mo2C. This heterostructure is composed of Mo2C covered with a layer of Honeycomb Borophene (HB). The HB layer serves two purposes: to ensure the stability of the catalyst and improve the FE of the reaction. Our findings demonstrate the HB/α-Mo2C performs the highest catalytic activity via a mixed mechanism with a limiting potential as low as -0.16 V, which was determined to be caused by the transfer of electrons from the active sites of the boron atoms to the adsorbate. Furthermore, the limiting potential of HER, a competing reaction, was found to be as high as −0.56 V, confirming the high efficiency of HB/α-Mo2C towards e-NRR. This present work contributes to the development of new strategies for e-NRR catalyst design.

Overview of coals as carbon anode materials for sodium-ion batteries

Abstract Energy storage is an important technology in achieving carbon neutrality goals. Compared with lithium-ion batteries, the raw materials of sodium-ion batteries are abundant, low-cost and highly safe. Furthermore, their costs are expected to be further reduced as large-scale applications take off, making them viable for energy storage applications. The primary anode material for sodium-ion batteries is hard carbon, which has a high sodium-ion storage capacity but is relatively expensive, limiting its applications in energy storage. In order to widen the applications of sodium-ion batteries in energy storage and other fields, it is particularly important to develop anode materials that have both high performance and low cost. Coals, with abundant reserves and worldwide availability, can serve as low-cost carbon sources for anode materials. Additionally, coals of different grades of metamorphism have different structural characteristics that can be tailored for the structural characteristics of coal-based anode materials for sodium-ion batteries. Recent researches on tailoring coals as the anode materials for sodium-ion batteries is summarized and the recent progress made towards mitigating the existing issues is analysed in this review. Specifically, the impacts of different grades of metamorphism on the sodium-ion storage performance of coal-based anode materials prepared with direct carbonization are discussed in detail. Studies on improving the electrochemical performances of coal-based anode materials through pore and microcrystalline structure controls, and surface as well as interface modifications are presented. Finally, the advantages and disadvantages of different preparation methods are identified. To make the industrial applications of coal-based anode materials for sodium-ion batteries more viable, the importance of the de-ashing process is introduced.

Molecular Photoelectrochemical Energy Storage Materials for Coupled Solar Batteries.

ConspectusSolar-to-electrochemical energy storage is one of the essential solar energy utilization pathways alongside solar-to-electricity and solar-to-chemical conversion. A coupled solar battery enables direct solar-to-electrochemical energy storage via photocoupled ion transfer using photoelectrochemical materials with light absorption/charge transfer and redox capabilities. Common photoelectrochemical materials face challenges due to insufficient solar spectrum utilization, which restricts their redox potential window and constrains energy conversion efficiency. In contrast, molecular photoelectrochemical energy storage materials are promising for their mechanism of exciton-involved redox reaction that allows for extra energy utilization from hot excitons generated by superbandgap excitation and localized heat after absorption of sub-bandgap photons. This enables more efficient redox reactions with a less restricted redox potentials window and, thus, better utilization of the full solar spectrum. Despite these advantages, practical application remains elusive due to the mismatch between the short lifetime of the charge separation state (<ns) and the slower redox reaction rate (>μs). This mismatch results in a significant portion of the photogenerated charges recombining before participating in desired electrochemical energy storage reactions, leading to diminished overall efficiency. It is therefore highly important to develop molecular materials with intrinsic prolonged charge separation state and extrinsic effective mass-electron transfer to enable efficient coupled solar batteries for practical applications.In this Account, we begin with an introduction of the general solar-to-electrochemical energy storage concept based on molecular photoelectrochemical energy storage materials, highlighting the advantages of periodic oxidative donor-reductive acceptor porous aggregate structures that have synergistic implications on charge separation state lifetime extension and mass-electron transfer. We then present our earliest trial on the design and application of molecular photoelectrochemical energy storage materials, which stimulated our subsequent studies on tuning electron donor and acceptor structures for enhanced charge separation and diverse photoelectrochemical redox reactions. Moreover, we introduce the best practices in the design and assembly of various coupled solar battery devices, along with our literature contributions and progresses in solar-to-electrochemical energy storage efficiency (ηSES) over nearly the past decade. Finally, we conclude by highlighting the universality of our strategies as essential design principles, spanning from regulating long-lived charge separation states and photocoupled ion transfer processes in molecular materials to the construction of efficient coupled solar batteries. We offer perspectives on the synergy between photovoltage and redox potentials and the practical significance of 3D printing, providing key evaluation indicators for large-scale application. This Account provides molecular level insights for the construction of high-efficiency photoelectrochemical energy storage materials and guidance for practical solar-to-electrochemical energy storage applications.

Toward Circular Energy: Exploring Direct Regeneration for Lithium-Ion Battery Sustainability.

Lithium-ion batteries (LIBs) are rapidly developing into attractive energy storage technologies. As LIBs gradually enter retirement, their sustainability is starting to come into focus. The utilization of recycled spent LIBs as raw materials for battery manufacturing is imperative for resource and environmental sustainability. The sustainability of spent LIBs depends on the recycling process, whereby the cycling of battery materials must be maximized while minimizing waste emissions and energy consumption. Although LIB recycling technologies (hydrometallurgy and pyrometallurgy) have been commercialized on a large scale, they have unavoidable limitations. They are incompatible with circular economy principles because they require toxic chemicals, emit hazardous substances, and consume large amounts of energy. The direct regeneration of degraded electrode materials from spent LIBs is a viable alternative to traditional recycling technologies and is a nondestructive repair technology. Furthermore, direct regeneration offers advantages such as maximization of the value of recycled electrode materials, use of sustainable, nontoxic reagents, high potential profitability, and significant application potential. Therefore, this review aims to investigate the state-of-the-art direct LIB regeneration technologies that can be extended to large-scale applications.

Peptide Drug Design Using Alchemical Free Energy Calculation: An Application and Validation on Agonists of Ghrelin Receptor.

With recent large-scale applications and validations, the relative binding free energy (RBFE) calculated using alchemical free energy methods has been proven to be an accurate measure to probe the binding of small-molecule drug candidates. On the other hand, given the flexibility of peptides, it is of great interest to find out whether sufficient sampling could be achieved within the typical time scale of such calculation, and a similar level of accuracy could be reached for peptide drugs. However, the systematic evaluation of such calculations on protein-peptide systems has been less reported. Most reported studies of peptides were restricted to a limited number of data points or lacking experimental support. To demonstrate the applicability of the alchemical free energy method for protein-peptide systems in a typical real-world drug discovery project, we report an application of the thermodynamic integration (TI) method to the RBFE calculation of ghrelin receptor and its peptide agonists. Along with the calculation, the synthesis and in vitro EC50 activity of relamorelin and 17 new peptide derivatives were also reported. A cost-effective criterion to determine the data collection time was proposed for peptides in the TI simulation. The average of three TI repeats yielded a mean absolute error of 0.98 kcal/mol and Pearson's correlation coefficient (R) of 0.77 against the experimental free energy derived from the in vitro EC50 activity, showing good repeatability of the proposed method and a slightly better agreement than the results obtained from the arbitrary time frames up to 20 ns. Although it is limited by having one target and a deduced binding pose, we hope that this study can add some insights into alchemical free energy calculation of protein-peptide systems, providing theoretical assistance to the development of peptide drugs.

Exploring Nanomaterials for Hydrogen Storage: Advances, Challenges, and Perspectives.

Hydrogen energy heralded for its environmentally friendly, renewable, efficient, and cost-effective attributes, stands poised as the primary alternative to fossil fuels in the future. Despite its great potential, the low volumetric density presents a formidable challenge in hydrogen storage. Addressing this challenge necessitates exploring effective storage techniques for a sustainable hydrogen economy. Solid-state hydrogen storage in nanomaterials (physically or chemically) holds promise for achieving large-scale hydrogen storage applications. Such approaches offer benefits, including safety, compactness, lightness, reversibility, and efficient generation of pure hydrogen fuel under mild conditions. This article presents solid-state nanomaterials, specifically nanoporous carbons (activated carbon, carbon fibers), metal-organic frameworks, covalently connected frameworks, nanoporous organic polymers, and nanoscale metal hydrides. Furthermore, new developments in hydrogen fuel cell technology for stationary and mobile applications have been demonstrated. The review outlines significant advancements thus far, identifies key barriers to practical implementation, and presents a perspective for future sustainable energy research. It concludes with recommendations to enhance hydrogen storage performance for cost-effective and long-lasting utilization.

Remediation of Saline Soils Using Halo-Tolerant Plant Growth Promoting Rhizobacteria

Soil salinization poses a significant threat to global agriculture, affecting approximately 6.73m Ha land area in India. Salinity stress impacts plant growth and soil health negatively, leading to reduced crop yields and soil degradation. This review examines the sources and effects of soil salinity, highlighting the intricate interplay between salinity and soil nutrients and its remediation. Traditional methods for soil remediation often have detrimental long-term effects, prompting the exploration of alternative strategies such as the use of halo-tolerant plant growth-promoting rhizobacteria. HT-PGPR offer a promising solution for sustainable agriculture by enhancing soil fertility and plant resilience to salinity stress through various mechanisms. Furthermore, this review identifies research gaps in understanding the metabolic pathways and strain selection of HT-PGPR, as well as their interactions with soil microbiota. Future research directions include field-scale experiments to validate the effectiveness and economic viability of HT-PGPR inoculation for large-scale application in saline soils. Overall, leveraging the potential of HT-PGPR represents a critical step towards mitigating the global challenge of soil salinity and ensuring food security in the face of climate change.

Optimizing Lithium-Ion Battery Performance: Integrating Machine Learning and Explainable AI for Enhanced Energy Management

Managing the capacity of lithium-ion batteries (LiBs) accurately, particularly in large-scale applications, enhances the cost-effectiveness of energy storage systems. Less frequent replacement or maintenance of LiBs results in cost savings in the long term. Therefore, in this study, AdaBoost, gradient boosting, XGBoost, LightGBM, CatBoost, and ensemble learning models were employed to predict the discharge capacity of LiBs. The prediction performances of each model were compared based on mean absolute error (MAE), mean squared error (MSE), and R-squared values. The research findings reveal that the LightGBM model exhibited the lowest MAE (0.103) and MSE (0.019) values and the highest R-squared (0.887) value, thus demonstrating the strongest correlation in predictions. Gradient boosting and XGBoost models showed similar performance levels but ranked just below LightGBM. The competitive performance of the ensemble model indicates that combining multiple models could lead to an overall performance improvement. Furthermore, the study incorporates an analysis of key features affecting model predictions using SHAP (Shapley additive explanations) values within the framework of explainable artificial intelligence (XAI). This analysis evaluates the impact of features such as temperature, cycle index, voltage, and current on predictions, revealing a significant effect of temperature on discharge capacity. The results of this study emphasize the potential of machine learning models in LiB management within the XAI framework and demonstrate how these technologies could play a strategic role in optimizing energy storage systems.

The biosynthesis mechanism of bacterioruberin in halophilic archaea revealed by genome and transcriptome analysis.

Recent studies have revealed that halophilic microorganism is a promising microbial factory for the next-generation industrialization. Among them, halophilic archaea are advantageous as microbial factories due to their low contamination risk and low freshwater consumption. The halophilic archaea usually accumulate long chain C50 carotenoids, which are barely found in other organisms. Bacterioruberin (BR), the major C50 carotenoid, has multi-bioactivities, allowing potential application in food, cosmetic, and biomedical industries. However, the low yield impedes its large-scale application. This work figured out the BR synthesis characteristics and mechanism, and proposed several strategies for BR yield improvement, encouraging halophilic archaea to function as microbial factories for BR production. Meanwhile, the archaea have special evolutionary status and unique characteristics in taxonomy, the revelation of BR biosynthesis mechanism is beneficial for a better understanding of archaea.

An Arsenic Removal Technology and Its Application in Arsenic-Containing Copper

The usage of copper (Cu) ores containing low or no arsenic (As) has reduced, and Cu ores containing high levels of As have emerged as vital mineral resources for Cu extraction and processing. The quality of the Cu ores has decreased from 1.6% to approximately 1.0%. The proportion of As to Cu in 15% of Cu resources currently reaches 1:5. However, during the extraction and processing of Cu ores, As presents significant environmental harm. Hence, safely and effectively removing As is paramount in Cu smelting and processing, holding substantial importance in fostering environmentally sustainable practices within the Cu extraction and processing industry. This article consolidates the resource distribution of As-containing Cu (ACC) ores, comprehensively and systematically evaluates the present advancements in extracting techniques for these minerals, and identifies the challenges inherent in pyrometallurgical and wet processes for treating ACC deposits. Pyrometallurgy is a simple primary roasting technique and has widespread applicability in the treatment of various ACC minerals. Its disadvantages are the emission of exhaust gas and the high treatment costs associated with it. The wet arsenic removal method boasts advantages including minimal air pollution and a high resource recovery rate, significantly aiding in Cu concentrate recovery; its major drawback is the production of As-containing wastewater. The hydrometallurgical removal of As from ACC mines involves extracting As through leaching. Recently, biometallurgy has presented innovative solutions using specialized microorganisms to bioleach or bioabsorb As, but large-scale industrial applications still lack specific practical implementation. This review explores the underlying causes of the challenges encountered in processing ACC minerals. Additionally, it highlights pyrometallurgical roasting coupled with high-temperature filtration as a pivotal advancement in the extraction and processing of ACC ores.

High performance phenothiazine-based battery materials achieved by synergistic steric blocking and extended conjugation

Phenothiazine derivatives, as sustainable cathode materials for batteries, show significant promise for large-scale electrical energy storage applications. However, the irreversibility of the sulfur redox active center severely limits their energy density and discharge voltage in rechargeable organic batteries. This study concentrates on identifying the potential side reactions that contribute to the irreversibility of phenothiazine-based materials. We propose a molecular design strategy that synergistically blocks the active site and extends the conjugation, markedly improving the electrochemical reversibility of these materials. Our findings reveal that phenothiazine derivatives can undergo two successive, one-electron redox reactions without interference from chemical bond rearrangement and reactive radicals. The assembled cells, utilizing lithium (Li) and sodium (Na) as anodes, display two distinct discharge plateaus at 3.3/3.9 V vs. Li+/Li and 3.1/3.7 V vs. Na+/Na, respectively, with nearly identical contributions from the nitrogen (N) and sulfur (S) redox centers. The phenothiazine derivatives designed via this strategy rank among the few phenothiazine-based organic electrode materials capable of achieving highly reversible, two-electron transfer redox reactions in organic batteries.

Feasibility of microwave remediation of simulative crude oil-contaminated soil assisted by bluecoke-based modifiers

Microwave (MW) remediation of organics-contaminated soil technology offers the advantages of high efficiency and minimal damage, representing a new approach of soil thermal remediation. However, soil, being a weak MW-absorbing medium, struggles to convert MW energy into thermal energy, thus failing to attain the necessary temperature for thermal remediation. This paper prepared two new bluecoke (BC)-based modifiers (KHCO3@BC and KHCO3/MnO2@BC) to address temperature problem of MW remediation, as well as enhance soil quality. Their composition, structure and electromagnetic properties were analyzed to investigate their role in assisting with the MW remediation of an artificially crude oil-contaminated soil were investigated. Additionally, the industrial feasibility of MW remediation was addressed for the first time. The results showed that the KHCO3 and MnO2 particles in the two modifiers were covered on the BC surface and exhibited local agglomeration. Their carbon crystalline grain size increased, and the electromagnetic properties were weaker than those of the BC. Following 10 min of MW remediation assisted by KBC or KMnBC, the remediation temperatures exceeded 300 °C, with the removal rates of PHs reaching 76.16% and 88.31%, respectively. The organic matter content, soil potassium and mechanical fraction of the remediated soil were improved, but soil acidification still needed to be further addressed. The industrial application analysis indicated that the technical process and techno-economics of MW remediation of crude oil-contaminated soil were feasible, suggesting significant potential for the large-scale industrial application.

Microbial treatment of waste crumb rubber: Reducing energy consumption and harmful emissions during asphalt production process

The emergence of crumb rubber modified asphalt (CRMA) has promoted the recycling utilization of waste tires and the improvement of asphalt performance. However, its unsatisfactory storage stability and high construction temperature have brought about excessive energy consumption and environmental challenges. In this study, the waste crumb rubber (CR) was bio-desulfurized by the synergy between two types bacteria for 7 days and 14 days, respectively. On this basis, bio-desulfurization crumb rubber modified asphalt (BCRMA) was prepared. The desulfurization effect of CR was characterized. Thermal storage stability and environmental performance of BCRMA were mainly investigated. The results showed that bio-desulfurization increased the number of pores, surface roughness and specific surface area of CR, and decreased the content of sulfur element. Bio-desulfurization of CR improved the insufficient thermal storage stability of rubberized asphalt and reduced the risk of system segregation. Bio-desulfurization CR has been proven to be a promising environmentally friendly material that can effectively lower the release concentration and release type of harmful flue gas from CRMA. This study makes the large-scale promotion and application of CRMA possible.

More Biosurfactants and Fewer Synthetic Surfactants to Improve Alkali-Surfactant-Polymer Flooding: Feasibility Study and Large-Scale Field Application

Summary Alkali-surfactant-polymer (ASP) flooding has achieved highly enhanced oil recovery (EOR) in the Daqing Oil Field; however, there are concerns about synthetic surfactants owing to their high cost and difficulty in biodegradation. Cheap biosurfactants conform to human concepts of green circular economy; however, known biosurfactants, as well as their mixtures with alkali, cannot reduce water/oil interfacial tension (IFT) to ultralow values below 0.01 mN/m, which is necessary for ASP flooding to effectively mobilize residual oil. Therefore, we investigate the feasibility of partially replacing synthetic surfactants with biosurfactants rather than completely replacing them to improve ASP flooding. First, through a series of IFT tests, a blend of rhamnolipids (RLs) and alkylbenzene sulfonate (ABS) in a 1:1 mass ratio is determined to be the optimal mixed surfactant and labeled RL/ABS-opt. Second, the interfacial activities, phase behaviors, and wettability alteration capabilities of ASP solutions with RL/ABS-opt are studied. Then, 1.0 wt% NaOH and 0.2 wt% RL/ABS-opt are determined to construct a new ASP system. Subsequently, the waterflooded cores are displaced using the new and the classical ASP systems. Based on the promising experimental results, the new ASP system floods a test block of 56 wells for 3 years. The EOR and surfactant costs are calculated to determine the technical and economic effects. Finally, the concentrations of surfactants before and after activated sludge treatment (AST) are tested by spectrophotometry to verify the biodegradability of RLs better than that of ABS. The laboratory and field results indicate that more biosurfactants and fewer synthetic surfactants could improve ASP flooding to be more environmentally friendly and cost-effective with a higher EOR.