{"id":41006,"date":"2026-11-04T13:13:38","date_gmt":"2026-11-04T13:13:38","guid":{"rendered":"https:\/\/itbusinesstoday.com\/?p=41006"},"modified":"2026-11-04T13:13:38","modified_gmt":"2026-11-04T13:13:38","slug":"ai-for-scientific-discovery-how-machine-learning-is-accelerating-materials-and-chemical-research","status":"publish","type":"post","link":"https:\/\/itbusinesstoday.com\/ja\/tech\/ai\/ai-for-scientific-discovery-how-machine-learning-is-accelerating-materials-and-chemical-research\/","title":{"rendered":"\u79d1\u5b66\u7684\u767a\u898b\u306e\u305f\u3081\u306eAI\uff1a\u6a5f\u68b0\u5b66\u7fd2\u304c\u6750\u6599\u30fb\u5316\u5b66\u7814\u7a76\u3092\u3044\u304b\u306b\u52a0\u901f\u3055\u305b\u3066\u3044\u308b\u304b"},"content":{"rendered":"

What if the very material we need is already there, but we just haven’t found it? It’s estimated that there are more than \\(10^{60}\\) possible small molecules in chemical space alone, a vast region of chemical space that eclipses anything we can synthesize and screen using the traditional approach to chemistry and materials discovery.<\/p>

\u79d1\u5b66\u7684\u767a\u898b\u306e\u305f\u3081\u306e\u6a5f\u68b0\u5b66\u7fd2\u306f\u3001\u3053\u306e\u30d1\u30e9\u30c0\u30a4\u30e0\u306b\u6311\u3093\u3067\u3044\u308b\u3002\u6a5f\u68b0\u5b66\u7fd2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3001\u79d1\u5b66\u8005\u304c\u5b9f\u9a13\u5ba4\u3067\u8cb4\u91cd\u306a\u6642\u9593\u3092\u8cbb\u3084\u3057\u3066\u5b9f\u969b\u306b\u6271\u3046\u524d\u306b\u3001\u5206\u5b50\u306e\u6319\u52d5\u3092\u4e88\u6e2c\u3057\u3001\u5019\u88dc\u3068\u306a\u308b\u7269\u8cea\u3084\u65b0\u305f\u306a\u7814\u7a76\u5206\u91ce\u3092\u7cbe\u67fb\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002.<\/p>

\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u6a5f\u68b0\u5b66\u7fd2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u4ed5\u7d44\u307f\u3001\u6750\u6599\u79d1\u5b66\u3084\u5316\u5b66\u306e\u7814\u7a76\u306b\u304a\u3044\u3066\u5177\u4f53\u7684\u306a\u6210\u679c\u3092\u3082\u305f\u3089\u3057\u305f\u5206\u91ce\u3001\u305d\u3057\u3066\u4e88\u6e2c\u3092\u767a\u898b\u3078\u3068\u7d50\u3073\u3064\u3051\u308b\u4e0a\u3067\u5b9f\u9a13\u3084\u30c7\u30fc\u30bf\u304c\u3044\u304b\u306b\u4e0d\u53ef\u6b20\u3067\u3042\u308b\u304b\u306b\u3064\u3044\u3066\u8003\u5bdf\u3059\u308b\u3002.<\/p>

\u6a5f\u68b0\u5b66\u7fd2\u304c\u5316\u5b66\u3084\u7269\u8cea\u7269\u7406\u5b66\u3068\u3069\u306e\u3088\u3046\u306b\u7d50\u3073\u3064\u304f\u304b\u3001\u305d\u306e\u4e2d\u6838\u3068\u306a\u308b\u4ed5\u7d44\u307f<\/h3>

\"Core-Mechanics\"\u6a5f\u68b0\u5b66\u7fd2\u3092\u7528\u3044\u3066\u7279\u6027\u3092\u4e88\u6e2c\u3059\u308b\u969b\u3001\u30e2\u30c7\u30eb\u304c\u307e\u305a\u884c\u308f\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3053\u3068\u306e1\u3064\u306f\u3001\u69cb\u9020\u3092\u53d6\u308a\u8fbc\u307f\u3001\u305d\u308c\u3092\u30e2\u30c7\u30eb\u304c\u7406\u89e3\u3067\u304d\u308b\u8a00\u8a9e\u3067\u8868\u73fe\u3059\u308b\u3053\u3068\u3060\u3002 \u4f8b\u3068\u3057\u3066\u306f\u3001\u5206\u5b50\u3092\u8868\u3059\u300cSMILES\u300d\u3068\u547c\u3070\u308c\u308b\u4e00\u9023\u306e\u5358\u8a9e\u3001\u539f\u5b50\u306e\u96fb\u8377\u3084\u8ddd\u96e2\u3092\u8868\u3059\u300c\u30af\u30fc\u30ed\u30f3\u884c\u5217\u300d\u3068\u547c\u3070\u308c\u308b\u4e00\u9023\u306e\u6570\u5024\u3001\u539f\u5b50\u3092\u30ce\u30fc\u30c9\u3001\u7d50\u5408\u3092\u30a8\u30c3\u30b8\u3068\u3059\u308b\u30b0\u30e9\u30d5\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u30e2\u30c7\u30eb\u3001\u5206\u5b50\u306e\u5f62\u72b6\u3092\u6349\u3048\u305f3D\u30dc\u30af\u30bb\u30eb\u30e2\u30c7\u30eb\u306a\u3069\u304c\u6319\u3052\u3089\u308c\u308b\u3002.<\/p>

\u6b21\u306e\u8ab2\u984c\u306f\u3001\u91cf\u5b50\u8a08\u7b97\u306b\u304b\u304b\u308b\u30b3\u30b9\u30c8\u3060\u3002SchNet\u3001PaiNN\u3001M3GNet\u3068\u3044\u3063\u305f\u30e2\u30c7\u30eb\u306f\u3001\u65e2\u5b58\u306e\u8a08\u7b97\u7d50\u679c\u304b\u3089\u5b66\u7fd2\u3057\u3066\u30a8\u30cd\u30eb\u30ae\u30fc\u3001\u529b\u3001\u30d0\u30f3\u30c9\u30ae\u30e3\u30c3\u30d7\u306a\u3069\u306e\u7279\u6027\u3092\u63a8\u5b9a\u3059\u308b\u305f\u3081\u3001\u30b3\u30b9\u30c8\u306e\u304b\u304b\u308b\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u7e70\u308a\u8fd4\u3057\u884c\u3046\u5fc5\u8981\u6027\u3092\u6e1b\u3089\u3059\u3053\u3068\u304c\u3067\u304d\u308b\u3002. Microsoft’s<\/a> Skala 1.1\u306f\u3001\u95a2\u9023\u3057\u3064\u3064\u3082\u72ec\u81ea\u306e\u30a2\u30d7\u30ed\u30fc\u30c1\u3092\u63a1\u7528\u3057\u3066\u3044\u308b\u3002\u305d\u306e\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u4ea4\u63db\u76f8\u95a2\u6c4e\u95a2\u6570\u306f\u300155\u306eGMTKN55\u30d9\u30f3\u30c1\u30de\u30fc\u30af\u30ab\u30c6\u30b4\u30ea\u306e\u3046\u306132\u30671\u4f4d\u3068\u306a\u308a\u3001\u52a0\u91cd\u5e73\u5747\u8aa4\u5dee\u306f2.8 kcal\/mol\u3067\u3042\u3063\u305f\u3002\u3053\u308c\u306fDFT\u306b\u53d6\u3063\u3066\u4ee3\u308f\u308b\u306e\u3067\u306f\u306a\u304f\u3001DFT\u3092\u6539\u826f\u3059\u308b\u3082\u306e\u3067\u3042\u308b\u3002.<\/p>

\u7814\u7a76\u8005\u306f\u691c\u7d22\u306e\u65b9\u6cd5\u3092\u5909\u66f4\u3067\u304d\u308b\u3002\u30d5\u30a9\u30ef\u30fc\u30c9\u30b9\u30af\u30ea\u30fc\u30cb\u30f3\u30b0\u3067\u306f\u3001\u5019\u88dc\u3092\u751f\u6210\u3057\u3001\u305d\u306e\u7279\u6027\u3092\u691c\u8a3c\u3059\u308b\u3002\u9006\u8a2d\u8a08\u3067\u306f\u3001\u671b\u307e\u3057\u3044\u7279\u6027\u304b\u3089\u51fa\u767a\u3057\u3001\u901a\u5e38\u306f\u751f\u6210\u30e2\u30c7\u30eb\u3092\u7528\u3044\u3066\u3001\u305d\u306e\u7279\u6027\u3092\u793a\u3059\u53ef\u80fd\u6027\u306e\u3042\u308b\u69cb\u9020\u3092\u8a2d\u8a08\u3059\u308b\u3002\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304c\u5c0f\u3055\u3044\u5834\u5408\u306f\u3001\u30e9\u30f3\u30c0\u30e0\u30d5\u30a9\u30ec\u30b9\u30c8\u3084\u30ac\u30a6\u30b9\u904e\u7a0b\u306a\u3069\u306e\u624b\u6cd5\u304c\u59a5\u5f53\u3067\u3042\u308b\u3002\u4e00\u65b9\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u306f\u3001\u6df1\u5c64\u7b49\u5909\u91cf\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u304c\u6709\u52b9\u306b\u6a5f\u80fd\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u3002.<\/p>

\u7523\u696d\u306e\u6700\u524d\u7dda\u3092\u5909\u9769\u3059\u308b\u5b9f\u793e\u4f1a\u3067\u306e\u5fdc\u7528<\/h3>

AI\u3092\u7528\u3044\u305f\u6750\u6599\u63a2\u7d22\u306e\u771f\u306e\u53ef\u80fd\u6027\u306f\u3001\u7814\u7a76\u304c\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u4e0a\u306e\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u304b\u3089\u3001\u5b9f\u969b\u306e\u7523\u696d\u4e0a\u306e\u8ab2\u984c\u306e\u89e3\u6c7a\u3078\u3068\u79fb\u884c\u3057\u305f\u3068\u304d\u306b\u660e\u3089\u304b\u306b\u306a\u308b\u3002\u305d\u306e\u4e00\u4f8b\u3068\u3057\u3066\u3001\u30a8\u30cd\u30eb\u30ae\u30fc\u8caf\u8535\u6280\u8853\u304c\u6319\u3052\u3089\u308c\u308b\u3002\u3053\u308c\u3092\u5229\u7528\u3059\u308b\u3053\u3068\u306f\u53ef\u80fd\u3060 \u6a5f\u68b0\u5b66\u7fd2<\/a> \u30a4\u30aa\u30f3\u4f1d\u5c0e\u6027\u306b\u95a2\u3059\u308b\u56fa\u4f53\u96fb\u89e3\u8cea\u306e\u691c\u8a0e\u3001\u56fa\u4f53\u96fb\u89e3\u8cea\u754c\u9762\u306e\u5f62\u6210\u30e1\u30ab\u30cb\u30ba\u30e0\u306e\u89e3\u660e\u3001\u304a\u3088\u3073\u30c7\u30f3\u30c9\u30e9\u30a4\u30c8\u5f62\u6210\u3092\u6291\u5236\u3067\u304d\u308b\u6750\u6599\u306e\u767a\u898b\u3092\u884c\u3046\u305f\u3081\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3067\u3042\u308b\u3002\u3055\u3089\u306b\u3001\u5e0c\u5c11\u91d1\u5c5e\u3092\u5fc5\u8981\u3068\u3057\u306a\u3044\u6b63\u6975\u6750\u6599\u3092\u63a2\u3059\u969b\u306b\u3082\u6709\u7528\u3067\u3042\u308b\u3002\u3068\u306f\u3044\u3048\u3001\u6709\u671b\u306a\u5019\u88dc\u7269\u8cea\u306b\u3064\u3044\u3066\u306f\u3001\u305d\u306e\u6709\u7528\u6027\u3092\u7acb\u8a3c\u3059\u308b\u305f\u3081\u306b\u96fb\u6c17\u5316\u5b66\u7684\u306a\u8a66\u9a13\u3092\u884c\u3046\u5fc5\u8981\u304c\u3042\u308b\u3002.<\/p>

\u6a5f\u68b0\u5b66\u7fd2\u304c\u6d3b\u7528\u3055\u308c\u308b\u53ef\u80fd\u6027\u306e\u3042\u308b\u3082\u3046\u4e00\u3064\u306e\u4f8b\u306f\u3001\u89e6\u5a92\u53cd\u5fdc\u3060\u3002\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u7528\u3044\u308c\u3070\u3001\u89e6\u5a92\u306e\u8868\u9762\u3068\u306e\u5206\u5b50\u9593\u76f8\u4e92\u4f5c\u7528\u3092\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3057\u3001\u6c34\u7d20\u767a\u751f\u53cd\u5fdc\u3092\u901a\u3058\u3066\u6c34\u7d20\u306e\u751f\u6210\u3092\u4fc3\u9032\u3059\u308b\u6750\u6599\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002\u540c\u69d8\u306b\u3001\u4e8c\u9178\u5316\u70ad\u7d20\u3092\u6355\u6349\u3057\u305f\u308a\u3001\u6709\u7528\u306a\u7269\u8cea\u306b\u5909\u63db\u3057\u305f\u308a\u3067\u304d\u308b\u6750\u6599\u3092\u898b\u3064\u3051\u308b\u969b\u306b\u3082\u3001\u6a5f\u68b0\u5b66\u7fd2\u304c\u6d3b\u7528\u3055\u308c\u308b\u3002.<\/p>

Materials used in electronics offer a third frontier. High-thermal-conductivity polymers, dielectric materials and organic semiconductors all require specific combinations of properties. Microsoft’s MatterSim-based workflow demonstrates how this search can narrow down candidates. It screened more than 240,000<\/a> \u6750\u6599\u3092\u8abf\u67fb\u3057\u3001\u30bf\u30f3\u30bf\u30eb\u30fb\u30ea\u30f3\uff08TaP\uff09\u3092\u6f5c\u5728\u7684\u306a\u9ad8\u71b1\u4f1d\u5c0e\u7387\u6750\u6599\u3068\u3057\u3066\u7279\u5b9a\u3057\u305f\u3002 \u5b9f\u9a13\u6e2c\u5b9a\u306e\u7d50\u679c\u3001\u305d\u306e\u71b1\u4f1d\u5c0e\u7387\u306f152 W\/m\/K\u3067\u3042\u308b\u3053\u3068\u304c\u78ba\u8a8d\u3055\u308c\u305f\u3002TaP\u81ea\u4f53\u306f\u4ee5\u524d\u304b\u3089\u77e5\u3089\u308c\u3066\u3044\u305f\u304c\u3001\u672c\u7814\u7a76\u306b\u3088\u308a\u3001\u3053\u308c\u307e\u3067\u6ce8\u76ee\u3055\u308c\u3066\u3044\u306a\u304b\u3063\u305f\u6709\u671b\u306a\u7279\u6027\u304c\u660e\u3089\u304b\u306b\u306a\u3063\u305f\u3002\u3053\u3053\u3053\u305d\u304c\u3001\u8a08\u7b97\u306b\u3088\u308b\u30b9\u30af\u30ea\u30fc\u30cb\u30f3\u30b0\u3068\u5b9f\u9a13\u7684\u306b\u6e2c\u5b9a\u53ef\u80fd\u306a\u6750\u6599\u6027\u80fd\u3092\u7d50\u3073\u3064\u3051\u308b\u3001\u79d1\u5b66\u7684\u767a\u898b\u306e\u305f\u3081\u306eAI\u304c\u6709\u7528\u3068\u306a\u308b\u70b9\u3067\u3042\u308b\u3002.<\/p>

\u6a5f\u68b0\u5b66\u7fd2\u3068\u81ea\u5f8b\u8d70\u884c\u5b9f\u9a13\u65bd\u8a2d\u306e\u7d71\u5408\u306b\u3088\u308b\u9589\u30eb\u30fc\u30d7<\/h3>

\u6709\u671b\u306a\u4e88\u6e2c\u3067\u3042\u3063\u3066\u3082\u3001\u5b9f\u9a13\u5ba4\u3067\u306e\u691c\u8a3c\u306b\u8010\u3048\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3002\u3053\u3053\u3067\u3001\u81ea\u5f8b\u578b\u5b9f\u9a13\u5ba4\u304c\u7814\u7a76\u30d7\u30ed\u30bb\u30b9\u3092\u4e00\u65b0\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u3002\u5f7c\u3089\u306e\u69cb\u60f3\u3067\u306f\u30014\u3064\u306e\u6bb5\u968e\u304c\u30b7\u30fc\u30e0\u30ec\u30b9\u306a\u30eb\u30fc\u30d7\u3092\u5f62\u6210\u3057\u3066\u3044\u308b\u3002\u751f\u6210AI\u304c\u5019\u88dc\u3068\u306a\u308b\u6750\u6599\u3092\u751f\u307f\u51fa\u3057\u3001\u30ed\u30dc\u30c3\u30c8\u30b7\u30b9\u30c6\u30e0\u304c\u5408\u6210\u3092\u884c\u3044\u3001\u81ea\u52d5\u5316\u3055\u308c\u305f\u5206\u5149\u5206\u6790\u3068X\u7dda\u56de\u6298\u306b\u3088\u3063\u3066\u305d\u306e\u7d50\u679c\u304c\u691c\u8a3c\u3055\u308c\u3001\u30d9\u30a4\u30b8\u30a2\u30f3\u30fb\u30a2\u30af\u30c6\u30a3\u30d6\u30e9\u30fc\u30cb\u30f3\u30b0\u304c\u30c7\u30fc\u30bf\u3092\u5206\u6790\u3057\u3066\u6b21\u306e\u8a66\u9a13\u306b\u5099\u3048\u308b\u3002.<\/p>

The benefit is that each experiment can inform the next. Rather than conducting a broad, random experiment, active learning can determine which experiment will offer the most information and erase as much uncertainty as possible. That ensures that scientists aren’t throwing away reagents or hours of lab time on candidates that will add little, if any, value. This also tackles one of virtual screening’s biggest weaknesses: a material’s apparent stability in a simulation that could easily not crystallize or synthesize in real-world lab conditions.<\/p>

\u305d\u306e\u3088\u3046\u306a\u610f\u601d\u6c7a\u5b9a\u304c\u3069\u306e\u3088\u3046\u306b\u884c\u308f\u308c\u308b\u304b\u306e\u4e00\u4f8b\u306f\u3001 IBM’s<\/a> \u7814\u7a76\u3002\u540c\u793e\u306f\u3001\u7b2c\u4e00\u539f\u7406\u306b\u57fa\u3065\u304f\u96fb\u5b50\u8f38\u9001\u8a08\u7b97\u3001\u534a\u6559\u5e2b\u3042\u308a\u7d50\u6676\u30b0\u30e9\u30d5\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3001\u304a\u3088\u3073\u30d9\u30a4\u30ba\u6700\u9069\u5316\u3092\u7528\u3044\u3066\u300110\u30ca\u30ce\u30e1\u30fc\u30c8\u30eb\u4ee5\u4e0b\u306e\u5bf8\u6cd5\u306b\u304a\u3051\u308b\u534a\u5c0e\u4f53\u306e\u30d0\u30c3\u30af\u30a8\u30f3\u30c9\u30fb\u30aa\u30d6\u30fb\u30e9\u30a4\u30f3\uff08BEOL\uff09\u914d\u7dda\u7528\u306e\u30c8\u30dd\u30ed\u30b8\u30ab\u30eb\u6750\u6599\u5019\u88dc\u3092\u7279\u5b9a\u3057\u305f\u3002\u3053\u3046\u3057\u305f\u624b\u6cd5\u306f\u3001\u7269\u7406\u7684\u306a\u8a66\u9a13\u304c\u59cb\u307e\u308b\u524d\u306b\u3001\u53ef\u80fd\u6027\u306e\u7bc4\u56f2\u3092\u7d5e\u308a\u8fbc\u3080\u306e\u306b\u5f79\u7acb\u3064\u3002 \u304a\u305d\u3089\u304f\u3001\u3055\u3089\u306a\u308b\u53ef\u80fd\u6027\u306f\u3001\u3053\u308c\u3089\u306e\u4e88\u6e2c\u3092\u81ea\u52d5\u5316\u3055\u308c\u305f\u5b9f\u9a13\u3068\u7d50\u3073\u3064\u3051\u3001\u30b7\u30b9\u30c6\u30e0\u304c\u5b9f\u4e16\u754c\u306e\u7d50\u679c\u304b\u3089\u5b66\u7fd2\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u3053\u3068\u306b\u3042\u308b\u3002.<\/p>

\u6280\u8853\u7684\u306a\u30dc\u30c8\u30eb\u30cd\u30c3\u30af\u3068\u79d1\u5b66\u7684\u306a\u5b89\u5168\u7b56<\/h3>

\u3042\u3089\u3086\u308b\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u7cbe\u5ea6\u306f\u3001\u305d\u306e\u30e2\u30c7\u30eb\u304c\u89e3\u91c8\u3067\u304d\u308b\u6761\u4ef6\u3084\u30c7\u30fc\u30bf\u306b\u5de6\u53f3\u3055\u308c\u308b\u3002\u3053\u306e\u305f\u3081\u3001\u7814\u7a76\u8005\u304c\u65b0\u3057\u3044\u5316\u5b66\u69cb\u9020\u3084\u7269\u8cea\u306e\u7d44\u6210\u3092\u7406\u89e3\u3057\u3088\u3046\u3068\u3059\u308b\u969b\u3001\u8ab2\u984c\u304c\u751f\u3058\u308b\u3002\u65e2\u5b58\u306e\u30e2\u30c7\u30eb\u306f\u3001\u65b0\u898f\u306e\u4e8b\u4f8b\u3084\u5206\u5e03\u5916\u306e\u4e8b\u4f8b\u306b\u5bfe\u3057\u3066\u4e0d\u6b63\u78ba\u306a\u4e88\u6e2c\u3092\u884c\u3046\u53ef\u80fd\u6027\u304c\u9ad8\u304f\u3001\u6642\u306b\u306f\u6570\u5b66\u7684\u306b\u306f\u6709\u671b\u3068\u898b\u306a\u3055\u308c\u308b\u65b0\u3057\u3044\u69cb\u9020\u3092\u63a8\u5b9a\u3057\u3066\u3082\u3001\u5b9f\u969b\u306b\u306f\u7269\u7406\u7684\u306b\u751f\u6210\u4e0d\u53ef\u80fd\u306a\u5834\u5408\u304c\u3042\u308b\u3002.<\/p>

\u30c7\u30fc\u30bf\u306e\u8cea\u3082\u307e\u305f\u3001\u5225\u306e\u8ab2\u984c\u3068\u306a\u3063\u3066\u3044\u308b\u3002\u7cbe\u5ea6\u306e\u9ad8\u3044\u5b9f\u9a13\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f\u3001\u4f9d\u7136\u3068\u3057\u3066\u53ce\u96c6\u304c\u56f0\u96e3\u3067\u3042\u308a\u3001\u4f5c\u6210\u306b\u306f\u591a\u984d\u306e\u8cbb\u7528\u304c\u304b\u304b\u308a\u3001\u591a\u304f\u306e\u5834\u5408\u3001\u5b66\u8853\u30ea\u30dd\u30b8\u30c8\u30ea\u5185\u306b\u5b64\u7acb\u3057\u3066\u3044\u308b\u3002\u307e\u305f\u3001\u767a\u8868\u3055\u308c\u305f\u8ad6\u6587\u3067\u306f\u3001\u6210\u529f\u3057\u305f\u5408\u6210\u4f8b\u306e\u307f\u304c\u53d6\u308a\u4e0a\u3052\u3089\u308c\u3001\u5931\u6557\u4f8b\u306b\u3064\u3044\u3066\u306f\u5341\u5206\u306b\u5831\u544a\u3055\u308c\u3066\u3044\u306a\u3044\u50be\u5411\u304c\u3042\u308b\u3002\u3053\u306e\u305f\u3081\u3001\u30e2\u30c7\u30eb\u304c\u300c\u4f55\u304c\u3046\u307e\u304f\u3044\u304b\u306a\u3044\u304b\u300d\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u5f97\u308b\u6a5f\u4f1a\u304c\u5236\u9650\u3055\u308c\u3066\u3057\u307e\u3046\u3002.<\/p>

There is also a gap between theoretical stability and practical synthesizability. A structure may appear thermodynamically stable in a simulation, yet the reaction conditions may prevent researchers from producing it. Microsoft’s RetroChimera addresses part of this challenge by predicting plausible synthesis routes. It achieved 90%<\/a> \u5316\u5b66\u8005\u305f\u3061\u304c\u63d0\u6848\u3055\u308c\u305f\u5408\u6210\u7d4c\u8def\u3092\u8a55\u4fa1\u3057\u305f\u30d6\u30e9\u30a4\u30f3\u30c9\u8a55\u4fa1\u306b\u304a\u3044\u3066\u3001\u5c02\u9580\u5bb6\u304b\u3089\u9ad8\u3044\u8a55\u4fa1\u3092\u5f97\u305f\u3002\u3057\u304b\u3057\u3001\u3053\u308c\u306f90%\u306e\u5b9f\u9a13\u5ba4\u3067\u306e\u5408\u6210\u6210\u529f\u7387\u3092\u793a\u3059\u3082\u306e\u3067\u306f\u306a\u3044\u3002\u7d50\u5c40\u306e\u3068\u3053\u308d\u3001AI\u306b\u3088\u308b\u4e88\u6e2c\u3092\u79d1\u5b66\u7684\u306a\u767a\u898b\u3068\u3057\u3066\u6271\u3046\u306b\u306f\u3001\u5b9f\u9a13\u306b\u3088\u308b\u88cf\u4ed8\u3051\u304c\u5fc5\u8981\u3060\u3002.<\/p>

\u7814\u7a76\u6a5f\u95a2\u306b\u304a\u3051\u308b\u6226\u7565\u306e\u5b9f\u884c<\/h3>

\"Strategic\"\u7814\u7a76\u6a5f\u95a2\u306f\u3001\u30b9\u30b1\u30fc\u30e9\u30d6\u30eb\u306a\u30b7\u30b9\u30c6\u30e0\u3092\u5c0e\u5165\u3059\u308b\u524d\u306b\u3001\u8cea\u306e\u9ad8\u3044\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3092\u69cb\u7bc9\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b AI<\/a> \u79d1\u5b66\u7684\u306a\u554f\u984c\u306b\u5bfe\u3057\u3066\u3002FAIR\u306e\u539f\u5247\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f\u3088\u308a\u898b\u3064\u3051\u3084\u3059\u304f\u306a\u308a\u3001\u30a2\u30af\u30bb\u30b9\u3057\u3084\u3059\u304f\u306a\u308a\u3001\u76f8\u4e92\u904b\u7528\u6027\u304c\u9ad8\u307e\u308a\u3001\u518d\u5229\u7528\u3057\u3084\u3059\u304f\u306a\u308b\u3060\u3051\u3067\u306a\u304f\u3001\u305d\u306e\u30c7\u30fc\u30bf\u3092\u751f\u6210\u3057\u305f\u5b9f\u9a13\u306b\u3064\u3044\u3066\u3082\u900f\u660e\u6027\u304c\u9ad8\u307e\u308b\u3002\u3082\u3061\u308d\u3093\u3001\u57fa\u790e\u3068\u306a\u308b\u8a3c\u62e0\u304c\u3069\u306e\u3088\u3046\u306b\u5f97\u3089\u308c\u305f\u304b\u3092\u793a\u3059\u3001\u7d50\u679c\u306b\u95a2\u3059\u308b\u5305\u62ec\u7684\u306a\u8a18\u9332\u304c\u5b58\u5728\u3059\u3079\u304d\u3060\u3002.<\/p>

IBM considers these data principles when designing a four-step data pipeline for chemistry and materials research that introduces candidate data sets, assesses the scientific quality, establishes expert validation and generates new data where existing evidence isn’t enough.<\/p>

\u3053\u3061\u3089\u3082\u304a\u8aad\u307f\u304f\u3060\u3055\u3044\uff1a \u30ac\u30a4\u30c9\u30ef\u30a4\u30e4\u30fc\u3001\u82f1\u56fd\u306e\u4fdd\u967aAI\u4f01\u696dhyperexponential\u3092\u8cb7\u53ce\u3078<\/a><\/h4>

\u3055\u3089\u306b\u3001\u7814\u7a76\u8005\u305f\u3061\u306f\u3001\u4fdd\u5b58\u5247\u3084\u71b1\u529b\u5b66\u7684\u6027\u8cea\u3001\u5bfe\u79f0\u6027\u3092\u8003\u616e\u3057\u305f\u7269\u7406\u60c5\u5831\u578b\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\uff08PINN\uff09\u3092\u5b66\u7fd2\u3055\u305b\u308b\u3053\u3068\u3067\u3001\u3088\u308a\u7269\u7406\u7684\u306b\u6574\u5408\u6027\u304c\u3042\u308a\u3001\u73fe\u5b9f\u7684\u306a\u30e2\u30c7\u30eb\u3092\u69cb\u7bc9\u3067\u304d\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u3002\u305d\u306e\u305f\u3081\u306b\u306f\u3001\u5316\u5b66\u8005\u3001\u6750\u6599\u79d1\u5b66\u8005\u3001\u6a5f\u68b0\u5b66\u7fd2\u306e\u5c02\u9580\u5bb6\u9593\u306e\u5354\u529b\u304c\u5fc5\u8981\u3068\u306a\u308b\u3002.<\/p>

\u79d1\u5b66\u7684\u767a\u898b\u306e\u672a\u6765\u306f\u3001\u4eba\u9593\u3068AI\u306e\u5354\u50cd\u306b\u304b\u304b\u3063\u3066\u3044\u308b<\/h3>

AI will not instantly bring predictable research to the discovery of new medicines or new materials. Models can guide exploration, highlight potential new structures, and cut down on the number of repetitive experiments, but they can’t decide if this will be useful, or marketable. That’s for scientists who grasp the physics and chemistry that underpins it. The ability to free up researchers’ time, so they can challenge \u4e88\u6e2c<\/a>, \u3001\u7570\u5e38\u3092\u8abf\u67fb\u3057\u3001\u30a2\u30a4\u30c7\u30a2\u3092\u8a66\u3059\u3053\u3068\u3053\u305d\u304c\u3001AI\u306e\u771f\u306e\u53ef\u80fd\u6027\u3060\u3002AI\u306f\u529b\u696d\u7684\u306a\u63a2\u7d22\u306e\u591a\u304f\u3092\u62c5\u3046\u3053\u3068\u304c\u3067\u304d\u308b\u304c\u3001\u5c02\u9580\u77e5\u8b58\u3068\u76f4\u611f\u306f\u4f9d\u7136\u3068\u3057\u3066\u5fc5\u8981\u3068\u3055\u308c\u308b\u3060\u308d\u3046\u3002.<\/p>

 <\/p>

 <\/p>","protected":false},"excerpt":{"rendered":"

What if the very material we need is already there, but we just haven’t found it? It’s estimated that there are more than \\(10^{60}\\) possible small molecules in chemical space alone, a vast region of chemical space that eclipses anything we can synthesize and screen using the traditional approach to chemistry and materials discovery.Machine learning for scientific discovery is challenging this paradigm. Machine learning algorithms are capable of predicting the behavior of molecules and sifting through candidate materials and frontiers before scientists spend valuable time in the lab working with them.In this article, we look at how machine learning algorithms work, where they have had a tangible effect on research […]<\/p>\n","protected":false},"author":6,"featured_media":41012,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"wprm-recipe-roundup-name":"","wprm-recipe-roundup-description":"","postBodyCss":"","postBodyMargin":[],"postBodyPadding":[],"postBodyBackground":{"backgroundType":"classic","gradient":""},"footnotes":""},"categories":[186,8098,85],"tags":[16709,1066,328,224,16708],"ppma_author":[325],"class_list":["post-41006","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","category-news-articles","category-tech","tag-ai-driven","tag-ibm","tag-machine-learning","tag-microsoft","tag-quantum-calculations"],"yoast_head":"\nMachine Learning Speeds Up Materials Discovery<\/title>\n<meta name=\"description\" content=\"Machine learning is helping researchers accelerate materials discovery, improve chemical analysis, and advance scientific research.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/itbusinesstoday.com\/ja\/tech\/ai\/ai-for-scientific-discovery-how-machine-learning-is-accelerating-materials-and-chemical-research\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Machine Learning Speeds Up Materials Discovery\" \/>\n<meta property=\"og:description\" content=\"Machine learning is helping researchers accelerate materials discovery, improve chemical analysis, and advance scientific research.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/itbusinesstoday.com\/ja\/tech\/ai\/ai-for-scientific-discovery-how-machine-learning-is-accelerating-materials-and-chemical-research\/\" \/>\n<meta property=\"og:site_name\" content=\"itbusinesstoday\" \/>\n<meta property=\"article:published_time\" content=\"2026-11-04T13:13:38+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/itbusinesstoday.com\/wp-content\/uploads\/2026\/11\/AI-for-Scientific-Discovery-How-Machine-Learning-is-Accelerating-Materials-and-Chemical-Research-1.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"800\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Ren Yamaguchi\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ren Yamaguchi\" \/>\n\t<meta name=\"twitter:label2\" 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