Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method

Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.

Data-mining and atmospheric corrosion resistance evaluation of Sn-and Sb-additional low alloy steel based on big data technology

Machine-learning and big data are among the latest approaches in corrosion research.The biggest challenge in corrosion research is to accurately predict how materials will degrade in a given environment.Corrosion big data is the application of mathematical methods to huge amounts of data to find correlations and infer probabilities.It is possible to use corrosion big data method to distinguish the influence of the minimal changes of alloying elements and small differences in microstructure on corrosion resistance of low alloy steels.In this research,corrosion big data evaluation methods and machine learning were used to study the effect of Sb and Sn,as well as environmental factors on the corrosion behavior of low alloy steels.Results depict corrosion big data method can accurately identify the influence of various factors on corrosion resistance of low alloy and is an effective and promising way in corrosion research.

Stress corrosion cracking behavior of high-strength mooring-chain steel in the SO_(2)-polluted coastal atmosphere

21Cr2NiMo steel is widely used to stabilize offshore oil platforms;however,it suffers from stress-corrosion cracking(SCC).Herein,we studied the SCC behavior of 21Cr2NiMo steel in SO_(2)-polluted coastal atmospheres.Electrochemical tests revealed that the addition of SO_(2) increased the corrosion current.Rust characterization showed that SO_(2) addition densified the corrosion products and promoted pitting.Furthermore,slow strain rate tests demonstrated a high susceptibility to SCC in high SO_(2) contents.Fracture morphologies revealed that the stress-corrosion cracks initiated at corrosion pits and the crack propagation showed transgranular and intergranular cracking modes.In conclusion,SCC is mix-controlled by anodic dissolution and hydrogen embrittlement mechanisms.

Anti-osteosarcoma trimodal synergistic therapy using NiFe-LDH and MXene nanocomposite for enhanced biocompatibility and efficacy

Osteosarcoma is usually resistant to immunotherapy and,thus primarily relies on surgical resection and high-dosage chemotherapy.Unfortunately,less invasive or toxic therapies such as photothermal therapy(PTT)and chemodynamic therapy(CDT)generally failed to show satisfactory outcomes.Adequate multimodal therapies with proper safety profiles may provide better solutions for osteosarcoma.Herein,a simple nanocomposite that synergistically combines CDT,PTT,and chemotherapy for osteosarcoma treatment was fabricated.In this composite,small 2D Ni Fe-LDH flakes were processed into 3D hollow nanospheres via template methods to encapsulate 5-Fluorouracil(5-FU)with high loading capacity.The nanospheres were then adsorbed onto larger 2D Ti3C2MXene monolayers and finally shielded by bovine serum albumin(BSA)to form 5-FU@Ni Fe-LDH/Ti3C2/BSA nanoplatforms(5NiTiB).Both in vitro and in vivo data demonstrated that the 5-FU induced chemotherapy,Ni Fe-LDH driven chemodynamic effects,and MXene-based photothermal killing collectively exhibited a synergistic“all-in-one”anti-tumor effect.5NiTiB improved tumor suppression rate from<5%by 5-FU alone to~80.1%.This nanotherapeutic platform achieved higher therapeutic efficacy with a lower agent dose,thereby minimizing side effects.Moreover,the composite is simple to produce,enabling the fine-tuning of dosages to suit different requirements.Thus,the platform is versatile and efficient,with potential for further development.

A new understanding of the effect of Cr on the corrosion resistance evolution of weathering steel based on big data technology

In this work,we studied the effect of Cr element on the corrosion resistance evolution of weathering steel based on corrosion big data technology.It suggested that corrosion big data technology is suitable for evaluation of the effect of microalloying Cr element on the corrosion evolution behavior of weathering steel.New understandings prove that the effect of Cr on the corrosion process is dynamic rather than static,the processes is affected by both of the environmental factors and the electrochemical or chemical reactions in the rust layer.Besides,Cr element has both beneficial effect and detrimental effect on the corrosion resistance of weathering steel.The beneficial effect is that the general corrosion resistance of Cr-additional steel is better than that of Cr-free steel,while the detrimental effect is that localized corrosion is intensified as the increase of Cr content in the Cr-additional steel.

Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors

Atmospheric corrosion monitoring(ACM)sensors were employed to study the initial atmospheric corrosion of carbon steels over a one-month period in six outdoor dynamic atmospheric environments in China.Based on the~250,000 corrosion data sets collected,the environmental impacts of relative humidity,temperature and rainfall on the initial corrosion behavior of carbon steels were investigated.The results showed that rainfall was the strongest environmental factor influencing the initial atmospheric corrosion rate.Relative humidity significantly influenced the corrosion of carbon steels in low-precipitation environments and non-rainfall period.

Distinct beneficial effect of Sn on the corrosion resistance of Cr-Mo low alloy steel

In this work,the beneficial effect of Sn addition on the corrosion resistance mechanism of Cr-Mo low alloy steel was studied.Results demonstrated that Sn improves the corrosion resistance of the steel matrix mainly by influencing the microstructural transformation.Sn addition and the synergistic effect of Sn,Cr,and Mo promote the formation of α-FeOOH,SnO_(2),SnO,Cr(OH)_(3),and molybdates,lead to the improved protection and stability of the rust layer.This synergistic effect also endows the inner rust layer with cation selectivity,preventing the further penetration of Cl-and inhibiting the localized corrosion of steel.