Materials Science Engineering Applications

Google's quantum computer achieved a measurable advantage over classical computers for molecular analysis. Their Quantum Echoes algorithm represents progress toward practical quantum computing applications in chemistry and materials science. The research details: ↳ Published in Nature with peer review ↳ 13,000x performance improvement on specific calculations ↳ Tested on molecules with 15 and 28 atoms ↳ Results verified against established Nuclear Magnetic Resonance data The algorithm functions as a "molecular ruler" that can measure atomic distances and interactions. It uses quantum interference effects to amplify measurement signals, providing sensitivity that classical computers struggle to achieve efficiently. Current applications being explored include: ↳ Drug development for understanding molecular binding ↳ Materials research for battery and polymer characterization   ↳ Chemical analysis for determining molecular structures ↳ Nuclear Magnetic Resonance enhancement for laboratory use Google worked with UC Berkeley to validate the approach. The quantum computer analyzed molecular structures and provided information that traditional methods either missed or required significantly more computational time to obtain. The research addresses a practical problem in computational chemistry where molecular modeling requires substantial computing resources. Quantum computers may offer efficiency advantages for these specific types of calculations. This work follows Google's established quantum computing research program, building on their previous demonstrations of quantum error correction and computational complexity advantages. Which scientific fields do you think will adopt quantum-enhanced analysis methods first? ♻️ Share this to inspire someone. ➕ Follow me to stay in touch.

Why Stones/Gravel are Used on the ground of Grid Substations ?💡 1️⃣ Reducing Contact Area & Increasing Safety Walking on bare soil provide large contact area between your feet and the ground, creating a low-resistance path for leakage currents. Stones/gravel reduce the effective contact area. Your feet touch only the tops of stones, increasing resistance and reducing step voltage risk. 2️⃣ Minimizing Step and Touch Voltage High-voltage equipment can leak current to the ground. Smaller contact area + high-resistance stones → less current flows through personnel, enhancing safety. 3️⃣ Additional Benefits Drainage: Stones allow rainwater to drain quickly, preventing waterlogging. Fire Safety: Non-flammable, reducing the risk from sparks or transformer oil leaks. Maintenance & Cleanliness: Prevents mud accumulation and vegetation growth, keeping the substation organized. ⚡ Key Concept: Using stones acts as a high resistance insulating layer, making substations safer for personnel while maintaining operational integrity. See IEEE 80 for more details. #SubstationGrounding #SubstationDesign #EarthingSystems #GravelBedding #PowerSystemSafety #EHVDesign #GridReliability #IEEEStandards #ElectricalEngineering #TransformerYard #StepAndTouchPotential

Sustainability challenges can’t be solved in isolation. A systems-thinking approach is needed that addresses the interconnections in complex systems to create impactful, lasting solutions. Solar Energy Through a Systems Lens While solar power is a clean alternative to fossil fuels, we have to consider the environmental and social trade-offs: ❇️ Raw Materials & Mining – Extracting lithium, cobalt, and rare earth metals for solar panels and batteries disturbs ecosystems, depletes resources, and contaminates water sources. ❇️ Water Usage – Mining, especially for lithium, is highly water-intensive, worsening water security in vulnerable regions. ❇️ Human Rights – Many materials come from regions with unethical labour practices. Responsible sourcing is key. ❇️ E-Waste & Circularity – Solar panels have a 25-30 year lifespan. Without recycling systems, they risk becoming the next waste crisis. ❇️ Energy Justice – Large solar farms can displace communities or prioritise profit over equitable energy access. Solar remains vital for the energy transition, but true sustainability means addressing these hidden impacts as well. The solutions should balance clean energy with nature conservation, ethical sourcing, and circular economy principles. If you want to learn more about systems thinking, visit: https://lnkd.in/d3SVnu4N https://lnkd.in/dM5Pzqej

I’m excited to share this new work from our IBM Quantum team in collaboration with Oak Ridge National Laboratory. This is a major demonstration of what we mean by realizing useful Quantum-centric supercomputing. Building on the chemistry work developed with RIKEN (https://lnkd.in/eK8jW-Wp) last year, and the previous Krylov demonstration with University of Tokyo (https://lnkd.in/eae_8zGc), the IBM Quantum and ORNL teams developed a quantum algorithm for ground states with convergence guarantees similar to phase estimation, while retaining the error mitigation aspect of sample-based methods. Putting together sample-based approaches and Krylov methods, we call this sample-based Krylov quantum diagonalization (SKQD). The algorithm can be used to compute ground state energies of quantum systems for many lattice models relevant in materials science and high-energy physics. SKQD is demonstrated experimentally on 85 qubits and 6,000 two-qubit gates on IBM quantum processors, against the ground state of the Anderson impurity model, obtaining high accuracies for problem sizes beyond the reach of exact diagonalization. This marks one of the largest implementations of quantum diagonalization to date, and points at how quantum computing, combined with classical computation in quantum-centric supercomputing environments, will enable us to push beyond classical methods for interesting applications. These new results also show again how algorithmic discovery is essential, especially for quantum-centric supercomputing architectures. Classical algorithms for materials science have made an impressive progress in the last decades. However, by thinking of quantum-classical workflows where quantum can deliver a value that cannot be matched by classical, we will move closer to demonstrating quantum advantage. Congratulations again to the team on this achievement. Check out the paper here: https://lnkd.in/epwCrG5R.

Stone Chipping in Substations: The Most Overlooked Safety Feature. When you walk into a PMU, the first thing you’ll notice under your feet is stone chipping. At first glance, it may look like just a layer of gravel for landscaping or neatness — but in reality, it’s one of the most important safety features in the entire substation. These stones are carefully chosen and placed to control step potential, touch potential, and surface insulation so that dangerous fault currents don’t put lives at risk. In this video, I’ll explain the real function of stone chipping inside a PMU and why it’s considered a silent protector for engineers and workers on site. By understanding this, you’ll see that stone chipping isn’t just about covering the ground — it’s about creating a safer working environment and ensuring the reliability of the high-voltage system Others Video related to 132kV System : 132kV Single Line Drawing and how to draw it: https://lnkd.in/grzBxqH3 132kV Numbering for Equipment and how to recognised it : https://lnkd.in/gtST9RCM 132kV Common Primary Equipment : https://lnkd.in/gjrCNZaE 132kV Side View: https://lnkd.in/gciSbDMM 132kv AIS Vs GIS Substation: https://lnkd.in/gtad7ZaU Different Between AIS & GIS Substation : https://lnkd.in/g3WsBVEK Surge Arrestor and its Function : https://lnkd.in/g8UecrJS Capacitive Voltage Transformer (CVT) and its function : https://lnkd.in/gWhm2y56 Line isolator function : https://lnkd.in/gHbzXngA Current Transformer https://lnkd.in/gUXSkGDP 132kv Circuit Breaker : https://lnkd.in/g8Tu4w5t Want to join my Class about 132kV System? : https://lnkd.in/grFNwj-z

🔋 SOLAR EVOLUTION: FROM SILICON TO TITANIUM ☀️ The solar industry is undergoing a silent but powerful transformation. ✅ From Mono PERC to HJT and TOPCon ✅ From silicon cells to bifacial gain and tandem efficiency ✅ And now… to next-gen breakthroughs like Perovskite and Titanium–Selenium solar modules from Japan, promising up to 30–35% efficiency with corrosion resistance and lower material cost. Here’s how the solar landscape is shifting: 🌞 Current Tech (2025) ▪️ Mono PERC → Reliable, cost-effective ▪️ TOPCon → Better bifaciality, N-type power ▪️ HJT → Premium efficiency, low degradation ▪️ Bifacial Systems → Smart gains from albedo 🚀 Emerging Tech (2028–30) ▪️ Perovskite–Silicon Tandems → Flexible, printable, 28%+ lab efficiency ▪️ Titanium–Selenium Panels → Abundant materials, high power density, Japan’s cutting-edge innovation ▪️ Organic PV, Quantum Dots → Building-integrated, niche futuristic roles ♻️ What’s Changing? 🔹 Shift from rare & toxic to abundant, recyclable materials 🔹 Focus on lightweight, flexible, glass-integrated solar 🔹 Race to build next-gen panels for AI, data centers & urban facades 🇮🇳 India is not behind. IIT Kanpur, IIT Bombay, and NCPRE are working on non-toxic perovskite solar, transparent solar glass, and circular energy solutions — paving the way for a more sustainable and self-reliant future. As a renewable energy entrepreneur, I believe the next big disruption will come not just from cost — but from material science, design integration, and sustainable sourcing. 📈 Are you tracking how fast your panels will become legacy hardware? Let’s power the future with smarter choices. #SolarEnergy #TitaniumSolar #Perovskite #HJT #TOPCon #Sustainability #Renewables #CleanTech #AtaruRenewPower #Innovation #FutureOfEnergy Bhavita Shukla , Akashsingh Rajput , Nisarg Bhavsar , Dr. Hitesh Doshi , Avaada Electro , Relaince Industries Limited , Adani Solar , Cecil Augustine , Panasonic India , Havells India Ltd , Polycab India Limited , Hitachi Energy , Aalok Chokshi , RenewSys India Pvt. Ltd. , ReNew , Samir Patel - BE Mech. MBA, CE , Siddharth Shah

🔍 Understanding Solar Panel Efficiency & Performance Metrics! ⚡ Choosing the right solar panel isn’t just about type—it’s also about efficiency and performance. In this post, we’ll break down key metrics that determine a panel’s output, longevity, and reliability. 1️⃣ Solar Panel Efficiency – What Does It Mean? Efficiency (%) = (Power Output / Sunlight Input) × 100 🔹 Definition: Efficiency represents how much of the sunlight hitting the panel is converted into usable electricity. 🔹 Typical Range: 15-22% for most commercial panels. 🔹 Higher Efficiency = More Power from Less Space ✅ Factors Affecting Efficiency: ✔️ Cell Type – Monocrystalline panels offer the highest efficiency. ✔️ Temperature Coefficient – Lower heat tolerance improves performance. ✔️ Anti-Reflective Coatings – Reduce light loss for better energy capture. ✔️ PERC & Bifacial Tech – Improve light absorption and rear-side generation. 2️⃣ Performance Ratio (PR) – Evaluating Real-World Efficiency PR = (Actual Output / Theoretical Output) × 100 🔹 Definition: A measure of how efficiently the system operates in real-world conditions. 🔹 Typical PR Values: 75-90% (higher is better). 🔹 A lower PR indicates losses due to shading, temperature, soiling, or system inefficiencies. ✅ Ways to Improve PR: ✔️ Keep panels clean and free from dust/debris. ✔️ Use high-quality inverters with optimal MPPT tracking. ✔️ Minimize wiring losses with proper cable sizing. 3️⃣ Temperature Coefficient – Why Heat Affects Output 🔹 Definition: Measures the power loss for every 1°C increase above STC (25°C). 🔹 Typical Range: -0.30%/°C to -0.50%/°C (lower is better). 🔹 Example: If a panel has a -0.4%/°C coefficient and reaches 40°C, power output drops by 6%. ✅ How to Reduce Heat Losses? ✔️ Choose panels with a lower temperature coefficient. ✔️ Ensure proper air circulation under panels for cooling. ✔️ Use light-colored rooftops or reflective ground surfaces. 4️⃣ Degradation Rate – Understanding Long-Term Performance 🔹 Definition: The rate at which a panel’s power output declines over time. 🔹 Typical Rate: 0.3%-0.8% per year. 🔹 After 25 Years: Most high-quality panels still operate at 80-90% of their original capacity. ✅ Factors Affecting Degradation: ✔️ UV exposure and material aging. ✔️ Thermal cycling and humidity. ✔️ Quality of encapsulation and backsheet. ✅ Choosing Low-Degradation Panels: ✔️ Look for Tier-1 manufacturers with <0.5%/year degradation. ✔️ Review IEC 61215 & IEC 61730 certified panels. ✔️ Check warranty terms for linear degradation guarantees. 5️⃣ Fill Factor (FF) – Indicator of Cell Quality FF = (Vmp × Imp) / (Voc × Isc) 🔹 Definition: Measures how well a panel converts voltage and current into usable power. 🔹 Typical Range: 70-80% (higher is better). ✅ Improving Fill Factor: ✔️ Use high-quality, low-resistance wiring. ✔️ Ensure proper MPPT operation in the inverter. ✔️ Avoid partial shading on module strings.

Tuning Magnetism with Voltage: A Breakthrough for Spintronic Neuromorphic Circuits Key Points: • Researchers have discovered a way to control magnetism in the quantum material lanthanum strontium manganite (LSMO) using applied voltage. • LSMO is magnetic and metallic at low temperatures but becomes non-magnetic and insulating when warmer. • The application of voltage creates distinct magnetic regions, challenging the conventional understanding that magnetism is not voltage-responsive. • The research was published in Nano Letters. Why It Matters This discovery could lead to energy-efficient control of magnetic properties, paving the way for spintronic neuromorphic circuits—electronic systems that mimic the brain’s information processing. What to Know • Quantum materials like LSMO exhibit unique properties governed by quantum mechanics. • By applying voltage, researchers found they could dynamically tune magnetism in different regions of the same material. • This approach differs from traditional methods that use magnetic fields to control magnetism. Insights & Implications • The ability to tune magnetism with voltage offers a new approach to low-power computing, especially in neuromorphic and spintronic devices. • The technique could enhance next-generation AI hardware, where energy-efficient, brain-like processing is essential. • This work represents a major step toward voltage-controlled spintronics, which could revolutionize memory storage, logic circuits, and AI-driven computing.