Bibliographic record
Abstract
Low cost NMR sensor for measuring moisture content of forest products. The Department of Energy (DOE) Industries of the Future (IOF) program seeks development and implementation of technologies that make industry more efficient--in particular, more energy-efficient. Quantum Magnetics, Inc. (QM), a wholly-owned subsidiary of GE Security, received an award under the program to investigate roles for low-cost Nuclear Magnetic Resonance (NMR) technology in furtherance of these goals. Most NMR systems are designed for high-resolution spectroscopy applications. These systems use intense magnetic fields produced by superconducting magnets that drive price and operating cost to levels beyond industry tolerance. At low magnetic fields, achievable at low cost, one loses the ability to obtain spectroscopic information. However, measuring the time constants associated with the NMR signal, called NMR relaxometry, gives indications of chemical and physical states of interest to process control and optimization. It was the purpose of this effort to investigate the technical and economic feasibility of using such low-field, low-cost NMR to monitor parameters enabling greater process efficiencies. The primary target industry identified in the Cooperative Development Agreement was the wood industry, where the moisture content of wood is a key process parameter from the time the cut tree enters a mill until the time it is delivered as pieces of lumber. Extracting the moisture is energy consuming, and improvements in drying efficiency stand to reduce costs and emissions substantially. QM designed and developed a new, low-cost NMR instrument suitable for inspecting lumber up to 3 inches by 12 inches in cross section, and other materials of similar size. Low cost is achieved via an inexpensive, permanent magnet and low-cost NMR spectrometer electronics. Laboratory testing demonstrated that the NMR system is capable of accurate ({+-} 0.5%) measurements of the moisture content of wood for moisture ranging from 2% to over 140% (referenced to the wood's dry weight). Accuracy exceeded that offered by existing instrumentation when the moisture content was in excess of the fiber saturation point ({approx}20%). Accuracy was independent of the wood form: solid wood, wood chips or sawdust. The prototype NMR system was designed and built for incorporation and use in a beta test site. Beta testing is under way at the pilot plant operated by the Pulp and Paper Research Institute of Canada (PAPRICAN) in Vancouver, B.C. Other industries were also investigated. For example, laboratory testing demonstrated that low-field NMR is capable of measuring the hydrogen content of calcium oxide (quicklime). Hydrogen content measurement can be done both rapidly (on the order of 1 second) and nondestructively. Measurement of moisture in quicklime affects energy consumption in the steel industry. Further advances in system electronics, ongoing under DOD support, will enable yet more substantial system cost reductions over the prototype system, opening up a wider range of utility.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".