Increasing Energy Demand Research Articles

Design of a Bubbling Fluidized Bed Reactor for Bio-oil Production from Sawdust

Due to the ever increase in energy demand, it becomes imperative to design appropriate reactor for the conversion of available raw materials to energy source such as bio oil. A fluidized bed reactor is one the most promising reactor for the conversion of biomass to bio-oil via pyrolysis. This work take into consideration the design of fluidized bed reactor and its subsidiaries (cyclone, filter, condenser and feed hopper) to be used for bio-oil production using sawdust as the feedstock. The operating conditions were temperature between 400-6000C, pressure 9.9atm and flow rate 1.86m/s. From the design calculations, it was found that the volume of the reactor, area, height, diameter and minimum fluidized velocity were 15.0796mm3, 5026mm2, 300mm, 80mm and 1.86m/s respectively. The material for construction for the reactor is stainless steel because of its high thermal conductivity and resistance to corrosion.

Experimental investigation on the restart characterization of shale oil-water flow in a horizontal pipe

ABSTRACT With the dwindling conventional oil resources and increasing energy demand, shale oil development has gradually become a hot spot in the global energy industry. Moreover, the shale oil pipeline also inevitably experiences abnormal operations, such as shutdown and restart during regular maintenance or emergency accident repairs. However, previous restart research primarily focused on conventional crude oil pipelines, and there is still a research gap on shale oil-water flow. Therefore, this work conducted the shale oil-water restart flow experiment in the multi-test section pipe flow loop, considering the temperature (20–50℃), starting frequency (15–25 hz), and water content (0–80%). Based on the restart pressure and volume flow rate change, the response characteristics of start pressure are studied. Moreover, the changing rules of restart pressure are explored with starting frequency, temperature, and water content. Eventually, the variation trend of the restart pressure absolute errors between the calculated value and the experimental data with the starting frequency is analyzed. The results show that the restart pressure reaches the maximum around 10 s after the pump starts, and the maximum restart pressure is approximately 1.5 times the stabilized restart pressure. Moreover, the restart pressure increases linearly with the starting frequency and decays exponentially with the temperature and water content (after the inversion point). With the starting frequency reduced from 45 hz to 15 hz, the restart pressure reduces from 24.6 kPa to 10.0 kPa at 20°C. Furthermore, the empirical formulas can predict the starting pressure at low frequencies. This research lays a theoretical foundation for the safe restart of shale oil-water flow.

Unit commitment in solar‐based integrated energy distribution systems with electrical, thermal and natural gas flexibilities: Application of information gap decision theory

AbstractThe depleting oil reserves, air pollution and increasing energy demand, have overturned the focus of the scientific community to renewable energy sources. Among which the photovoltaic (PV) systems occupy more than half of the market share and are generally installed at the distribution level. The volatile and uncertain nature of these PV productions necessitates flexible resources in energy systems. To this end, the district heating systems have an outstanding flexibility on account of their high thermal inertia. This study investigates the optimal unit commitment scheduling for gas‐fired and non‐gas‐fired distributed generation units (NGU) in an integrated energy distribution system (IEDS) within the physical constraints of the electrical, natural gas and thermal energy distribution networks. Moreover, a planning‐based optimization framework is proposed to investigate the investment of battery storage systems in the electric distribution network under the high penetration of PV systems with the aim of enhancing flexibility and reducing the operating costs of the IEDS. In this framework, the information gap decision theory is deployed under risk‐averse and risk‐seeker strategies to deal with uncertain PV energy production. Additionally, the environmental emissions are considered in a multi‐objective approach. The IEDS is embodied through IEEE 33‐bus EDS, 20‐node natural gas network and an 8‐node district heating systems. Eventually, The proposed approach makes a noteworthy contribution to the advancement of solar energy systems in IEDS.

Metabolic Chaos in Kidney Disease: Unraveling Energy Dysregulation

Background: Acute kidney injury (AKI) and chronic kidney disease (CKD) share a fundamental disruption: metabolic dysfunction. Methods: A literature review was performed to determine the metabolic changes that occur in AKI and CKD as well as potential therapeutic targets related to these changes. Results: In AKI, increased energy demand in proximal tubular epithelial cells drives a shift from fatty acid oxidation (FAO) to glycolysis. Although this shift offers short-term support, it also heightens cellular vulnerability to further injury. As AKI progresses to CKD, metabolic disruption intensifies, with both FAO and glycolysis becoming downregulated, exacerbating cellular damage and fibrosis. These metabolic alterations are governed by shifts in gene expression and protein signaling pathways, which can now be precisely analyzed through advanced omics and histological methods. Conclusions: This review examines these metabolic disturbances and their roles in disease progression, highlighting therapeutic interventions that may restore metabolic balance and enhance kidney function. Many metabolic changes that occur in AKI and CKD can be utilized as therapeutic targets, indicating a need for future studies related to the clinical utility of these therapeutics.

An exploratory study of metabolomics in endogenous and cannabis-use-associated psychotic-like experiences in adolescence

In adolescence, psychotic-like experiences (PLE) may indicate potential prodromal symptoms preceding the onset of psychosis. Metabolomic studies have shown promise in providing valuable insights into predicting psychosis with enhanced precision compared to conventional clinical features. This study investigated metabolomic alterations associated with PLE in 76 depressed adolescents aged 14–20 years. Serum concentrations of 92 metabolites were analyzed with liquid chromatography–mass spectrometry. PLE were assessed using the Youth Experiences and Health (YEAH) questionnaire. The associations between PLE symptom dimensions (delusions, paranoia, hallucinations, negative symptoms, thought disorder, and dissociation) and metabolite concentrations were analyzed in linear regression models adjusted for different covariates. The symptom dimensions consistently correlated with the metabolome in different models, except those adjusted for cannabis use. Specifically, the hallucination dimension was associated with 13 metabolites (acetoacetic acid, allantoin, asparagine, decanoylcarnitine, D-glucuronic acid, guanidinoacetic acid, hexanoylcarnitine, homogentisic acid, leucine, NAD+, octanoylcarnitine, trimethylamine-N-oxide, and valine) in the various linear models. However, when adjusting for cannabis use, eight metabolites were associated with hallucinations (adenine, AMP, cAMP, chenodeoxycholic acid, cholic acid, L-kynurenine, neopterin, and D-ribose-5-phosphate). The results suggest diverse mechanisms underlying PLE in adolescence; hallucinatory experiences may be linked to inflammatory functions, while cannabis use may engage an alternative metabolic pathway related to increased energy demand and ketogenesis in inducing PLE. The limited sample of individuals with depression restricts the generalizability of these findings. Future research should explore whether various experiences and related metabolomic changes jointly predict the onset of psychoses and related disorders.

Multi-objective optimal configuration of CCHP system containing hybrid electric-hydrogen energy storage system

In order to cope with the increasing energy demand and achieve the “double carbon “goal of China’s 14th Five-Year Plan,” combined with hydrogen energy storage technology, it has the characteristics of zero pollution, high efficiency and rich source. In the context of reducing energy consumption and the vigorous development of hydrogen energy storage technology, a multi-objective optimization configuration model with economy, energy consumption index and carbon emission index is proposed, which takes into account the working characteristics of the hydrogen energy storage system, and the exothermic heat release from the electrolysis tanks and fuel cells when they are working to provide the loads with an additional heat source of the Combined Cooling, Heating and Power (CCHP) system, to reduce energy consumption and carbon emission. Finally, taking a region as an example, a multi-objective optimization algorithm based on decomposition is used to solve the model, so as to obtain a series of alternatives with better optimization effect. At the same time, the two-way projection method based on interval intuitionistic fuzzy information is used to make decisions, and the scheme that optimizes the economy, energy consumption index and carbon emission index is obtained, which verifies the feasibility of the system proposed in this paper.

Toward Carbon‐Negative Methanol Production from Biogas: Intensified Membrane Reactor

AbstractThe modern world's major challenges, such as global warming, air pollution, and increasing energy demands, escalate the importance of sustainable development and transition toward renewables using innovative and environmentally friendly solutions, such as intensifying chemical processes, to reduce carbon footprints effectively. Aiming to enhance the process toward negative carbon emissions, this perspective explores the intensified membrane reactors for reducing the energy intensity of converting biogas into methanol, a versatile chemical feedstock, and renewable liquid fuel. Syngas and methanol synthesis processes, catalysts, and membranes were explored, and novel reactor designs were proposed. Introduction of selective membranes into the catalytic reaction zone to combine synthesis separation steps could enhance the system efficiency and intensify the process by recycling energy and materials, besides reducing costs and required energy for the separation process: the continuous harnessing of products shifts reactions toward desired species while recycling energy and materials enhances the process efficiency, and separating water from methanol reduces the required energy and costs of extra processes for methanol separation. The successful implementation of this technology holds significant promise for sustainable developments in producing chemicals and renewable fuel from renewable biogas and reducing methane and carbon dioxide emissions toward achieving carbon‐negative technologies.

Exploring advanced microwave strategy for the synthesis of two-dimensional energy materials

The rapid pace of technology and increasing energy demands underscore the urgent need for eco-friendly materials with exceptional energy conversion and storage capabilities. Two-dimensional (2D) energy materials, characterized by unique physicochemical properties, hold great promise in renewable energy conversion, catalysis, and electronics. Nevertheless, conventional synthesis methods often falter in balancing high quality, high yield, and cost-effectiveness, presenting substantial obstacles to their large-scale application. Microwave-assisted synthesis, characterized by its rapid and efficient process, emerges as a promising approach to surmount these limitations. This review meticulously examines the pivotal role of microwave-assisted synthesis in the preparation of 2D materials, highlighting its profound impact on enhancing material quality and production efficiency. By scrutinizing the unique physical properties of microwaves and their applications in material synthesis, the review elucidates the innovative contributions of microwave technology to materials science. Furthermore, it delves into the intricate influence of microwave parameter control on the synthesis process and resultant material properties, offering insight into the potential of microwave technology for the precise modulation of material structure and functionality. This comprehensive analysis underscores microwave-assisted synthesis as a viable solution for overcoming current challenges, thereby advancing the development of high-performance 2D energy materials.

Performance evaluation of nano-enhanced phase change materials for thermal energy storage: An experimental study

In rapidly developing economies, the increasing energy demand and fossil fuel consumption have made the need for renewable energy sources and efficient thermal energy storage (TES) solutions more urgent than ever. This study focuses on enhancing the thermal energy storage capabilities of paraffin-based phase change materials (PCMs) by incorporating Al2O3, MgO, and CuO nanoparticles. The evaluation of nano-enhanced PCMs focused on their melting temperatures, thermal storage capacities, thermal conductivities, and charge/discharge times. The experimental results revealed significant changes in the thermal properties of the nano-enhanced PCMs compared to pure paraffin. The melting temperature was raised by 2 °C due to Al2O3 nanoparticles, whereas CuO and MgO nanoparticles decreased it by 1.7 °C and 1.8 °C, respectively. Compared to pure paraffin, Al2O3-PW, MgO-PW, and CuO-PW exhibited improvements of 13 %, 39 %, and 48 % in thermal conductivities, respectively. CuO-doped paraffin showed an 11.8 % decrease in discharge time, suggesting its suitability for rapid heat transfer applications like defrosting systems or thermal management in electronics. On the other hand, paraffin doped with MgO showed a minimal 2.24 % reduction in discharge time, indicating its effectiveness in applications requiring heat retention, particularly for improved thermal insulation in building materials. The results highlighted the potential of nano-enhanced PCMs in energy storage and construction is underlined, offering a sustainable approach to improving energy efficiency in various sectors.

The risk of increasing energy demand while pursuing decarbonisation: the case of the e-fuels in the EU aviation sector

The European Union target of a net-zero economy by mid-century requires an unprecedented effort in the reduction of carbon emissions. Aviation is among the most difficult sectors to decarbonize, and since direct electrification is unlikely to become a viable option in the short-term, other alternatives are considered, including biofuels and e-fuels. The blending mandates recently approved in the ReFuelEU Aviation package (35% of e-fuels at 2050) will require devoting an important amount of renewable electricity to produce e-fuels, increasing the relative weight of aviation with respect other sectors in terms of energy consumption. Aviation accounts today for 13% of the EU27 (2019) energy consumption for transport, while in 2050 this is expected to reach the 22%. This “magnifying effect” for the energy required by the sector, due to the low overall conversion efficiency of e-fuel production, will likely foster a competition for the access to renewable energy. This shift toward the aviation sector may occur to detriment of other applications potentially most effective in decreasing carbon emissions per unit of electricity. This apparent dichotomy between GHG reduction and energy efficiency could reduce the actual effectiveness of existing policies and the possibility of fostering similar initiatives in other countries.

Transition metal-assisted layer-by-layer binder free deposition for high-performance energy storage devices

The increasing energy demands of the world necessitate the development of advanced energy storage systems. Hybrid supercapacitors (HSCs) have emerged as promising candidates, combining the high specific power density (PS) of supercapacitors (SCs) with the high specific energy density (ES) of batteries (BATs). However, its performance is dependent on the properties of electrode materials, which need enhancements in conductivity, surface area, and electrochemical stability. In this study, we utilized magnetron sputtering technique for exploring the potential of interface engineering to improve the electrochemical performance of tungsten disulfide (WS2) as a battery grade electrode material by incorporating chromium (Cr) and titanium (Ti) as an interfacial layer. This strategic modification significantly increased the conductivity, charge transfer efficiency, and structural stability of the WS2 electrode. Electrochemical experimentation in both half-cell and full-cell configurations revealed that the WS2/Cr and WS2/Ti electrode exhibits superior CS [2400 and 3800] F/g, respectively compared to pristine WS2. Fabricated WS2/Cr//AC and WS2/Ti//AC attained ES [95 and 117] Wh/kg and PS [6800 and 8500] W/kg, respectively. The outcomes from the electrochemical testing further demonstrated the superior cyclic stability of WS2/Cr//AC and WS2/Ti//AC with [96.5 and 98.3] % which shows that Cr and Ti as an interfacial layer not only mitigates the limitations of WS2 but also enables the devices to achieve higher performance metrics, underscoring the critical role of interface engineering in advancing HSCs technologies.

Effect of Architecture and Inference Parameters of Artificial Neural Network Models in the Detection Task on Energy Demand

Artificial neural network models for the task of detection are used in many fields and find various applications. Models of this kind require adequate computational resources and thus require adequate energy expenditure. The increase in the number of parameters, the complexity of architectures, and the need to process large data sets significantly increase energy consumption, which is becoming a key sustainability challenge. Optimization of computing and the development of energy-efficient hardware technologies are essential to reduce the energy footprint of these models. This article examines the effect of the type of model, as well as its parameters, on energy consumption during inference. For this purpose, sensors built into the graphics card were used, and software was developed to measure the energy demand of the graphics card for different architectures of YOLO models (v8, v9, v10), as well as for different batch and model sizes. This study showed that the increase in energy demand is not linearly dependent on batch size. After a certain level of batch size, the energy demand begins to decrease. This dependence does not occur only for n/t size models. Optimum utilization of computing power due to the number of processed images for the studied models occurs at the maximum studied batch size. In addition, tests were conducted on an embedded device.

Perancangan dan Analisis Tekno Ekonomi PLTS On-Grid System sebagai Supply Energi Listrik Masjid Al-Istiqamah Politeknik Negeri Jember

The increasing energy demand is directly proportional to the growing population and technological advancements. The energy needs in Indonesia largely rely on fossil fuels, which are limited and environmentally unfriendly due to their emission characteristics. The potential of solar energy in Indonesia is around 4.8 kWh/m2, making it a renewable and environmentally friendly energy source that can be utilized for Solar Power Plants (PLTS). The aim of this research is to design an on-grid PLTS system and conduct techno-economic analysis using PVSyst software. This design requires 14 Longi Solar/LR5-72HPH-550M solar panels and 1 Huawei SUN2000-6KTL-M1 inverter. The estimated electricity production is 10,852 kWh/year in the first year. The initial investment cost for this PLTS system is Rp. 120,343,517.00, with estimated savings over 25 years amounting to Rp. 270,115,412.00. Economically, based on the feasibility analysis using the LWBP tariff calculation method, the NPV is Rp. 2,174,707.00, BCR is 1.68, and PBP is 11.8 years. Meanwhile, based on the feasibility analysis using the LCoE calculation method, the NPV is Rp. 74,877,690.00, BCR is 2.61, and PBP is 7.5 years. Based on the conducted research, the construction of this PLTS is deemed feasible to be implemented.

GAPS OF INDIAN ELECTRICAL ENERGY SECTOR AND ITS OPTIMAL MITIGATION BY USING OPTIMAL UTILIZATION OF INDIAN RENEWABLE ENERGY POLICY WITH THE HELP OF THE P&O MPPT TECHNIQUE

Developing countries, especially, India, depend importantly on energy sources to perform their country’s industrial and economic activities. Mainly the two factors continuous population growth of the country and the rapid growth rate of industrialization of the country, the gap between electrical energy supply and demand for electrical energy is slowly and consistently increasing. To resolve this unevenness, there is a jointly planned attempt is required to enhance the contribution of renewable energy in the all over mix of energy. Despite these attempts, unexpected surges caused by the sector of domestic energy consumption could lead to important shortfalls between energy requirements at peak demand and available supply in India. As a solution to this challenge, the Union government of India has launched a new policy, named PM SURYA GHAR: MUFT BIJLI YOJANA, targeted to handle this crucial problem head-on. This initiative requires addressing the increasing energy demand by promoting the utilization of solar power in households throughout the length and breadth of the country. With the implementation techniques of Photo voltaic optimization, this analysis explores how such types of strategies can play a significant role in filling the gap between the energy supply-demand in the Indian context. Employing the solar energy potential and optimizing and utilization of solar energy, creates a path to not only meet the enhancing energy requirements but also creates the path for a more environmentally friendly and sustainable energy in India. By integration of innovative technologies and solutions of renewable energy holds the key to ensuring a balanced, sustainable, stable energy supply for the future of India and country’s growth and development.

Tool–Branch Interaction Mechanism of Impact-Pruning Process Based on Finite Element Method

This study addresses the necessity for a more profound comprehension of the mechanical behavior and fracture mechanisms of tree branches during impact pruning. The methodologies of the research are to develop a failure model of impact-cutting mechanics and a tool–branch interaction model using the finite element method (FEM). The validation of the model was conducted through the measurement of cutting forces and cross-sectional morphology in the field. A comparative analysis between experimental and simulation data revealed an average relative error below 15% for cutting force and below 10% for the cross-sectional ratio, thereby confirming the accuracy of the model. The findings indicate the presence of plastic deformation within the cutting zone, with elastic deformation prevailing in the surrounding region. As the branch approaches the yield point, the phenomenon of plastic deformation intensifies, resulting in a notable increase in internal energy demands, particularly in larger branches. The optimal pruning diameter was identified as 15 mm. An increase in cutting velocity raises the peak cutting force by 460.9 N per m/s, while a 1° increase in the blade wedge angle adds 34.9 N. A reduction in normal stress by increasing the tool back angle improves energy efficiency. This study provides insights to optimize pruning practices, enhancing efficiency and precision.

Sustainability Prediction by Evaluating the Emergy of a Co-Treatment System for Municipal Wastewater and Acidic Water Using Intermittent Electrocoagulation

The objective of this research was to evaluate the sustainability of a co-treatment system that combines Municipal Wastewater (MW) and Acid Mine Drainage (AMD) through the technique of intermittent electrocoagulation, applied as an advanced solution to improve contaminant removal efficiency and optimize energy balance. Four scenarios were analyzed: Treatment I (with a 1/7 ratio of urban wastewater to AMD), Treatment II (which includes an artificial wetland), Treatment IIIa (which introduces electrocoagulation to enhance sulfate removal and pH regulation), and Treatment IIIb (which employs a 1/15 ratio of AMD to eutrophic water). The methodology focused on calculating key sustainability indicators such as the Net Yield Ratio (EYR), Emergy Inversion Ratio (EIR), Environmental Loading Ratio (ELR), and Sustainability Index (SI), in order to assess the impact of each technology on the energy efficiency and environmental load of the system. The results showed that, although Treatment IIIa was effective in contaminant removal, the EIR increased to 0.18 and the ELR rose to 0.62, indicating a higher reliance on non-renewable inputs due to increased energy demand. However, Treatment IIIb, which combines electrocoagulation with eutrophic water, significantly improved the sustainability of the system, achieving an SI of 2.31 and an ELR of 1.22, reflecting a reduction in energy efficiency due to intensive use of external resources, but overall greater sustainability compared to the other scenarios. This research concludes that intermittent electrocoagulation, when integrated with synergistic resources like eutrophic water, can enhance contaminant removal efficiency and improve the use of renewable resources, minimizing environmental load and increasing the sustainability of wastewater treatment systems.

Enhancing energy control for a hybrid system comprising a wind turbine, diesel generator, and storage systems

The increase in demand for electrical energy has made renewable energy sources, such as wind power, increasingly attractive. However, intermittency and variability represent the major problems of these types of energies. The hybridization of several energy sources allows to have a reliable and efficient supply system. This paper was interested in the control of a hybrid energy system, which includes a wind turbine, storage systems (batteries and super-capacitors) and a conventional diesel generator, with the aim of generating constant power. A control strategy is developed taking into account the various constraints of the hybrid system. Both of storage systems as well as the diesel generator operate according to the modes presented in the supervision algorithm to absorb and compensate the fluctuation of the wind energy and reach to a constant energy flow. The super-capacitor operates before the battery to absorb the power peaks in both charge and discharge modes. The hybrid system is simulated using MATLAB/Simulink software, and the results are provided in order to show the effectiveness of this control strategy.

Developmental nicotine exposure alters cardiovascular structure and function in neonatal and juvenile rats.

Here we test the hypothesis that continuous nicotine exposure throughout pre- and postnatal development (developmental nicotine exposure, DNE) alters cardiovascular structure and function in neonatal and juvenile rats. Echocardiography showed that DNE reduced left ventricular mass, left ventricular outflow tract (LVOT) diameter, and posterior wall thickness, but only in females. Both male and female DNE rats had a lower end-systolic volume, higher ejection fraction, and increased fractional shortening, with unchanged stroke volume and cardiac output. Left ventricular single cardiac myocytes from male and female DNE animals exhibited increased calcium-evoked maximal tension with no effect on EC50. Tail-cuff plethysmography in awake rats showed that DNE males had lower systolic blood pressure and higher heart rate than control males. No significant changes in preload, afterload, or the in vitro renal artery response to vasodilators was observed. The results suggest that DNE enhances myocyte tension-generating capacity, possibly compensating for an unknown developmental insult, which may differ in males and females. While this adaptation maintains normal resting cardiac function, it may lead to reduced cardiac reserve, increased energy demand, and elevated oxidative stress, potentially compromising both short-and-long-term cardiovascular health in developing neonates.

Assessing Photo-Voltaic Potential in Urban Environments: A Comparative Study between Aerial Photogrammetry and LiDAR Technologies

Abstract. Urban development and population growth have significantly increased energy demands, predominantly met by non-renewable resources, negatively impacting nature and climate. Consequently, there has been a global shift towards renewable energy sources, with solar energy being widely adopted. Photovoltaic (PV) potential measures the usable electricity from solar energy using PV technology. With conventional methods, estimating PV potential involves converting 3D point cloud data to 2.5D elevation models, which can affect the accuracy of the estimation. A research gap exists in using adequate 3D point cloud datasets for PV potential estimation considering roof surface area and the surface normal vectors. This study compares aerial photogrammetry and aerial LiDAR point clouds for PV potential estimation against the DSM-based approach. Accurate PV potential estimation must consider solar incidence, roof area, azimuth, tilt angles, and PV efficiency. Traditional 2.5D methods often overlook crucial azimuth and tilt data, limiting the accuracy of the PV estimation. Converting 3D data to 2.5D may result in information loss, while 3D analyses offer higher accuracy. To investigate the mentioned gaps, this research aims to evaluate the capabilities of photogrammetry and LiDAR for urban PV potential estimation, highlighting their feasibility and accuracy over 2.5D methods.

Data-independent acquisition proteomic analysis of the brain microvasculature in Alzheimer’s disease identifies major pathways of dysfunction and upregulation of cytoprotective responses

Brain microvascular dysfunction is an important feature of Alzheimer’s disease (AD). To better understand the brain microvascular molecular signatures of AD, we processed and analyzed isolated human brain microvessels by data-independent acquisition liquid chromatography with tandem mass spectrometry (DIA LC–MS/MS) to generate a quantitative dataset at the peptide and protein level. Brain microvessels were isolated from parietal cortex grey matter using protocols that preserve viability for downstream functional studies. Our cohort included 23 subjects with clinical and neuropathologic concordance for Alzheimer’s disease, and 21 age-matched controls. In our analysis, we identified 168 proteins whose abundance was significantly increased, and no proteins that were significantly decreased in AD. The most highly increased proteins included amyloid beta, tau, midkine, SPARC related modular calcium binding 1 (SMOC1), and fatty acid binding protein 7 (FABP7). Additionally, Gene Ontology (GO) enrichment analysis identified the enrichment of increased proteins involved in cellular detoxification and antioxidative responses. A systematic evaluation of protein functions using the UniProt database identified groupings into common functional themes including the regulation of cellular proliferation, cellular differentiation and survival, inflammation, extracellular matrix, cell stress responses, metabolism, coagulation and heme breakdown, protein degradation, cytoskeleton, subcellular trafficking, cell motility, and cell signaling. This suggests that AD brain microvessels exist in a stressed state of increased energy demand, and mount a compensatory response to ongoing oxidative and cellular damage that is associated with AD. We also used public RNAseq databases to identify cell-type enriched genes that were detected at the protein level and found no changes in abundance of these proteins between control and AD groups, indicating that changes in cellular composition of the isolated microvessels were minimal between AD and no-AD groups. Using public data, we additionally found that under half of the proteins that were significantly increased in AD microvessels had concordant changes in brain microvascular mRNA, implying substantial discordance between gene and protein levels. Together, our results offer novel insights into the molecular underpinnings of brain microvascular dysfunction in AD.