Adsorption-type aluminium-based direct lithium extraction: The effect of heat, salinity and lithium content

Conventional lithium production through solar evaporation is considered a time-consuming procedure, taking a substantial 12 to 18 months with significant environmental impacts such as aquifer depletion and damaging the basin\u27s complex hydrological system. Direct Lithium Extraction (DLE) has emerged as a promising alternative for lithium extraction from brines, offering reduced environmental impact. Although adsorption-type DLE with aluminium-based adsorbents is the sole commercial technology of DLE, a debate persists concerning its Technology Readiness Level (TRL), which challenges the prevailing notion that adsorption-type DLE undeniably reaches a TRL of 9. Within this narrative, we propose that adsorption is capable of attaining its highest potential TRL in lithium recovery from brines when three critical conditions are met: the presence of a certain level of salinity, a minimum lithium content in the brine, and a heat source to heat up the brine. In this account, an attempt has been made to elucidate the role of these three minimum criteria during adsorption-type DLE

Applying Membrane Distillation for the Recovery of Nitrate from Saline Water Using PVDF Membranes Modified as Superhydrophobic Membranes.

In this study, a flat sheet direct contact membrane distillation (DCMD) module was designed to eliminate nitrate from water. A polyvinylidene fluoride (PVDF) membrane was used in a DCMD process at an ambient pressure and at a temperature lower than the boiling point of water. The electrical conductivity of the feed containing nitrate increased, while the electrical conductivity of the permeate remained constant during the entire process. The results indicated that the nitrate ions failed to pass through the membrane and their concentration in the feed increased as pure water passed through the membrane. Consequently, the membrane was modified using TiO2 nanoparticles to make a hierarchical surface with multi-layer roughness on the micro/nanoscales. Furthermore, 1H,1H,2H,2H-Perfluorododecyltrichlorosilane (FTCS) was added to the modified surface to change its hydrophobic properties into superhydrophobic properties and to improve its performance. The results for both membranes were compared and reported on a pilot scale using MATLAB. In the experimental scale (a membrane surface area of 0.0014 m2, temperature of 77 °C, nitrate concentration of 0.9 g/Kg, and flow rate of 0.0032 Kg/s), the flux was 2.3 Kgm-2h-1. The simulation results of MATLAB using these data showed that for the removal of nitrate (with a concentration of 35 g/Kg) from the intake feed with a flow rate of 1 Kg/s and flux of 0.96 Kgm-2h-1, a membrane surface area of 0.5 m2 was needed

Artificial intelligence-based material discovery for clean energy future

Artificial intelligence (AI)-assisted materials design and discovery methods can come to the aid of global concerns for introducing new efficient materials in different applications. Also, a sustainable clean future requires a transition to a low-carbon economy that is material-intensive. AI-assisted methods advent as inexpensive and accelerated methods in the design of new materials for clean energies. Herein, the emerging research area of AI-assisted material discovery with a focus on developing clean energies is discussed. The applications, advantages, and challenges of using AI in material discovery are discussed and the future perspective of using AI in clean energy is studied. This perspective paves the way for a better understanding of the future of AI applications in clean energies

Chronic complications of diabetes mellitus in newly diagnosed patients

AbstractThe prevalence of Diabetes Mellitus (DM) has increased in recent decades. This study was designed to determine retinopathy, neuropathy, nephropathy, hypertension and hyperlipidemia and their interdependence in newly diagnosed diabetic patients. In this study, 200 consecutive newly diagnosed patients were evaluated and screening tests for retinopathy, neuropathy, nephropathy, hypertension and hyperlipidemia were undertaken.The frequency of positive screening tests for hyperlipidemia, hypertension, neuropathy, nephropathy and retinopathy was found to be 73.5%, 58.5%, 52%, 10%, and 6% respectively.A significant proportion of newly diagnosed diabetic patients have signs of these chronic complications

Pattern of recovery following total shoulder arthroplasty and humeral head replacement

BACKGROUND: Understanding the pattern of recovery and expected rate of change after shoulder arthroplasty is helpful to clinicians and patients for setting realistic expectations and goals. The purpose of this study was to describe the pattern of recovery over a 2-year period for patients receiving either a Total Shoulder Arthroplasty (TSA) or Humeral Head Replacement (HHR). METHODS: This was a secondary analysis of prospectively collected data of patients who had undergone TSA or HHR and were followed for up to 2 years. Patients were seen prior to surgery and at 6 months, one year and two years after surgery and completed the American Shoulder and Elbow Surgeon’s (ASES) questionnaire, Relative Constant Murley score (RCMS) and underwent range of motion and strength assessment. RESULTS: Data of 134 patients who had surgery from April 2001 to July 2011 were used for analysis. One hundred and eight patients underwent TSA (81%) and 26 (19%) had HHR. Both surgeries were associated with a statistically significant improvement in physical symptoms, ASES, RCMS, range of motion and strength (p <0.0001). The greatest change for all outcomes occurred within the first 6-months of surgery. Improvement in ASES, RCMS continued up to 12-months and then plateaued. Improvement in physical symptoms leveled off at 6-months in the HHR group but continued up to 12-months in the TSR group. Strength showed improvement in both groups up to 24-months post-surgery. CONCLUSION: Both TSA and HHR groups showed a statistically significant improvement in perceived disability, range of motion and strength over two years with the greatest improvement made by 6 months. The recovery profiles for the surgeries showed different patterns. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2474-15-306) contains supplementary material, which is available to authorized users

Comparison of quality of clinical supervision as perceived by attending physicians and residents in university teaching hospitals in Tehran

Background: Clinical supervision is an important factor in the development of competency in residency program. Attending physicians play a key role in supervision of residents. However little is known about how attending physicians and residents perceive the quality of clinical supervision. The aim of this study was to explore the differences between perceived qualities of supervision in these two groups in different wards in teaching hospitals in Tehran, Iran. Methods: A valid questionnaire were completed by 219 attending physicians and residents from surgery, psychiatry, gynecology, pediatrics, internal medicine, orthopedics and radiology wards in two teaching hospital affiliated to Iran University of Medical Sciences. This questionnaire contained 15 items in regards to supervisory roles, rated on a five point Likert scale (1=never, 2=seldom, 3=sometimes, 4=often, 5=always). Results: Out of 219 participants, 90 (41) were attending physicians and 129 (59) were residents. The overall mean±SD scores of perceived clinical supervision achieved by attending physicians and residents were respectively, 4.20±0.5 and 3.00±0.7 which was statistically significant (p<0.05). Attending physicians and residents acquired minimum scores (mean=4.06 and 2.7, respectively) regarding expectation from their supervisor to know and do during training period of residency. Conclusion: It seems that the clinical supervisory does not have an efficient performance in teaching hospitals which needs to be more assessed and improved. Therefore it is suggested that policymakers in medical education system pay more attention to this important issue and enhance some faculty development programs for clinical educators in Iran

Population genetic structure of Neogobius caspius (Eichwald ,1831) in the South Caspian Sea using PCR-RFLP Marker

Neogobius caspius is a small benthic fish that is native to the Caspian Sea. The importance of this fish is because of it is role as a main food resource of the sturgeon fish. The genetic diversity of N. caspius population in the Caspian Sea was studied using PCR- RFLP technique. A total of 135 samples of N. caspius were collected from coastal line in the north Caspian sea, including specimens from coasts of Anzali , Torkman Port and Chalus. Genomic DNA was extracted by phenol-chloroform method and then was amplified using a pair primer of cytochrom b gene, 2 tRNA gene and the control region sequences by a thermal cycler. D2 (5'-CCGGAGTATGTAGGGCATTCTCAC-3'), CY1 (5'-YYTAACCRRGACYAATGACTTGA-3') 12 restriction enzyme were used to digest the target gene region including: Alul HincII —Tas1 —Rsa1 -MboI -DraI -BSeNI(BSRI) Alw261(BsmAI). Bsul 51 Hin11 Bsh12851- BsuRI(HaeIII) digested PCR products were observed by silver staining method followed by Polyacrylamide gel electrophoresis (PAGE). The results were shown the same pattern among the species. There was no polymorphism and no differentiation in population in the Neogobius caspius fish and all individuals have shown homogenous genotype

Microplastics fouling mitigation in forward osmosis membranes by the molecular assembly of sulfobetaine zwitterion

Forward osmosis (FO) membranes have potential for the efficient water and wastewater treatment applications. However, their development has faced significant challenges due to their fouling propensity. In this study, FO membranes modified with sulfobetaine zwitterions (i.e., [2-(Methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl) ammonium hydroxide) were fabricated and used for the first time to address microplastic (MP) fouling issue. Water flux, reverse salt flux (RSF), fouling, and flux recovery were evaluated for the membranes loaded with different quantities of the zwitterions ranging from 0.25 % to 2 %. The developed membranes were tested over 49 h with feed solutions containing polyethylene MPs and bovine serum albumin (BSA) to evaluate their fouling resistance. The synergistic effects of the two foulants indicated that the MPs were the primary cause of fouling. The presence of BSA effectively reduced the blocking effect of MPs and therefore lowers overall fouling. Additionally, improved water flux, structural parameter (S), and RSF were reported for the modified membranes. The zwitterion\u27s unique structure with hydrophilic groups (C[dbnd]O and O[dbnd]S[dbnd]O) resulted in high flux recovery rates of over 90 % for all modified membranes within only 30 min of physical cleaning upon fouling tests. The results demonstrate the high potential of the modification method for targeting the removal of MPs in TFC-based membranes

Harnessing the power of neural networks for the investigation of solar-driven membrane distillation systems under the dynamic operation mode

Accurate modeling of solar-driven direct contact membrane distillation systems (DCMD) can enhance the commercialization of these promising systems. However, the existing dynamic mathematical models for predicting the performance of these systems are complex and computationally expensive. This is due to the intermittent nature of solar energy and complex heat/mass transfer of different components of solar-driven DCMD systems (solar collectors, MD modules and storage tanks). This study applies a machine learning-based approach to model the dynamic nature of a solar-driven DCMD system for the first time. A small-scale rig was designed and fabricated to experimentally assess the performance of the system over 20 days. The predictive capabilities of two neural network models: multilayer perceptron (MLP) and long short-term memory (LSTM) were then comprehensively examined to predict the permeate flux, efficiency and gain-output-ratio (GOR). The results showed that both models can efficiently predict the dynamic performance of solar-driven DCMD systems, where MLP outperformed the LSTM model overall, especially in the prediction of efficiency. Additionally, it was indicated that the accuracy of the models for the prediction of GOR can be significantly improved by increasing the size of the dataset