{"id":7122,"date":"2026-08-06T13:51:44","date_gmt":"2026-08-06T04:51:44","guid":{"rendered":"https:\/\/matlantis.com\/ja\/?post_type=news&p=7122"},"modified":"2026-08-06T13:51:45","modified_gmt":"2026-08-06T04:51:45","slug":"acs-fall-2026","status":"publish","type":"news","link":"https:\/\/matlantis.com\/ja\/news\/acs-fall-2026\/","title":{"rendered":"ACS Fall 2026 \u767a\u8868\u306e\u304a\u77e5\u3089\u305b"},"content":{"rendered":"\n

Matlantis\u682a\u5f0f\u4f1a\u793e\u306f\u30012026\u5e748\u670823\u65e5\uff5e8\u670827\u65e5\uff08\u7c73\u56fd\u4e2d\u90e8\u590f\u6642\u9593\uff0fCDT\uff09\u306b\u7c73\u56fd\u30b7\u30ab\u30b4\uff08McCormick Place Convention Center\uff09\u3067\u958b\u50ac\u3055\u308c\u308b\u300cACS Fall 2026\u300d\u306b\u304a\u3044\u3066\u30011\u540d\u306e\u30e1\u30f3\u30d0\u30fc\u304c\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u304a\u3088\u3073\u53e3\u982d\u767a\u8868\u3092\u884c\u3044\u307e\u3059\u3002\u5185\u5bb9\u306f\u4ee5\u4e0b\u3054\u53c2\u7167\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n

\u30d7\u30ec\u30bc\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\u8a73\u7d30\u2460\uff08\u30dd\u30b9\u30bf\u30fc\u767a\u8868\uff1aSci-Mix\uff09<\/h2>\n\n\n\n

\u30eb\u30fc\u30e0: <\/strong>Hall F2 \u2013 POSTERS\uff08McCormick Place Convention Center\uff09<\/p>\n\n\n\n

\u30dd\u30b9\u30bf\u30fc\u30dc\u30fc\u30c9\u756a\u53f7: <\/strong>1506<\/p>\n\n\n\n

\u767a\u8868\u8005 1: <\/strong>\u677e\u672c \u7693\u592a\uff08Kota Matsumoto\uff09<\/p>\n\n\n\n

\u30bb\u30c3\u30b7\u30e7\u30f3: <\/strong>ENFL Sci-Mix<\/p>\n\n\n\n

\u65e5\u6642: <\/strong>2026\u5e748\u670824\u65e5\uff08\u6708\uff098:00 PM \u2013 10:00 PM\uff08\u7c73\u56fd\u4e2d\u90e8\u590f\u6642\u9593\uff0fCDT\uff09
\u3000\u3000 \u203b\u65e5\u672c\u6642\u9593\uff1a8\u670825\u65e5\uff08\u706b\uff0910:00 \u2013 12:00<\/p>\n\n\n\n

\u90e8\u9580: <\/strong>ENFL: Division of Energy and Fuels<\/p>\n\n\n\n

\u30bb\u30c3\u30b7\u30e7\u30f3\u30bf\u30a4\u30d7: <\/strong>\u30dd\u30b9\u30bf\u30fc\uff08Sci-Mix\uff09<\/p>\n\n\n\n

\u30bf\u30a4\u30c8\u30eb: <\/strong>Analysis of structural stability and irreversible structural transformations in Li-ion battery cathode materials using a universal machine-learning interatomic potential and autonomous transformation pathway exploration<\/p>\n\n\n\n

\u203b Sci-Mix\u306f\u3001\u5404\u90e8\u9580\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u59d4\u54e1\u9577\u304c\u63a1\u629e\u6f14\u984c\u306e\u4e2d\u304b\u3089\u9078\u51fa\u3057\u305f\u512a\u79c0\u6f14\u984c\u306e\u307f\u3067\u69cb\u6210\u3055\u308c\u308b\u90e8\u9580\u6a2a\u65ad\u578b\u306e\u30dd\u30b9\u30bf\u30fc\u30bb\u30c3\u30b7\u30e7\u30f3\u3067\u3059\u3002<\/p>\n\n\n\n

\u30d7\u30ec\u30bc\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\u8a73\u7d30\u2461\uff08\u53e3\u982d\u767a\u8868\uff09<\/h2>\n\n\n\n

\u30eb\u30fc\u30e0: <\/strong>N134\uff08McCormick Place Convention Center\uff09<\/p>\n\n\n\n

\u767a\u8868\u8005 1: <\/strong>\u677e\u672c \u7693\u592a\uff08Kota Matsumoto\uff09<\/p>\n\n\n\n

\u30bb\u30c3\u30b7\u30e7\u30f3: <\/strong>Earth-Abundant and Low-Cost Rechargeable Battery Chemistries<\/p>\n\n\n\n

\u65e5\u6642: <\/strong>2026\u5e748\u670826\u65e5\uff08\u6c34\uff093:30 PM \u2013 3:45 PM\uff08\u7c73\u56fd\u4e2d\u90e8\u590f\u6642\u9593\uff0fCDT\uff09\u3000
\u3000\u3000 \u203b\u65e5\u672c\u6642\u9593\uff1a8\u670827\u65e5\uff08\u6728\uff095:30 \u2013 5:45<\/p>\n\n\n\n

\u90e8\u9580: <\/strong>ENFL: Division of Energy and Fuels<\/p>\n\n\n\n

\u30bb\u30c3\u30b7\u30e7\u30f3\u30bf\u30a4\u30d7: <\/strong>\u30aa\u30fc\u30e9\u30eb<\/p>\n\n\n\n

\u30bf\u30a4\u30c8\u30eb: <\/strong>Analysis of structural stability and irreversible structural transformations in Li-ion battery cathode materials using a universal machine-learning interatomic potential and autonomous transformation pathway exploration<\/p>\n\n\n\n

\u6982\u8981<\/h2>\n\n\n\n

[Introduction]<\/h4>\n\n\n\n

Extending usable capacity in lithium-ion batteries hinges on preventing irreversible structural change in the cathode. Layered rock-salt oxides LiMO\u2082 (M = Ni, Co, Mn) dominate commercial use, yet lose capacity through transition-metal migration that triggers phase change, typified by layered-to-spinel conversion. Because the kinetics are governed by individual hopping barriers, resolving the atomistic sequence of migration events is a prerequisite for rational stabilization by doping. Such events carry barriers far too high for direct MD. NEB, the standard alternative, requires end points and an initial path to be specified and copes poorly with the pronounced cell-shape changes involved; earlier work has therefore been confined to assumed mechanisms such as dumbbell formation, leaving unknown intermediates undiscovered. SC-AFIR removes both restrictions \u2014 automatic exhaustive search, access to high barriers, tolerance of lattice deformation \u2014 but its use for periodic solids has been throttled by DFT cost. Here we lift that constraint by driving SC-AFIR with a machine-learning interatomic potential (MLIP).<\/p>\n\n\n\n

[Method]<\/h4>\n\n\n\n

SC-AFIR in GRRM20 was coupled to the universal MLIP Matlantis PFP (hereafter PFP), enumerating minima and connecting transition states without prior mechanistic assumptions.<\/p>\n\n\n\n

[Results and Discussion]<\/h4>\n\n\n\n

For Li\u2080.\u2085CoO\u2082, where Co displacement into the Li layer beyond 50% Li extraction caps practical capacity, the search yielded 1,008 minima and 1,882 pathways, from which the kinetically dominant layered-to-spinel route was extracted (Fig. 1). Its highest barrier \u2014 the first Co hop \u2014 was ~1.5 eV for a 14-atom cell, in line with published values. Notably, the favored route is multistep, passing through square-pyramidally coordinated Co and Co at an octahedral site in the Li layer \u2014 intermediates inaccessible to assumed-pathway calculations. Dopant effects and other cathode compositions will also be presented.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u767a\u8868\u8005\u30d7\u30ed\u30d5\u30a3\u30fc\u30eb<\/h2>\n\n\n\n

\u677e\u672c \u7693\u592a\uff08\u307e\u3064\u3082\u3068 \u3053\u3046\u305f\uff09<\/h4>\n\n\n\n

Matlantis\u682a\u5f0f\u4f1a\u793e \u30ab\u30b9\u30bf\u30de\u30fc\u30b5\u30af\u30bb\u30b9\u30a8\u30f3\u30b8\u30cb\u30a2<\/strong><\/p>\n\n\n\n

\u5317\u6d77\u9053\u5927\u5b66\u5927\u5b66\u9662\u7dcf\u5408\u5316\u5b66\u9662\u4fee\u4e86\u5f8c\u3001ENEOS\u682a\u5f0f\u4f1a\u793e\u306b\u5165\u793e\u3057\u3001\u8a08\u7b97\u5316\u5b66\u306b\u3088\u308b\u6750\u6599\u958b\u767a\u306e\u7814\u7a76\u304a\u3088\u3073Matlantis\u306e\u691c\u8a3c\u958b\u767a\u3001\u306a\u3089\u3073\u306b\u300cGRRM20 with Matlantis\u300d\u306e\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9\u958b\u767a\u306b\u643a\u308f\u308b\u3002\u305d\u306e\u5f8c\u3001\u682a\u5f0f\u4f1a\u793ePreferred Computational Chemistry\uff08\u73fe\u30fbMatlantis\u682a\u5f0f\u4f1a\u793e\uff09\u306b\u5165\u793e\u3002\u73fe\u5728\u306f\u30ab\u30b9\u30bf\u30de\u30fc\u30b5\u30af\u30bb\u30b9\u30a8\u30f3\u30b8\u30cb\u30a2\u3068\u3057\u3066\u3001Matlantis\u3092\u4f7f\u7528\u3057\u305f\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u958b\u767a\u306b\u5f93\u4e8b\u3002<\/p>\n","protected":false},"featured_media":7150,"template":"","meta":{"_acf_changed":false},"news_category":[2],"class_list":["post-7122","news","type-news","status-publish","has-post-thumbnail","hentry","news_category-event-seminar"],"acf":[],"_links":{"self":[{"href":"https:\/\/matlantis.com\/ja\/wp-json\/wp\/v2\/news\/7122","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/matlantis.com\/ja\/wp-json\/wp\/v2\/news"}],"about":[{"href":"https:\/\/matlantis.com\/ja\/wp-json\/wp\/v2\/types\/news"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/matlantis.com\/ja\/wp-json\/wp\/v2\/media\/7150"}],"wp:attachment":[{"href":"https:\/\/matlantis.com\/ja\/wp-json\/wp\/v2\/media?parent=7122"}],"wp:term":[{"taxonomy":"news_category","embeddable":true,"href":"https:\/\/matlantis.com\/ja\/wp-json\/wp\/v2\/news_category?post=7122"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}