01581nas a2200145   4500008004100000245011300041210006900154260000900223300001100232490000700243520102200250100001901272700001801291856012601309       2025                        eng d00aMH-PCTpro: a machine learning model for rapid prediction of pressure-composition-temperature (PCT) isotherms0 aMHPCTpro a machine learning model for rapid prediction of pressu  cAPR   a1122510 v283 a<p>
	We present a machine-learning powered Metal Hydride's Pressure-Composition-Temperature isotherm Predictor (MH-PCTpro) for metal compositions. To train the MH-PCTpro, an experimental database of PCT isotherms is built from published literature. The database comprises over 14,000 data points extracted from 237 PCT isotherms representing 138 distinct compositions. The dataset encompasses more than 25 elements and spans a broad spectrum of absorption temperatures (263-653 K) and hydrogen pressures (0.001-40 MPa). The model is validated on a wide range of alloy families and its predictions are consistent with experimental results. The model also captures temperature-dependent variations in plateau pressure, enabling determination of enthalpy and entropy of hydride formation through Van't Hoff plots. Hence, MH-PCTpro can be used as an ML tool for guiding PCT experiments, offering PCT isotherm predictions and valuable thermodynamic insights into materials suitable for solid-state hydrogen storage.</p>
1 aVerma, Ashwini1 aJoshi, Kavita  uhttps://library.ncl.res.in/content/mh-pctpro-machine-learning-model-rapid-prediction-pressure-composition-temperature-pct