Energy Sciences
Parent: Lawrence Berkeley National Laboratory
eScholarship stats: Breakdown by Item for September through December, 2024
Item | Title | Total requests | Download | View-only | %Dnld |
---|---|---|---|---|---|
4xq057pv | A decarboxylative approach for regioselective hydroarylation of alkynes | 2,845 | 1,191 | 1,654 | 41.9% |
6mq3j474 | High-volume natural volcanic pozzolan and limestone powder as partial replacements for portland cement in self-compacting and sustainable concrete | 569 | 41 | 528 | 7.2% |
3cs0m4vr | Atomic Resolution Imaging with a sub-50 pm Electron Probe | 562 | 15 | 547 | 2.7% |
3h26p692 | Commentary: The Materials Project: A materials genome approach to accelerating materials innovation | 466 | 60 | 406 | 12.9% |
0w02253p | Understanding interface stability in solid-state batteries | 412 | 389 | 23 | 94.4% |
9zn3q96n | Chelation and stabilization of berkelium in oxidation state plus IV | 400 | 29 | 371 | 7.3% |
30v0j6cc | Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis | 289 | 188 | 101 | 65.1% |
9q83p4fg | Flexible Electronics toward Wearable Sensing | 243 | 219 | 24 | 90.1% |
51w3s3s1 | Thin-film ferroelectric materials and their applications | 238 | 208 | 30 | 87.4% |
6b4839bp | A bicarbonate-rich liquid condensed phase in non-saturated solutions in the absence of divalent cations. | 231 | 4 | 227 | 1.7% |
4q9585s0 | Wearable sweat sensors | 229 | 169 | 60 | 73.8% |
0r27j85x | Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices | 219 | 135 | 84 | 61.6% |
6p2408jt | Hydroxylation of the surface of PbS nanocrystals passivated with oleic acid | 214 | 30 | 184 | 14.0% |
308097nb | Design principles for enabling an anode-free sodium all-solid-state battery | 208 | 152 | 56 | 73.1% |
65v9z5vp | Accelerating the discovery of materials for clean energy in the era of smart automation | 208 | 64 | 144 | 30.8% |
9wh2w9rg | X-Ray Interactions: Photoabsorption, Scattering, Transmission and Reflection E = 50-30,000 eV, Z = 1-92 | 198 | 126 | 72 | 63.6% |
4t59495x | Supramolecular assembly of blue and green halide perovskites with near-unity photoluminescence | 192 | 72 | 120 | 37.5% |
6jn170sr | Matminer: An open source toolkit for materials data mining | 188 | 64 | 124 | 34.0% |
7b00f0nt | Promises and Challenges of Next-Generation “Beyond Li-ion” Batteries for Electric Vehicles and Grid Decarbonization | 186 | 91 | 95 | 48.9% |
3tr9v1wc | Lithium-Ion Battery Supply Chain Considerations: Analysis of Potential Bottlenecks in Critical Metals | 175 | 54 | 121 | 30.9% |
9wn3w79b | Advances in molecular quantum chemistry contained in the Q-Chem 4 program package | 174 | 162 | 12 | 93.1% |
9xd827xp | Mechanism of CO2 Reduction at Copper Surfaces: Pathways to C2 Products | 174 | 36 | 138 | 20.7% |
55g1h87k | Metal–Organic Frameworks for Electrocatalytic Reduction of Carbon Dioxide | 164 | 49 | 115 | 29.9% |
4cn657t1 | Atomic layer etching of SiO2 with Ar and CHF 3 plasmas: A self‐limiting process for aspect ratio independent etching | 163 | 100 | 63 | 61.3% |
0fr1q984 | Temperature-adaptive radiative coating for all-season household thermal regulation | 162 | 61 | 101 | 37.7% |
18h3f02f | Ultrathin ferroic HfO2–ZrO2 superlattice gate stack for advanced transistors | 162 | 104 | 58 | 64.2% |
95r3v8xk | Efficient hydrogen peroxide generation using reduced graphene oxide-based oxygen reduction electrocatalysts | 162 | 70 | 92 | 43.2% |
3ft5f2jx | Toughening materials: enhancing resistance to fracture | 161 | 15 | 146 | 9.3% |
082091b4 | Unsupervised word embeddings capture latent knowledge from materials science literature | 155 | 39 | 116 | 25.2% |
6rw4t3cw | Emerging exciton physics in transition metal dichalcogenide heterobilayers | 154 | 56 | 98 | 36.4% |
72972402 | An Algorithm for the Extraction of Tafel Slopes | 154 | 37 | 117 | 24.0% |
42n664kt | Enabling ultra-low-voltage switching in BaTiO3 | 152 | 68 | 84 | 44.7% |
945633cg | Polymers with Tailored Electronic Structure for High Capacity Lithium Battery Electrodes | 149 | 66 | 83 | 44.3% |
07h5f8vn | Preparing for the Next Generation of EUV Lithography at the Center for X-ray Optics | 148 | 64 | 84 | 43.2% |
2nx8r6pz | Engineered Recognition of Tetravalent Zirconium and Thorium by Chelator–Protein Systems: Toward Flexible Radiotherapy and Imaging Platforms | 148 | 15 | 133 | 10.1% |
4212s92j | Carbon capture and storage (CCS): the way forward | 146 | 51 | 95 | 34.9% |
5jn8d415 | Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis | 146 | 120 | 26 | 82.2% |
05d359b4 | Two-dimensional perovskite templates for durable, efficient formamidinium perovskite solar cells | 145 | 44 | 101 | 30.3% |
0kd1p37x | A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy | 145 | 125 | 20 | 86.2% |
4x44d9j0 | 4D-STEM of Beam-Sensitive Materials | 145 | 71 | 74 | 49.0% |
1gm2n89d | Advances in the growth and characterization of magnetic, ferroelectric, and multiferroic oxide thin films | 144 | 44 | 100 | 30.6% |
2vs0h0wg | Cooperative insertion of CO2 in diamine-appended metal-organic frameworks | 144 | 82 | 62 | 56.9% |
4554h9vj | Local lattice distortions and the structural instabilities in bcc Nb–Ta–Ti–Hf high-entropy alloys: An ab initio computational study | 143 | 129 | 14 | 90.2% |
3cz511v8 | Prospects for Employing Lithium Copper Phosphates as High-Voltage Li-Ion Cathodes | 142 | 7 | 135 | 4.9% |
1596g9zr | Tailored catalyst microenvironments for CO2 electroreduction to multicarbon products on copper using bilayer ionomer coatings | 141 | 34 | 107 | 24.1% |
8bb4g1gk | Semiconductor nanowire lasers | 141 | 39 | 102 | 27.7% |
6gp6b287 | Operando studies reveal active Cu nanograins for CO2 electroreduction | 140 | 112 | 28 | 80.0% |
7dm4g62g | Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction | 140 | 68 | 72 | 48.6% |
3618r7gc | Diffusion and migration in polymer electrolytes | 138 | 38 | 100 | 27.5% |
3pd0h9nt | Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals | 135 | 117 | 18 | 86.7% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.